ALBERT

Description: Remote Sensing, Vol. 10, Pages 1171: Multi-Criteria Evaluation of Snowpack Simulations in Complex Alpine Terrain Using Satellite and In Situ Observations Remote Sensing doi: 10.3390/rs10081171 Authors: Jesús Revuelto Grégoire Lecourt Matthieu Lafaysse Isabella Zin Luc Charrois Vincent Vionnet Marie Dumont Antoine Rabatel Delphine Six Thomas Condom Samuel Morin Alessandra Viani Pascal Sirguey This work presents an extensive evaluation of the Crocus snowpack model over a rugged and highly glacierized mountain catchment (Arve valley, Western Alps, France) from 1989 to 2015. The simulations were compared and evaluated using in-situ point snow depth measurements, in-situ seasonal and annual glacier surface mass balance, snow covered area evolution based on optical satellite imagery at 250 m resolution (MODIS sensor), and the annual equilibrium-line altitude of glaciers, derived from satellite images (Landsat, SPOT, and ASTER). The snowpack simulations were obtained using the Crocus snowpack model driven by the same, originally semi-distributed, meteorological forcing (SAFRAN) reanalysis using the native semi-distributed configuration, but also a fully distributed configuration. The semi-distributed approach addresses land surface simulations for discrete topographic classes characterized by elevation range, aspect, and slope. The distributed approach operates on a 250-m grid, enabling inclusion of terrain shadowing effects, based on the same original meteorological dataset. Despite the fact that the two simulations use the same snowpack model, being potentially subjected to same potential deviation from the parametrization of certain physical processes, the results showed that both approaches accurately reproduced the snowpack distribution over the study period. Slightly (although statistically significantly) better results were obtained by using the distributed approach. The evaluation of the snow cover area with MODIS sensor has shown, on average, a reduction of the Root Mean Squared Error (RMSE) from 15.2% with the semi-distributed approach to 12.6% with the distributed one. Similarly, surface glacier mass balance RMSE decreased from 1.475 m of water equivalent (W.E.) for the semi-distributed simulation to 1.375 m W.E. for the distribution. The improvement, observed with a much higher computational time, does not justify the recommendation of this approach for all applications; however, for simulations that require a precise representation of snowpack distribution, the distributed approach is suggested.

Description: Remote Sensing, Vol. 10, Pages 1169: Multi-Year Analyses of Columnar Aerosol Optical and Microphysical Properties in Xi’an, a Megacity in Northwestern China Remote Sensing doi: 10.3390/rs10081169 Authors: Xiaoli Su Junji Cao Zhengqiang Li Kaitao Li Hua Xu Suixin Liu Xuehua Fan A thorough understanding of aerosol optical properties and their spatio-temporal variability are required to accurately evaluate aerosol effects in the climate system. In this study, a multi-year study of aerosol optical and microphysical properties was firstly performed in Xi’an based on three years of sun photometer remote sensing measurements from 2012 to 2015. The multi-year average of aerosol optical depth (AOD) at 440 nm was about 0.88 ± 0.24 (mean ± SD), while the averaged Ångström Exponent (AE) between 440 and 870 nm was 1.02 ± 0.15. The mean value of single scattering albedo (SSA) was around 0.89 ± 0.03. Aerosol optical depth and AE showed different seasonal variation patterns. Aerosol optical depth was slightly higher in winter (0.99 ± 0.36) than in other seasons (~0.85 ± 0.20), while AE showed its minimum in spring (0.85 ± 0.05) due to the impact of dust episodes. The seasonal variations of volume particle size distribution, spectral refractive index, SSA, and asymmetry factor were also analyzed to characterize aerosols over this region. Based on the aerosol products derived from sun photometer measurements, the classification of aerosol types was also conducted using two different methods in this region. Results show that the dominant aerosol types are absorbers in all seasons, especially in winter, demonstrating the strong absorptivity of aerosols in Xi’an.

Description: Remote Sensing, Vol. 10, Pages 1166: Inventory of Glaciers in the Shaksgam Valley of the Chinese Karakoram Mountains, 1970–2014 Remote Sensing doi: 10.3390/rs10081166 Authors: Haireti Alifu Yukiko Hirabayashi Brian Alan Johnson Jean-Francois Vuillaume Akihiko Kondoh Minoru Urai The Shaksgam Valley, located on the north side of the Karakoram Mountains of western China, is situated in the transition zone between the Indian monsoon system and dry arid climate zones. Previous studies have reported abnormal behaviors of the glaciers in this region compared to the global trend of glacier retreat, so the region is of special interest for glacier-climatological studies. For this purpose, long-term monitoring of glaciers in this region is necessary to obtain a better understanding of the relationships between glacier changes and local climate variations. However, accurate historical and up-to-date glacier inventory data for the region are currently unavailable. For this reason, this study conducted glacier inventories for the years 1970, 1980, 1990, 2000 and 2014 (i.e., a ~10-year interval) using multi-temporal remote sensing imagery. The remote sensing data used included Corona KH-4A/B (1965–1971), Hexagon KH-9 (1980), Landsat Thematic Mapper (TM) (1990/1993), Landsat Enhanced Thematic Mapper Plus (ETM+) (2000/2001), and Landsat Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) (2014/2015) multispectral satellite images, as well as digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM), DEMs generated from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images (2005–2014), and Advanced Land Observing Satellite (ALOS) World 3D 30 m mesh (AW3D30). In the year 2014, a total of 173 glaciers (including 121 debris-free glaciers) (>0.5 km2), covering an area of 1478 ± 34 km2 (area of debris-free glaciers: 295 ± 7 km2) were mapped. The multi-temporal glacier inventory results indicated that total glacier area change between 1970–2014 was not significant. However, individual glacier changes showed significant variability. Comparisons of the changes in glacier terminus position indicated that 55 (32 debris-covered) glaciers experienced significant advances (~40–1400 m) between 1970–2014, and 74 (32 debris-covered) glaciers experienced significant advances (~40–1400 m) during the most recent period (2000–2014). Notably, small glaciers showed higher sensitivity to climate changes, and the glaciers located in the western part of the study site were exhibiting glacier area expansion compared to other parts of the Shaksgam Valley. Finally, regression analyses indicated that topographic parameters were not the main driver of glacier changes. On the contrary, local climate variability could explain the complex behavior of glaciers in this region.

Description: Geosciences, Vol. 8, Pages 274: Cryomorphological Topographies in the Study of Ice Caves Geosciences doi: 10.3390/geosciences8080274 Authors: Manuel Gómez-Lende Manuel Sánchez-Fernández The current interest in ice caves requires that their varied manifestations be known as accurately as possible in view of their responses to a global change and also to their great potential as paleoenvironmental witnesses. This phenomenon has been known about for a long time but is still scarcely studied from the point of view of its cryological values and the evolution and distribution of many of their morphologies. For this, the development of cryomorphological topographies from traditional techniques to geodetic surveys with different tools, including terrestrial laser scanning, is one of the most current ways to characterize and quantify this type of cryospheric phenomena. It represents a new kind of periglacial cartography whose use is feasible in spite of the difficulties these environments present.

Description: Geosciences, Vol. 8, Pages 272: Towards National Archaeological Mapping. Assessing Source Data and Methodology—A Case Study from Scotland Geosciences doi: 10.3390/geosciences8080272 Authors: Łukasz Banaszek Dave C. Cowley Mike Middleton While the National Record of the Historic Environment (NRHE) in Scotland contains valuable information on more than 170,000 archaeological monuments, it is clear that this dataset is conditioned by the disposition of past survey and changing parameters of data collection strategies over many decades. This highlights the importance of creating systematic datasets, in which the standards to which they were created are explicit, and against which the reliability of our knowledge of the material remains of the past can be assessed. This paper describes issues of data structure and reliability, then discussing the methodologies under development for expediting the progress of national-scale mapping with specific reference to the Isle of Arran. Preliminary outcomes of a recent archaeological mapping project of the island, which has been used to develop protocols for rapid large area mapping, are outlined. The primary sources for the survey were airborne laser scanning derivatives and orthophotographs, supplemented by field observation, and the project has more than doubled the number of known monuments of Arran. The survey procedures are described, followed by a discussion of the utility of ‘general purpose’ remote sensed datasets, focusing on the assessment of strengths and weaknesses for rapid mapping of large areas.

Description: Geosciences, Vol. 8, Pages 273: The Caribbean’s Geotourism Potential and Challenges: A Focus on Two Islands in the Region Geosciences doi: 10.3390/geosciences8080273 Authors: Colmore S. Christian Geotourism is a relatively new concept in the tourism industry, a concept which apparently has not yet been formally embraced by Caribbean destinations. This paper, based primarily on a literature review supplemented by the first-hand knowledge of the author, who served for over a decade in the natural resource management and tourism sectors in the region, identifies some of the geotourism assets and assesses the geotourism potential of two selected Caribbean islands, namely the Commonwealth of Dominica and St. Lucia. Indications are that the islands of the region have outstanding geological formations, dormant and active volcanic zones and associated geomorphological features, and breath-taking terrestrial and marine landscapes, including deep river gorges and tall mountains, and beautiful beaches, which together constitute important geotourism assets. Currently, these resources are marketed and promoted as part of the region’s nature tourism attractions. The feasibility of incorporating geotourism as a component of this overall nature tourism thrust is explored in this paper. As a follow-up to this study a survey of tourism officials, natural resource professionals, and selected scientists of the region is proposed for the purpose of identifying the reasons and constraints preventing the Caribbean region from formally embracing geotourism, developing and promoting the geotourism resources of the region as a unique component of the overall tourism product.

Description: Minerals, Vol. 8, Pages 315: Biomineral Reactivity: The Kinetics of the Replacement Reaction of Biological Aragonite to Apatite Minerals doi: 10.3390/min8080315 Authors: Martina Greiner Lurdes Férnandez-Díaz Erika Griesshaber Moritz N. Zenkert Xiaofei Yin Andreas Ziegler Sabino Veintemillas-Verdaguer Wolfgang W. Schmahl We present results of bioaragonite to apatite conversion in bivalve, coral and cuttlebone skeletons, biological hard materials distinguished by specific microstructures, skeletal densities, original porosities and biopolymer contents. The most profound conversion occurs in the cuttlebone of the cephalopod Sepia officinalis, the least effect is observed for the nacreous shell portion of the bivalve Hyriopsis cumingii. The shell of the bivalve Arctica islandica consists of cross-lamellar aragonite, is dense at its innermost and porous at the seaward pointing shell layers. Increased porosity facilitates infiltration of the reaction fluid and renders large surface areas for the dissolution of aragonite and conversion to apatite. Skeletal microstructures of the coral Porites sp. and prismatic H. cumingii allow considerable conversion to apatite. Even though the surface area in Porites sp. is significantly larger in comparison to that of prismatic H. cumingii, the coral skeleton consists of clusters of dense, acicular aragonite. Conversion in the latter is sluggish at first as most apatite precipitates only onto its surface area. However, the process is accelerated when, in addition, fluids enter the hard tissue at centers of calcification. The prismatic shell portion of H. cumingii is readily transformed to apatite as we find here an increased porosity between prisms as well as within the membranes encasing the prisms. In conclusion, we observe distinct differences in bioaragonite to apatite conversion rates and kinetics depending on the feasibility of the reaction fluid to access aragonite crystallites. The latter is dependent on the content of biopolymers within the hard tissue, their feasibility to be decomposed, the extent of newly formed mineral surface area and the specific biogenic ultra- and microstructures.

Description: Minerals, Vol. 8, Pages 318: Mapping Surface Quartz Content in Sand Dunes Covered by Biological Soil Crusts Using Airborne Hyperspectral Images in the Longwave Infrared Region Minerals doi: 10.3390/min8080318 Authors: Shahar Weksler Offer Rozenstein Eyal Ben-Dor Biological soil crusts (BSCs), composed of cyanobacteria, algae, mosses, lichens, and fungi, are important ecosystem engineers that stabilize the quartz-rich dunes in the Nitzana study area near the Israel–Egypt border. The longwave infrared (LWIR) region of the electromagnetic spectrum is very useful for quartz identification since quartz reflectance in the visible, near infrared, and shortwave infrared (VIS-NIR-SWIR, 0.4–2.5 µm) spectral regions lacks identifying features, whereas in the LWIR region, the quartz emissivity spectrum presents a strong doublet feature. This emissivity feature can be used as a diagnostic tool for BSCs development in desert environments, because BSCs attenuate the quartz feature as a function of their successional development. A pair of day and night airborne hyperspectral images were acquired using the Specim AisaOWL LWIR sensor (7.7–12 µm) and processed using an innovative algorithm to reduce the atmospheric interference in this spectral domain. The resulting day and night apparent emissivity products were used to produce a surface quartz content map of the study area. The significant reduction in atmospheric interference resulted in a high correlation (R2 = 0.88) between quartz content in field samples determined by X-ray powder diffraction analysis and emissivity estimations from the airborne images. This, in turn, served as the ground truth to our quartz content map of the surface, and by proxy to the BSC.

Description: Minerals, Vol. 8, Pages 313: Reverse Flotation Separation of Fluorite from Calcite: A Novel Reagent Scheme Minerals doi: 10.3390/min8080313 Authors: Jianjun Wang Zihan Zhou Yuesheng Gao Wei Sun Yuehua Hu Zhiyong Gao Fluorite (CaF2), as an important strategic mineral source, is usually separated from calcite by the common froth flotation method, but this separation is still not selective enough. The development of a selective collector and/or depressant is the key to achieving high selective separation. 1-Hydroxyethylidene-1,1-diphosphonic acid (HEDP or H4L) is widely used as an environmentally friendly water treatment reagent due to its low cost and excellent anti-scaling performance in an aqueous solution. In this study, a novel reagent scheme was developed using HEDP as a fluorite depressant and sodium oleate (NaOL) as a calcite collector for the first time. When 3 × 10−5 mol/L of HEDP and 6 × 10−5 mol/L of NaOL were used at pH 6, the optimal selective separation for single minerals and mixed binary minerals was obtained. Zeta potential measurements indicated that HEDP possessed a stronger adsorption on fluorite than calcite, while NaOL did the opposite. This novel reagent scheme is of low cost, uses a small dosage, and is friendly to the environment, which makes it a promising reagent scheme for fluorite flotation in industrial application.

Description: Remote Sensing, Vol. 10, Pages 1181: Improved Albedo Estimates Implemented in the METRIC Model for Modeling Energy Balance Fluxes and Evapotranspiration over Agricultural and Natural Areas in the Brazilian Cerrado Remote Sensing doi: 10.3390/rs10081181 Authors: Bruno Silva Oliveira Elisabete Caria Moraes Marcos Carrasco-Benavides Gabriel Bertani Guilherme Augusto Verola Mataveli In this study we assessed METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model performance to estimate energy balance fluxes and evapotranspiration (ET) in two heterogeneous landscapes in the Brazilian Cerrado, including fluxes and ET in both agricultural and natural vegetation. The estimates were evaluated by comparing them to flux tower data collected over sugarcane (USR site), woody savanna (PDG site) and stricto-sensu savanna (RECOR site) areas. The selection of the study years (2005–2007 for USR/PDG sites and 2011–2015 for RECOR site) was based on the availability of meteorological data (to be used as inputs in METRIC) and of flux tower data for energy balance fluxes and ET comparisons. The broadband albedo submodel was adjusted in order to improve Net Radiation estimates. For this adjustment, we applied at-surface solar radiation simulations obtained from the SMARTS2 model under different conditions of land elevation, precipitable water content and solar angles. We also tested the equivalence between the measured crop coefficient (Kc_ec) and the reference evapotranspiration fraction (ETrF or F), seeking to extrapolate from instantaneous to daily values of actual evapotranspiration (ETa). Surface albedo was underestimated by 10% at the USR site (showing a better performance for full crop coverage), by 15% at the PDG site (following the woody savanna dynamics pattern through dry and wet seasons) and was overestimated by 21% at the RECOR site. METRIC was effective in simulating the spatial and temporal variability of energy balance fluxes and ET over agricultural and natural vegetation in the Brazilian Cerrado, with errors within those reported in the literature. Net radiation (Rn) presented consistent results (coefficient of determination (R2) > 0.94) but it was overestimated by 8% and 9% in sugarcane and woody savanna, respectively. METRIC-derived ET estimates showed an agreement with ground data at USR and PDG sites (R2 > 0.88, root mean square error (RMSE) up to 0.87 mm day−1), but at the RECOR site, ET was overestimated by 14% (R2 = 0.96, mean absolute error (MAE) = 0.62 mm.day−1 and RMSE = 0.75 mm day−1). Surface energy balance fluxes and ET were marked by seasonality, with direct dependence on available energy, rainfall distribution, soil moisture and other parameters like albedo and NDVI.

Description: Remote Sensing, Vol. 10, Pages 1182: Detection of Frozen Soil Using Sentinel-1 SAR Data Remote Sensing doi: 10.3390/rs10081182 Authors: Nicolas Baghdadi Hassan Bazzi Mohammad El Hajj Mehrez Zribi The objective of this paper is to evaluate the potential of Sentinel-1 Synthetic Aperture Radar “SAR” data (C-band) for monitoring agricultural frozen soils. First, investigations were conducted from simulated radar signal data using a SAR backscattering model combined with a dielectric mixing model. Then, Sentinel-1 images acquired at a study site near Paris, France were analyzed using temperature data to investigate the potential of the new Sentinel-1 SAR sensor for frozen soil mapping. The results show that the SAR backscattering coefficient decreases when the soil temperature drops below 0 °C. This decrease in signal is the most important for temperatures that ranges between 0 and −5 °C. A difference of at least 2 dB is observed between unfrozen soils and frozen soils. This difference increases under freezing condition when the temperature at the image acquisition date decreases. In addition, results show that the potential of the C-band radar signal for the discrimination of frozen soils slightly decreases when the soil moisture decreases (simulated data were used with soil moisture contents of 20 and 30 vol%). The difference between the backscattering coefficient of unfrozen soil and the backscattering coefficient of frozen soil decreases by approximately 1 dB when the soil moisture decreases from 30 to 20 vol%). Finally, the results show that both VV and VH allow a good detection of frozen soils but the sensitivity of VH is higher by approximately 1.5 dB. In conclusion, this study shows that the difference between a reference image acquired without freezing and an image acquired under freezing conditions is a good tool for detecting frozen soils.

Description: Atmosphere, Vol. 9, Pages 293: The Impact of Mount Washington on the Height of the Boundary Layer and the Vertical Structure of Temperature and Moisture Atmosphere doi: 10.3390/atmos9080293 Authors: Eric Kelsey Adriana Bailey Georgia Murray Discrimination of the type of air mass along mountain slopes can be a challenge and is not commonly performed, but is critical for identifying factors responsible for influencing montane weather, climate, and air quality. A field campaign to measure air mass type and transitions on the summit of Mount Washington, New Hampshire, USA was performed on 19 August 2016. Meteorological observations were taken at the summit and at several sites along the east and west slopes. Ozone concentrations were measured at the summit and on the valley floor. Additionally, water vapor stable isotopes were measured from a truck that drove up and down the Mount Washington Auto Road concurrent with radiosonde launches that profiled the free atmosphere. This multivariate perspective revealed thermal, moisture, and air mass height differences among the free atmosphere, leeward, and windward mountain slopes. Both thermally and mechanically forced upslope flows helped shape these differences by altering the height of the boundary layer with respect to the mountain surface. Recommendations for measurement strategies hoping to develop accurate observational climatologies of air mass exposure in complex terrain are discussed and will be important for evaluating elevation-dependent warming and improving forecasting for weather and air quality.

Description: Atmosphere, Vol. 9, Pages 292: A Mechanism of the Interdecadal Changes of the Global Low-Frequency Oscillation Atmosphere doi: 10.3390/atmos9080292 Authors: Ruowen Yang Quanliang Chen Yuyun Liu Lin Wang Based on the National Center for Environmental Prediction/National Center for Atmospheric Research reanalysis dataset from 1948 to 2009, this study reveals that global low-frequency oscillation features two major temporal bands. One is a quasi-60-day period known as the intraseasonal oscillation (ISO), and the other is a quasi-15-day period known as the quasi-biweekly oscillation (QBWO). After the mid-1970s, both the ISO and QBWO become intensified and more active, and these changes are equivalently barotropic. The primitive barotropic equations are adopted to study the involved mechanism. It reveals that the e-folding time of the least stable modes of both the ISO and QWBO becomes shorter if the model is solved under the atmospheric basic state after the mid-1970s than if solved under the basic state before the mid-1970s. This result suggests that the atmospheric basic flow after the mid-1970s facilitates a more rapid growth of the ISO and QBWO, and thereby an intensification of the low-frequency oscillations at the two bands.

Description: Atmosphere, Vol. 9, Pages 291: A Statistical Parameter Correction Technique for WRF Medium-Range Prediction of Near-Surface Temperature and Wind Speed Using Generalized Linear Model Atmosphere doi: 10.3390/atmos9080291 Authors: Jinmyeong Jeong Seung-Jae Lee A statistical post-processing method was developed to increase the accuracy of numerical weather prediction (NWP) and simulation by matching the daily distribution of predicted temperatures and wind speeds using the generalized linear model (GLM) and parameter correction, considering an increase in model bias when the range of the prediction time lengthens. The Land Atmosphere Modeling Package Weather Research and Forecasting model, which provides 12-day agrometeorological predictions for East Asia, was employed from May 2017 to April 2018. Training periods occurred one month prior to and after the test period (12 days). A probabilistic consideration accounts for the relatively short training period. Based on the total and monthly root mean square error values for each test site, the results show an improvement in the NWP accuracy after bias correction. The spatial distributions in July and January were compared in detail. It was also shown that the physical consistency between temperature and wind speed was retained in the correction procedure, and that the GLM exhibited better performance than the quantile matching method based on monthly Pearson correlation comparison. The characteristics of coastal and mountainous sites are different from inland automatic weather stations, indicating that supplements to cover these distinctive topographic locations are necessary.

Description: Minerals, Vol. 8, Pages 323: (10.4) Face of Ordered and Disordered Dolomite, MgCa(CO3)2: A Computational Study to Reveal the Growth Mechanism Minerals doi: 10.3390/min8080323 Authors: Marco Bruno Erica Bittarello In this study, the stability of the (10.4) face of dolomite was systematically investigated. The surface energies at 0 K of the different (10.4) surfaces resulting from the cut of both ordered and disordered bulk structures were determined and compared, to establish how different atomic configurations (surface terminations) can affect the stability of the investigated face. To study the thermodynamic behavior of a surface, a 2D periodic slab model and the ab initio CRYSTAL code were adopted. The surface energies of the (10.4) faces of calcite and magnesite were also calculated in order to compare them with those of the different terminations of the (10.4) face of dolomite. Our calculations showed that the bulk of the dolomite crystal must have an ordered structure to reach the minimum of the energy, whereas the (10.4) surface is more stable when its structure is disordered. A growth model of the (10.4) face has been proposed: the peculiarity of this model consists in the existence of some disordered layers forming at the interface crystal/solution, which arrange in an ordered structure once covered by others disordered layers resulting by the spiral steps propagation.

Description: Minerals, Vol. 8, Pages 322: Particle Size Distribution Effects on the Strength Characteristic of Cemented Paste Backfill Minerals doi: 10.3390/min8080322 Authors: Jiangyu Wu Meimei Feng Zhanqing Chen Xianbiao Mao Guansheng Han Yiming Wang It is of great significance, for economic, environmental and security reasons, to investigate the strength characteristic of underground cemented paste backfill (CPB). Consequently, an ultrasonic test, uniaxial and triaxial compression experiment, and acoustic emission (AE) monitoring were carried out on CPB, for which the particles satisfied Talbot gradation. The homogeneity of CPB specimens was evaluated by ultrasonic pulse velocity (UPV). The stress–strain behavior and AE characteristic of CPB specimens under different Talbot indices and confining pressures were investigated. The effects of the particle size distribution and the confining pressure on the peak strength of CPB were analyzed. The strength parameter model of CPB under the coupled influence of the particle size distribution and the confining pressure was constructed based on the Mohr–Coulomb strength criterion. The results show that the peak strength of CPB is positively linear with confining pressure, however, the relationship between its strength parameters and the Talbot index can be characterized by a quadratic polynomial function. This suggests that there is an optimal gradation of particles reflected in the maximum strength of CPB.

Description: Minerals, Vol. 8, Pages 319: Fault Zone Evolution and Development of a Structural and Hydrological Barrier: The Quartz Breccia in the Kiggavik Area (Nunavut, Canada) and Its Control on Uranium Mineralization Minerals doi: 10.3390/min8080319 Authors: Alexis Grare Olivier Lacombe Julien Mercadier Antonio Benedicto Marie Guilcher Anna Trave Patrick Ledru John Robbins In the Kiggavik area (Nunavut, Canada), major fault zones along, or close to, where uranium deposits are found are often associated with occurrence of thick quartz breccia (QB) bodies. These bodies formed in an early stage (~1750 Ma) of the long-lasting tectonic history of the Archean basement, and of the Proterozoic Thelon basin. The main characteristics of the QB are addressed in this study; through field work, macro and microscopic observations, cathodoluminescence microscopy, trace elements, and oxygen isotopic signatures of the quartz forming the QB. Faults formed earlier during syn- to post-orogenic rifting (1850–1750 Ma) were subsequently reactivated, and underwent cycles of cataclasis, pervasive silicification, hydraulic brecciation, and quartz recrystallization. This was synchronous with the circulation of meteoric fluids mixing with Si-rich magmatic-derived fluids at depth, and were coeval with the emplacement of the Kivalliq igneous suite at 1750 Ma. These processes led to the emplacement of up to 30 m thick QB, which behaved as a mechanically strong, transverse hydraulic barrier that localized later fracturing, and compartmentalized/channelized vertical flow of uranium-bearing fluids after the deposition of the Thelon Basin (post 1750 Ma). The development and locations of QB control the location of uranium mineralization in the Kiggavik area.

Description: IJGI, Vol. 7, Pages 300: A Comparative Study of Three Non-Geostatistical Methods for Optimising Digital Elevation Model Interpolation ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080300 Authors: Serajis Salekin Jack H. Burgess Justin Morgenroth Euan G. Mason Dean F. Meason It is common to generate digital elevation models (DEMs) from aerial laser scanning (ALS) data. However, cost and lack of knowledge may preclude its use. In contrast, global navigation satellite systems (GNSS) are seldom used to collect and generate DEMs. These receivers have the potential to be considered as data sources for DEM interpolation, as they can be inexpensive, easy to use, and mobile. The data interpolation method and spatial resolution from this method needs to be optimised to create accurate DEMs. Moreover, the density of GNSS data is likely to affect DEM accuracy. This study investigates three different deterministic approaches, in combination with spatial resolution and data thinning, to determine their combined effects on DEM accuracy. Digital elevation models were interpolated, with resolutions ranging from 0.5 m to 10 m using natural neighbour (NaN), topo to raster (ANUDEM), and inverse distance weighted (IDW) methods. The GNSS data were thinned by 25% (0.389 points m−2), 50% (0.259 points m−2), and 75% (0.129 points m−2) and resulting DEMs were contrast against a DEM interpolated from unthinned data (0.519 points m−2). Digital elevation model accuracy was measured by root mean square error (RMSE) and mean absolute error (MAE). It was found that the highest resolution, 0.5 m, produced the lowest errors in resulting DEMs (RMSE = 0.428 m, MAE = 0.274 m). The ANUDEM method yielded the greatest DEM accuracy from a quantitative perspective (RMSE = 0.305 m and MAE = 0.197 m); however, NaN produced a more visually appealing surface. In all the assessments, IDW showed the lowest accuracy. Thinning the input data by 25% and even 50% had relatively little impact on DEM quality; however, accuracy decreased markedly at 75% thinning (0.129 points m−2). This study showed that, in a time where ALS is commonly used to generate DEMs, GNSS-surveyed data can be used to create accurate DEMs. This study confirmed the need for optimization to choose the appropriate interpolation method and spatial resolution in order to produce a reliable DEM.

Description: Remote Sensing, Vol. 10, Pages 1186: Application of Multi-Sensor Satellite Data for Exploration of Zn–Pb Sulfide Mineralization in the Franklinian Basin, North Greenland Remote Sensing doi: 10.3390/rs10081186 Authors: Amin Beiranvand Pour Tae-Yoon S. Park Yongcheol Park Jong Kuk Hong Basem Zoheir Biswajeet Pradhan Iman Ayoobi Mazlan Hashim Geological mapping and mineral exploration programs in the High Arctic have been naturally hindered by its remoteness and hostile climate conditions. The Franklinian Basin in North Greenland has a unique potential for exploration of world-class zinc deposits. In this research, multi-sensor remote sensing satellite data (e.g., Landsat-8, Phased Array L-band Synthetic Aperture Radar (PALSAR) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) were used for exploring zinc in the trough sequences and shelf-platform carbonate of the Franklinian Basin. A series of robust image processing algorithms was implemented for detecting spatial distribution of pixels/sub-pixels related to key alteration mineral assemblages and structural features that may represent potential undiscovered Zn–Pb deposits. Fusion of Directed Principal Component Analysis (DPCA) and Independent Component Analysis (ICA) was applied to some selected Landsat-8 mineral indices for mapping gossan, clay-rich zones and dolomitization. Major lineaments, intersections, curvilinear structures and sedimentary formations were traced by the application of Feature-oriented Principal Components Selection (FPCS) to cross-polarized backscatter PALSAR ratio images. Mixture Tuned Matched Filtering (MTMF) algorithm was applied to ASTER VNIR/SWIR bands for sub-pixel detection and classification of hematite, goethite, jarosite, alunite, gypsum, chalcedony, kaolinite, muscovite, chlorite, epidote, calcite and dolomite in the prospective targets. Using the remote sensing data and approaches, several high potential zones characterized by distinct alteration mineral assemblages and structural fabrics were identified that could represent undiscovered Zn–Pb sulfide deposits in the study area. This research establishes a straightforward/cost-effective multi-sensor satellite-based remote sensing approach for reconnaissance stages of mineral exploration in hardly accessible parts of the High Arctic environments.

Description: Remote Sensing, Vol. 10, Pages 1184: An Evaluation of Forest Health Insect and Disease Survey Data and Satellite-Based Remote Sensing Forest Change Detection Methods: Case Studies in the United States Remote Sensing doi: 10.3390/rs10081184 Authors: Ian W. Housman Robert A. Chastain Mark V. Finco The Operational Remote Sensing (ORS) program leverages Landsat and MODIS data to detect forest disturbances across the conterminous United States (CONUS). The ORS program was initiated in 2014 as a collaboration between the US Department of Agriculture Forest Service Geospatial Technology and Applications Center (GTAC) and the Forest Health Assessment and Applied Sciences Team (FHAAST). The goal of the ORS program is to supplement the Insect and Disease Survey (IDS) and MODIS Real-Time Forest Disturbance (RTFD) programs with imagery-derived forest disturbance data that can be used to augment traditional IDS data. We developed three algorithms and produced ORS forest change products using both Landsat and MODIS data. These were assessed over Southern New England and the Rio Grande National Forest. Reference data were acquired using TimeSync to conduct an independent accuracy assessment of IDS, RTFD, and ORS products. Overall accuracy for all products ranged from 71.63% to 92.55% in the Southern New England study area and 63.48% to 79.13% in the Rio Grande National Forest study area. While the accuracies attained from the assessed products are somewhat low, these results are similar to comparable studies. Although many ORS products met or exceeded the overall accuracy of IDS and RTFD products, the differences were largely statistically insignificant at the 95% confidence interval. This demonstrates the current implementation of ORS is sufficient to provide data to augment IDS data.

Description: Atmosphere, Vol. 9, Pages 294: The Influence of the North Atlantic Oscillation Index on Emergency Ambulance Calls for Elevated Arterial Blood Pressure Atmosphere doi: 10.3390/atmos9080294 Authors: Jone Vencloviene Agne Braziene Jurate Zaltauskaite Paulius Dobozinskas The North Atlantic Oscillation (NAO) is the most prominent pattern of atmospheric variability over the middle and high latitudes of the Northern Hemisphere, especially during the cold season. It is found that “weather types” are associated with human health. It is possible that variations in NAO indices (NAOI) had additional impact on human health. We investigated the association between daily emergency ambulance calls (EACs) for exacerbation of essential hypertension and the NAOI by using Poisson regression, adjusting for season, weather variables and exposure to CO, particulate matter and ozone. An increased risk of EACs was associated with NAOI < −0.5 (Rate Ratio (RR) = 1.07, p = 0.013) and NAOI > 0.5 (RR = 1.06, p = 0.004) with a lag of 2 days as compared to −0.5 ≤ NAOI ≤ 0.5. The impact of NAOI > 0.5 was stronger during November-March (RR = 1.10, lag = 0, p = 0.026). No significant associations were found between the NAOI and EACs during 8:00–13:59. An elevated risk was associated during 14:00–21:59 with NAOI < −0.5 (RR = 1.09, p = 0.003) and NAOI > 0.5 (RR = 1.09, p = 0.019) and during 22:00–7:59 with NAOI < −0.5 (RR = 1.12, lag = 1, p = 0.001). The non-linear associations were found between the NAO and EACs. The different impact of the NAO was found during the periods November–March and April–October. The impact of the NAOI was not identical for different times of the day.

Description: Geosciences, Vol. 8, Pages 279: Detection of Stones in Marine Habitats Combining Simultaneous Hydroacoustic Surveys Geosciences doi: 10.3390/geosciences8080279 Authors: Svenja Papenmeier H. Christian Hass Exposed stones in sandy sublittoral environments are hotspots for marine biodiversity, especially for benthic communities. The detection of single stones is principally possible using sidescan-sonar (SSS) backscatter data. The data resolution has to be high to visualize the acoustic shadows of the stones. Otherwise, stony substrates will not be differentiable from other high backscatter substrates (e.g., gravel). Acquiring adequate sonar data and identifying stones in backscatter images is time consuming because it usually requires visual-manual procedures. To develop a more efficient identification and demarcation procedure of stone fields, sidescan sonar and parametric echo sound data were recorded within the marine protected area of “Sylt Outer Reef” (German Bight, North Sea). The investigated area (~5.900 km2) is characterized by dispersed heterogeneous moraine and marine deposits. Data from parametric sediment echo sounder indicate hyperbolas at the sediment surface in stony areas, which can easily be exported. By combining simultaneous recorded low backscatter data and parametric single beam data, stony grounds were demarcated faster, less complex and reproducible from gravelly substrates indicating similar high backscatter in the SSS data.

Description: Minerals, Vol. 8, Pages 326: Hydrotalcite and Hydrocalumite in Mortar Binders from the Medieval Castle of Portilla (Álava, North Spain): Accurate Mineralogical Control to Achieve More Reliable Chronological Ages Minerals doi: 10.3390/min8080326 Authors: Graciela Ponce-Antón Luis Angel Ortega Maria Cruz Zuluaga Ainhoa Alonso-Olazabal Jose Luis Solaun Mortars from different stratigraphic units at Portilla Castle (Alava, North Spain) have been analyzed for mineralogical characterization before radiocarbon dating. The mortar binder at Portilla Castle is composed not only of neoformation calcite but also of double-layered hydroxide (LDH) minerals such as hydrotalcite and hydrocalumite. The mineralogy of several fractions of the binder has been analyzed to determine the granulometric distribution of minerals in the binder. The continuous monitoring of mineralogy during the extraction of different grain size fractions has been performed by using a scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analyses (TGA). Hydrotalcite and hydrocalumite-bearing mortar binders give older ages than expected since they introduce dead carbon into the system.

Description: Atmosphere, Vol. 9, Pages 299: The Effect of Nonlocal Vehicle Restriction Policy on Air Quality in Shanghai Atmosphere doi: 10.3390/atmos9080299 Authors: Junjie Li Xiao-Bing Li Bai Li Zhong-Ren Peng In recent years, road space rationing policies have been increasingly applied as a traffic management solution to tackle congestion and traffic emission problems in big cities. Existing studies on the effect of traffic policy on air quality have mainly focused on the odd–even day traffic restriction policy or one-day-per-week restriction policy. There are few studies paying attention to the effect of nonlocal license plate restrictions on air quality in Shanghai. Restrictions toward nonlocal vehicles usually prohibit vehicles with nonlocal license plates from entering certain urban areas or using certain subsets of the road network (e.g., the elevated expressway) during specific time periods on workdays. To investigate the impact of such a policy on the residents’ exposure to pollutants, CO concentration and Air Quality Index (AQI) were compared during January and February in 2015, 2016 and 2017. Regression discontinuity (RD) was used to test the validity of nonlocal vehicle restriction on mitigating environmental pollution. Several conclusions can be made: (1) CO concentration was higher on ground-level roads on the restriction days than those in the nonrestriction days; (2) the extension of the restriction period exposed the commuters to high pollution for a longer time on the ground, which will do harm to them; and (3) the nonlocal vehicle restriction policy did play a role in improving the air quality in Shanghai when extending the evening rush period. Additionally, some suggestions are mentioned in order to improve air quality and passenger health and safety.

Description: Atmosphere, Vol. 9, Pages 297: Sources Profiles of Volatile Organic Compounds (VOCs) Measured in a Typical Industrial Process in Wuhan, Central China Atmosphere doi: 10.3390/atmos9080297 Authors: Longjiao Shen Ping Xiang Shengwen Liang Wentai Chen Ming Wang Sihua Lu Zuwu Wang Industrial emission is an important source of ambient volatile organic compounds (VOCs) in Wuhan City, Hubei Province, China. We collected 53 VOC samples from petrochemical, surface coating, electronic manufacturing, and gasoline evaporation using stainless canisters to develop localized source profiles. Concentrations of 86 VOC species, including hydrocarbons, halocarbons, and oxygenated VOCs, were quantified by a gas chromatography–flame ionization detection/mass spectrometry system. Alkanes were the major constituents observed in the source profile from the petrochemical industry. Aromatics (79.5~81.4%) were the largest group in auto-painting factories, while oxygenated VOCs (82.0%) and heavy alkanes (68.7%) were dominant in gravure printing and offset printing factories, respectively. Acetone was the largest contributor and the most frequently monitored species in printed circuit board (PCB) manufacturing, while VOC species emitted from integrated chip (IC) were characterized by high contents of isopropanol (56.4–98.3%) and acetone (30.8%). Chemical compositions from vapor of gasoline 92#, 93#, and 98# were almost identical. Alkanes were the dominant VOC group, with i-pentane being the most abundant species (31.4–37.7%), followed by n-butane and n-pentane. However, high loadings of heavier alkanes were observed in the profile of diesel evaporation.

Description: Atmosphere, Vol. 9, Pages 298: Chemical Composition and Sources of Marine Aerosol over the Western North Pacific Ocean in Winter Atmosphere doi: 10.3390/atmos9080298 Authors: Hong-Wei Xiao Hua-Yun Xiao Chun-Yan Shen Zhong-Yi Zhang Ai-Min Long Atmospheric deposition of long-range transported continental substances from natural and anthropogenic sources affects biogeochemical processes in marine systems. Emissions of sea spray contribute aerosol particles to the marine atmosphere. Despite the importance of continental dispersion and atmospheric processes involving aerosol particles within remote marine atmosphere, knowledge of the sources of various water-soluble ions is limited because of insufficient observations. Concentrations of Total suspended particulates (TSPs) and major inorganic ions (Cl−, Na+, SO42−, Mg2+, Ca2+, K+, NO3−, NH4+), as well as organic nitrogen (ON-N) values, were measured in marine aerosol collected over the western north Pacific (WNP) during a cruise from 3 December 2014 to 13 March 2015. Aerosol samples were analyzed to determine their chemical characteristics and a source apportionment for this region and the continental influence on the open ocean when air masses are from continent in winter. TSP mass concentrations ranged from 14.1 to 136.0 μg/m3 with an average of 44.8 ± 28.1 μg/m3. Concentrations of TSPs and major ions were higher near the coast (close to Qingdao and Xiamen) and lower over the open ocean. The total mass of inorganic ions and organic nitrogen accounted for 51.1% of the total TSP. Cl− had highest concentrations among the major inorganic ions, followed by SO42−, NO3−, Mg2+, Ca2+, K+, and NH4+, respectively. However, Cl− showed a deficit relative to Na+ in most samples, likely related to heterogeneous reactions within the marine atmosphere. Most SO42−, Mg2+, Ca2+, and K+ were from sea salt, while other major ions were from continental sources. The non-sea-salt (nss) fractions of Ca2+, Mg2+ and K+ were derived from continental crust, while nss-SO42− and NO3− were derived from anthropogenic sources. ON had several sources, including reactions of NOx with volatile organic compounds (anthropogenic sources) or NH3 with gaseous hydrocarbons, as well as crustal and marine biogenic sources.

Description: Remote Sensing, Vol. 10, Pages 1196: Evaluating the Best Spectral Indices for the Detection of Burn Scars at Several Post-Fire Dates in a Mountainous Region of Northwest Yunnan, China Remote Sensing doi: 10.3390/rs10081196 Authors: Davide Fornacca Guopeng Ren Wen Xiao Remote mountainous regions are among the Earth’s last remaining wild spots, hosting rare ecosystems and rich biodiversity. Because of access difficulties and low population density, baseline information about natural and human-induced disturbances in these regions is often limited or nonexistent. Landsat time series offer invaluable opportunities to reconstruct past land cover changes. However, the applicability of this approach strongly depends on the availability of good quality, cloud-free images, acquired at a regular time interval, which in mountainous regions are often difficult to find. The present study analyzed burn scar detection capabilities of 11 widely used spectral indices (SI) at 1 to 5 years after fire events in four dominant vegetation groups in a mountainous region of northwest Yunnan, China. To evaluate their performances, we used M-statistic as a burned-unburned class separability index, and we adapted an existing metric to quantify the SI residual burn signal at post-fire dates compared to the maximum severity recorded soon after the fire. Our results show that Normalized Burn Ratio (NBR) and Normalized Difference Moisture Index (NDMI) are always among the three best performers for the detection of burn scars starting 1 year after fire but not for the immediate post-fire assessment, where the Mid Infrared Burn Index, Burn Area Index, and Tasseled Cap Greenness were superior. Brightness and Wetness peculiar patterns revealed long-term effects of fire in vegetated land, suggesting their potential integration to assist other SI in burned area detection several years after the fire event. However, in general, class separability of most of the SI was poor after one growing season, due to the seasonal rains and the relatively fast regrowth rate of shrubs and grasses, confirming the difficulty of assessment in mountainous ecosystems. Our findings are meaningful for the selection of a suitable SI to integrate in burned area detection workflows, according to vegetation type and time lag between image acquisitions.

Description: Remote Sensing, Vol. 10, Pages 1192: Automating Parameter Learning for Classifying Terrestrial LiDAR Point Cloud Using 2D Land Cover Maps Remote Sensing doi: 10.3390/rs10081192 Authors: Chen-Chieh Feng Zhou Guo The automating classification of point clouds capturing urban scenes is critical for supporting applications that demand three-dimensional (3D) models. Achieving this goal, however, is met with challenges because of the varying densities of the point clouds and the complexity of the 3D data. In order to increase the level of automation in the point cloud classification, this study proposes a segment-based parameter learning method that incorporates a two-dimensional (2D) land cover map, in which a strategy of fusing the 2D land cover map and the 3D points is first adopted to create labelled samples, and a formalized procedure is then implemented to automatically learn the following parameters of point cloud classification: the optimal scale of the neighborhood for segmentation, optimal feature set, and the training classifier. It comprises four main steps, namely: (1) point cloud segmentation; (2) sample selection; (3) optimal feature set selection; and (4) point cloud classification. Three datasets containing the point cloud data were used in this study to validate the efficiency of the proposed method. The first two datasets cover two areas of the National University of Singapore (NUS) campus while the third dataset is a widely used benchmark point cloud dataset of Oakland, Pennsylvania. The classification parameters were learned from the first dataset consisting of a terrestrial laser-scanning data and a 2D land cover map, and were subsequently used to classify both of the NUS datasets. The evaluation of the classification results showed overall accuracies of 94.07% and 91.13%, respectively, indicating that the transition of the knowledge learned from one dataset to another was satisfactory. The classification of the Oakland dataset achieved an overall accuracy of 97.08%, which further verified the transferability of the proposed approach. An experiment of the point-based classification was also conducted on the first dataset and the result was compared to that of the segment-based classification. The evaluation revealed that the overall accuracy of the segment-based classification is indeed higher than that of the point-based classification, demonstrating the advantage of the segment-based approaches.

Description: Remote Sensing, Vol. 10, Pages 1197: Quantifying Drought Propagation from Soil Moisture to Vegetation Dynamics Using a Newly Developed Ecohydrological Land Reanalysis Remote Sensing doi: 10.3390/rs10081197 Authors: Yohei Sawada Despite the importance of the interaction between soil moisture and vegetation dynamics to understand the complex nature of drought, few land reanalyses explicitly simulate vegetation growth and senescence. In this study, I provide a new land reanalysis which explicitly simulates the interaction between sub-surface soil moisture and vegetation dynamics by the sequential assimilation of satellite microwave brightness temperature observations into a land surface model (LSM). Assimilating satellite microwave brightness temperature observations improves the skill of a LSM to simultaneously simulate soil moisture and the seasonal cycle of leaf area index (LAI). By analyzing soil moisture and LAI simulated by this new land reanalysis, I identify the drought events which significantly damage LAI on the climatological day-of-year of the LAI’s seasonal peak and quantify drought propagation from soil moisture to LAI in the global snow-free region. On average, soil moisture in the shallow soil layers (0–0.45 m) quickly recovers from the drought condition before the climatological day-of-year of the LAI’s seasonal peak while soil moisture in the deeper soil layer (1.05–2.05 m) and LAI recover from the drought condition approximately 100 days after the climatological day-of-year of the LAI’s seasonal peak.

Description: Geosciences, Vol. 8, Pages 287: A New Occurrence of Terrestrial Native Iron in the Earth’s Surface: The Ilia Thermogenic Travertine Case, Northwestern Euboea, Greece Geosciences doi: 10.3390/geosciences8080287 Authors: Christos Kanellopoulos Eugenia Valsami-Jones Panagiotis Voudouris Christina Stouraiti Robert Moritz Constantinos Mavrogonatos Panagiotis Mitropoulos Native iron has been identified in an active thermogenic travertine deposit, located at Ilia area (Euboea Island, Greece). The deposit is forming around a hot spring, which is part of a large active metallogenetic hydrothermal system depositing ore-bearing travertines. The native iron occurs in two shapes: nodules with diameter 0.4 and 0.45 cm, and angular grains with length up to tens of μm. The travertine laminae around the spherical/ovoid nodules grow smoothly, and the angular grains are trapped inside the pores of the travertine. Their mineral-chemistry is ultra-pure, containing, other than Fe, only Mn (0.34–0.38 wt.%) and Ni (≤0.05 wt.%). After evaluating all the possible environments where native iron has been reported up until today and taking under consideration all the available data concerning the study area, we propose two possible scenarios: (i) Ilia’s native iron has a magmatic/hydrothermal origin i.e., it is a deep product near the magmatic chamber or a peripheral cooling igneous body that was transferred during the early stages of the geothermal field evolution, from high temperature, reduced gas-rich fluids and deposited along with other metals in permeable structural zones, at shallow levels. Later on, it was remobilized and mechanically transferred and precipitated at the Ilia’s thermogenic travertine by the active lower temperatures geothermal fluids; (ii) the native iron at Ilia is remobilized from deep seated ophiolitic rocks, originated initially from reduced fluids during serpentinization processes; however, its mechanical transport seems less probable. The native iron mineral-chemistry, morphology and the presence of the other mineral phases in the same thermogenic travertine support both hypotheses.

Description: Minerals, Vol. 8, Pages 312: Leaching of Primary Copper Sulfide Ore in Chloride-Ferrous Media Minerals doi: 10.3390/min8080312 Authors: Karina E. Salinas Osvaldo Herreros Cynthia M. Torres Copper extraction from primary copper sulfide ore from a typical porphyry copper deposit from Antofagasta, Chile, was investigated after leaching with a chloride-ferrous media at two temperatures. The study focused on whether this chemical leaching system could be applied at an industrial scale. Leaching tests were conducted in columns loaded with approximately 50 kg of agglomerated ore; the ore was first cured for 14 days and then leached for 90 days. The highest copper extraction, 50.23%, was achieved at 32.9 °C with the addition of 0.6 kg of H2SO4 per ton of ore, 0.525 kg of NaCl per ton of ore, and 0.5 kg of FeSO4 per ton of ore. In respect to copper extraction, the most effective variables were temperature and the addition of NaCl.

Description: Remote Sensing, Vol. 10, Pages 1202: Potential of Photochemical Reflectance Index for Indicating Photochemistry and Light Use Efficiency in Leaves of European Beech and Norway Spruce Trees Remote Sensing doi: 10.3390/rs10081202 Authors: Daniel Kováč Petra Veselovská Karel Klem Kristýna Večeřová Alexander Ač Josep Peñuelas Otmar Urban Hyperspectral reflectance is becoming more frequently used for measuring the functions and productivity of ecosystems. The purpose of this study was to re-evaluate the potential of the photochemical reflectance index (PRI) for evaluating physiological status of plants. This is needed because the reasons for variation in PRI and its relationships to physiological traits remain poorly understood. We examined the relationships between PRI and photosynthetic parameters in evergreen Norway spruce and deciduous European beech grown in controlled conditions during several consecutive periods of 10–12 days between which the irradiance and air temperature were changed stepwise. These regime changes induced significant changes in foliar biochemistry and physiology. The responses of PRI corresponded particularly to alterations in the actual quantum yield of photosystem II photochemistry (ΦPSII). Acclimation responses of both species led to loss of PRI sensitivity to light use efficiency (LUE). The procedure of measuring PRI at multiple irradiance-temperature conditions has been designed also for testing accuracy of ΔPRI in estimating LUE. A correction mechanism of subtracting daily measured PRI from early morning PRI has been performed to account for differences in photosynthetic pigments between irradiance-temperature regimes. Introducing ΔPRI, which provided a better estimate of non-photochemical quenching (NPQ) compared to PRI, also improved the accuracy of LUE estimation. Furthermore, ΔPRI was able to detect the effect of drought, which is poorly observable from PRI.

Description: Remote Sensing, Vol. 10, Pages 1200: Mapping up-to-Date Paddy Rice Extent at 10 M Resolution in China through the Integration of Optical and Synthetic Aperture Radar Images Remote Sensing doi: 10.3390/rs10081200 Authors: Xin Zhang Bingfang Wu Guillermo E. Ponce-Campos Miao Zhang Sheng Chang Fuyou Tian Rice is a staple food in East Asia and Southeast Asia—an area that accounts for more than half of the world’s population, and 11% of its cultivated land. Studies on rice monitoring can provide direct or indirect information on food security, and water source management. Remote sensing has proven to be the most effective method for the large-scale monitoring of croplands, by using temporary and spectral information. The Google Earth Engine (GEE) is a cloud-based platform providing access to high-performance computing resources for processing extremely large geospatial datasets. In this study, by leveraging the computational power of GEE and a large pool of satellite and other geophysical data (e.g., forest and water extent maps, with high accuracy at 30 m), we generated the first up-to-date rice extent map with crop intensity, at 10 m resolution in the three provinces with the highest rice production in China (the Heilongjiang, Hunan and Guangxi provinces). Optical and synthetic aperture radar (SAR) data were monthly and metric composited to ensure a sufficient amount of up-to-date data without cloud interference. To remove the common confounding noise in the pixel-based classification results at medium to high resolution, we integrated the pixel-based classification (using a random forest classifier) result with the object-based segmentation (using a simple linear iterative clustering (SLIC) method). This integration resulted in the rice planted area data that most closely resembled official statistics. The overall accuracy was approximately 90%, which was validated by ground crop field points. The F scores reached 87.78% in the Heilongjiang Province for monocropped rice, 89.97% and 80.00% in the Hunan Province for mono- and double-cropped rice, respectively, and 88.24% in the Guangxi Province for double-cropped rice.

Description: IJGI, Vol. 7, Pages 311: Processing BIM and GIS Models in Practice: Experiences and Recommendations from a GeoBIM Project in The Netherlands ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080311 Authors: Ken Arroyo Ohori Abdoulaye Diakité Thomas Krijnen Hugo Ledoux Jantien Stoter It is widely acknowledged that the integration of BIM and GIS data is a crucial step forward for future 3D city modelling, but most of the research conducted so far has covered only the high-level and semantic aspects of GIS-BIM integration. This paper presents the results of the GeoBIM project, which tackled three integration problems focussing instead on aspects involving geometry processing: (i) the automated processing of complex architectural IFC models; (ii) the integration of existing GIS subsoil data in BIM; and (iii) the georeferencing of BIM models for their use in GIS software. All the problems have been studied using real world models and existing datasets made and used by practitioners in The Netherlands. For each problem, this paper exposes in detail the issues faced, proposed solutions, and recommendations for a more successful integration.

Description: Minerals, Vol. 8, Pages 332: Kurchatovite and Clinokurchatovite, Ideally CaMgB2O5: An Example of Modular Polymorphism Minerals doi: 10.3390/min8080332 Authors: Yulia A. Pankova Sergey V. Krivovichev Igor V. Pekov Edward S. Grew Vasiliy O. Yapaskurt Kurchatovite and clinokurchatovite, both of ideal composition CaMgB2O5, from the type localities (Solongo, Buryatia, Russia, and Sayak-IV, Kazakhstan, respectively) have been studied using electron microprobe and single-crystal X-ray diffraction methods. The empirical formulae of the samples are Ca1.01Mg0.87Mn0.11Fe2+0.02B1.99O5 and Ca0.94Mg0.91Fe2+0.10Mn0.04B2.01O5 for kurchatovite and clinokurchatovite, respectively. The crystal structures of the two minerals are similar and based upon two-dimensional blocks arranged parallel to the c axis in kurchatovite and parallel to the a axis in clinokurchatovite. The blocks are built up from diborate B2O5 groups, and Ca2+ and Mg2+ cations in seven- and six-fold coordination, respectively. Detailed analysis of geometrical parameters of the adjacent blocks reveals that symmetrically different diborate groups have different degrees of conformation in terms of the δ angles between the planes of two BO3 triangles sharing a common O atom, featuring two discrete sets of the δ values of ca. 55° (B’ blocks) and 34° (B” blocks). The stacking of the blocks in clinokurchatovite can be presented as …(+B’)(+B”)(+B’)(+B”)… or [(+B’)(+B”)], whereas in kurchatovite it is more complex and corresponds to the sequence …(+B’)(+B”)(+B’)(−B’)(−B”)(−B’)(+B’)(+B”)(+B’)(−B’)(−B”)(−B’)… or [(+B’)(+B”)(+B’)(−B’)(−B”)(−B’)]. The B’:B” ratios for clinokurchatovite and kurchatovite are 1:1 and 2:1, respectively. According to this description, the two minerals cannot be considered as polytypes and their mutual relationship corresponds to the term modular polymorphs. From the viewpoint of information-based measures of structural complexity, clinokurchatovite (IG = 4.170 bits/atom and IG,total = 300.235 bits/cell) is structurally simpler than kurchatovite (IG = 4.755 bits/atom and IG,total = 1027.056 bits/cell). The high structural complexity of kurchatovite can be inferred from the modular character of its structure. The analysis of structural combinatorics in terms of the modular approach allows to construct the whole family of theoretically possible “kurchatovite”-type structures that bear the same structural features common for kurchatovite and clinokurchatovite. However, the crystal structures of the latter minerals are the simplest and are the only ones that have been observed in nature. The absence of other possible structures is remarkable and can be explained by either the maximum-entropy of the least-action fundamental principles.

Description: Minerals, Vol. 8, Pages 331: Textural Characteristics of Noncrystalline Silica in Sinters and Quartz Veins: Implications for the Formation of Bonanza Veins in Low-Sulfidation Epithermal Deposits Minerals doi: 10.3390/min8080331 Authors: Tadsuda Taksavasu Thomas Monecke T. James Reynolds Silica sinters forming at the Wairakei geothermal power plant in New Zealand are composed of noncrystalline opal-A that deposited rapidly from cooling geothermal liquids flashed to atmosphere. The sinter is laminated with alternating layers of variably compacted silicified filamentous microbes encased by chains of fused silica microspheres. Microscopic inspection of bonanza quartz vein samples from the Buckskin National low-sulfidation epithermal precious metal deposit in Nevada showed that colloform bands in these veins exhibit relic microsphere textures similar to those observed in the silica sinters from the Wairakei power plant. The textural similarity suggests that the colloform bands were originally composed of noncrystalline opal-A that subsequently recrystallized to quartz. The colloform bands contain dendrites of electrum and naumannite that must have grown in a yielding matrix of silica microspheres deposited at the same time as the ore minerals, implying that the noncrystalline silica exhibited a gel-like behavior. Quartz bands having other textural characteristics in the crustiform veins lack ore minerals. This suggests that ore deposition and the formation of the colloform bands originally composed of compacted microspheres of noncrystalline silica are genetically linked and that ore deposition within the bonanza veins was only episodic. Supersaturation of silica and precious metals leading to the formation of the colloform bands may have occurred in response to transient flashing of the hydrothermal liquids. Flashing of geothermal liquids may thus represent a key mechanism in the formation of bonanza precious metal grades in low-sulfidation epithermal deposits.

Description: Geosciences, Vol. 8, Pages 288: Development of a New Simulation Tool Coupling a 2D Finite Volume Overland Flow Model and a Drainage Network Model Geosciences doi: 10.3390/geosciences8080288 Authors: Javier Fernández-Pato Pilar García-Navarro Numerical simulation of mixed flows combining free surface and pressurized flows is a practical tool to prevent possible flood situations in urban environments. When dealing with intense storm events, the limited capacity of the drainage network conduits can cause undesirable flooding situations. Computational simulation of the involved processes can lead to better management of the drainage network of urban areas. In particular, it is interesting to simultaneuously calculate the possible pressurization of the pipe network and the surface water dynamics in case of overflow. In this work, the coupling of two models is presented. The surface flow model is based on two-dimensional shallow water equations with which it is possible to solve the overland water dynamics as well as the transformation of rainfall into runoff through different submodels of infiltration. The underground drainage system assumes mostly free surface flow that can be pressurized in specific situations. The pipe network is modeled by means of one-dimensional sections coupled with the surface model in specific regions of the domain, such as drains or sewers. The numerical techniques considered for the resolution of both mathematical models are based on finite volume schemes with a first-order upwind discretization. The coupling of the models is verified using laboratory experimental data. Furthermore, the potential usefulness of the approach is demonstrated using real flooding data in a urban environment.

Description: Geosciences, Vol. 8, Pages 289: Multi-Wavelength High-Resolution Spectroscopy for Exoplanet Detection: Motivation, Instrumentation and First Results Geosciences doi: 10.3390/geosciences8080289 Authors: Serena Benatti Exoplanet research has shown an incessant growth since the first claim of a hot giant planet around a solar-like star in the mid-1990s. Today, the new facilities are working to spot the first habitable rocky planets around low-mass stars as a forerunner for the detection of the long-awaited Sun-Earth analog system. All the achievements in this field would not have been possible without the constant development of the technology and of new methods to detect more and more challenging planets. After the consolidation of a top-level instrumentation for high-resolution spectroscopy in the visible wavelength range, a huge effort is now dedicated to reaching the same precision and accuracy in the near-infrared. Actually, observations in this range present several advantages in the search for exoplanets around M dwarfs, known to be the most favorable targets to detect possible habitable planets. They are also characterized by intense stellar activity, which hampers planet detection, but its impact on the radial velocity modulation is mitigated in the infrared. Simultaneous observations in the visible and near-infrared ranges appear to be an even more powerful technique since they provide combined and complementary information, also useful for many other exoplanetary science cases.

Description: Remote Sensing, Vol. 10, Pages 1211: Evaluating Metal Effects on the Reflectance Spectra of Plant Leaves during Different Seasons in Post-Mining Areas, China Remote Sensing doi: 10.3390/rs10081211 Authors: Chao Zhou Shengbo Chen Yuanzhi Zhang Jianhua Zhao Derui Song Dawei Liu This study examined the relationship between the leaf reflectance of different seasons and the concentration of heavy metal elements in leaves, such as Co, Cu, Mo, and Ni in a post-mining area. The reflectance spectra and leaf samples of three typical plants were measured and collected in a whole growth cycle (June, July, August, and September). The Red Edge Position (REP), Readjustment Normalized Difference Vegetation Index (RE-NDVI), and Photochemical Reflectance Index (PRI) were extracted and used to explore its relation with the heavy metals concentrations in leaves between different seasons. The results show that all three Vegetation Indices (VIs) were insensitive indicators for monitoring the metal effects of vegetation in different seasons, which showed similar trends. Based on this, the Continuum Removal Indices (CRIs) were proposed from the continuum removed approach and extended for detecting the effects of heavy metal pollution over a full growth cycle. The relationship between the metal concentrations and CRIs of different plants was respectively analyzed by Stepwise Multiple Linear Regression (SMLR) and Partial Least Squares Regression (PLSR). It is found that a significant correlation exists between the band depth and the concentration of Cu and Ni based on the White birch data sets using the PLSR, resulting in a small deviation from the established relationships. Compared with VIs, the approach of coupling CRIs and multiple regressions was effective for improving the estimation accuracy. The presented study provides a detection model of leaf heavy metals that can be adapted to different growing cycles, even an arbitrary growing cycle.

Description: Remote Sensing, Vol. 10, Pages 1234: HOMPC: A Local Feature Descriptor Based on the Combination of Magnitude and Phase Congruency Information for Multi-Sensor Remote Sensing Images Remote Sensing doi: 10.3390/rs10081234 Authors: Zhitao Fu Qianqing Qin Bin Luo Hong Sun Chun Wu Local region description of multi-sensor images remains a challenging task in remote sensing image analysis and applications due to the non-linear radiation variations between images. This paper presents a novel descriptor based on the combination of the magnitude and phase congruency information of local regions to capture the common features of images with non-linear radiation changes. We first propose oriented phase congruency maps (PCMs) and oriented magnitude binary maps (MBMs) using the multi-oriented phase congruency and magnitude information of log-Gabor filters. The two feature vectors are then quickly constructed based on the convolved PCMs and MBMs. Finally, a dense descriptor named the histograms of oriented magnitude and phase congruency (HOMPC) is developed by combining the histograms of oriented phase congruency (HPC) and the histograms of oriented magnitude (HOM) to capture the structure and shape properties of local regions. HOMPC was evaluated with three datasets composed of multi-sensor remote sensing images obtained from unmanned ground vehicle, unmanned aerial vehicle, and satellite platforms. The descriptor performance was evaluated by recall, precision, F1-measure, and area under the precision-recall curve. The experimental results showed the advantages of the HOM and HPC combination and confirmed that HOMPC is far superior to the current state-of-the-art local feature descriptors.

Description: Remote Sensing, Vol. 10, Pages 1236: Progressive Degradation of an Ice Rumple in the Thwaites Ice Shelf, Antarctica, as Observed from High-Resolution Digital Elevation Models Remote Sensing doi: 10.3390/rs10081236 Authors: Seung Hee Kim Duk-jin Kim Hyun-Cheol Kim Ice rumples are locally-grounded features of flowing ice shelves, elevated tens of meters above the surrounding surface. These features may significantly impact the dynamics of ice-shelf grounding lines, which are strongly related to shelf stability. In this study, we used TanDEM-X data to construct high-resolution DEMs of the Thwaites ice shelf in West Antarctica from 2011 to 2013. We also generated surface deformation maps which allowed us to detect and monitor the elevation changes of an ice rumple that appeared sometime between the observations of a grounding line of the Thwaites glacier using Double-Differential Interferometric SAR (DDInSAR) in 1996 and 2011. The observed degradation of the ice rumple during 2011–2013 may be related to a loss of contact with the underlying bathymetry caused by the thinning of the ice shelf. We subsequently used a viscoelastic deformation model with a finite spherical pressure source to reproduce the surface expression of the ice rumple. Global optimization allowed us to fit the model to the observed deformation map, producing reasonable estimates of the ice thickness at the center of the pressure source. Our conclusion is that combining the use of multiple high-resolution DEMs and the simple viscoelastic deformation model is feasible for observing and understanding the transient nature of small ice rumples, with implications for monitoring ice shelf stability.

Description: Remote Sensing, Vol. 10, Pages 1232: Assessing Coastal SMAP Surface Salinity Accuracy and Its Application to Monitoring Gulf of Maine Circulation Dynamics Remote Sensing doi: 10.3390/rs10081232 Authors: Semyon A. Grodsky Douglas Vandemark Hui Feng Monitoring the cold and productive waters of the Gulf of Maine and their interactions with the nearby northwestern (NW) Atlantic shelf is important but challenging. Although remotely sensed sea surface temperature (SST), ocean color, and sea level have become routine, much of the water exchange physics is reflected in salinity fields. The recent invention of satellite salinity sensors, including the Soil Moisture Active Passive (SMAP) radiometer, opens new prospects in regional shelf studies. However, local sea surface salinity (SSS) retrieval is challenging due to both cold SST limiting salinity sensor sensitivity and proximity to land. For the NW Atlantic, our analysis shows that SMAP SSS is subject to an SST-dependent bias that is negative and amplifies in winter and early spring due to the SST-related drop in SMAP sensor sensitivity. On top of that, SMAP SSS is subject to a land contamination bias. The latter bias becomes noticeable and negative when the antenna land contamination factor (LC) exceeds 0.2%, and attains maximum negative values at LC = 0.4%. Coastward of LC = 0.5%, a significant positive land contamination bias in absolute SMAP SSS is evident. SST and land contamination bias components are seasonally dependent due to seasonal changes in SST/winds and terrestrial microwave properties. Fortunately, it is shown that SSS anomalies computed relative to a satellite SSS climatology can effectively remove such seasonal biases along with the real seasonal cycle. SMAP monthly SSS anomalies have sufficient accuracy and applicability to extend nearer to the coasts. They are used to examine the Gulf of Maine water inflow, which displayed important water intrusions in between Georges Banks and Nova Scotia in the winters of 2016/17 and 2017/18. Water intrusion patterns observed by SMAP are generally consistent with independent measurements from the European Soil Moisture Ocean Salinity (SMOS) mission. Circulation dynamics related to the 2016/2017 period and enhanced wind-driven Scotian Shelf transport into the Gulf of Maine are discussed.

Description: Remote Sensing, Vol. 10, Pages 1230: Assisting Flood Disaster Response with Earth Observation Data and Products: A Critical Assessment Remote Sensing doi: 10.3390/rs10081230 Authors: Guy J-P. Schumann G. Robert Brakenridge Albert J. Kettner Rashid Kashif Emily Niebuhr Floods are among the top-ranking natural disasters in terms of annual cost in insured and uninsured losses. Since high-impact events often cover spatial scales that are beyond traditional regional monitoring operations, remote sensing, in particular from satellites, presents an attractive approach. Since the 1970s, there have been many studies in the scientific literature about mapping and monitoring of floods using data from various sensors onboard different satellites. The field has now matured and hence there is a general consensus among space agencies, numerous organizations, scientists, and end-users to strengthen the support that satellite missions can offer, particularly in assisting flood disaster response activities. This has stimulated more research in this area, and significant progress has been achieved in recent years in fostering our understanding of the ways in which remote sensing can support flood monitoring and assist emergency response activities. This paper reviews the products and services that currently exist to deliver actionable information about an ongoing flood disaster to emergency response operations. It also critically discusses requirements, challenges and perspectives for improving operational assistance during flood disaster using satellite remote sensing products.

Description: Atmosphere, Vol. 9, Pages 306: Correction: Bärfuss et al. New Setup of the UAS ALADINA for Measuring Boundary Layer Properties, Atmospheric Particles and Solar Radiation. Atmosphere, 2018, 9, 28 Atmosphere doi: 10.3390/atmos9080306 Authors: Konrad Bärfuss Falk Pätzold Barbara Altstädter Endres Kathe Stefan Nowak Lutz Bretschneider Ulf Bestmann Astrid Lampert The authors would like to correct the published article [1] concerning acknowlegdements as follows[...]

Description: Remote Sensing, Vol. 10, Pages 1228: Generic and Automatic Markov Random Field-Based Registration for Multimodal Remote Sensing Image Using Grayscale and Gradient Information Remote Sensing doi: 10.3390/rs10081228 Authors: Li Yan Ziqi Wang Yi Liu Zhiyun Ye The automatic image registration serves as a technical prerequisite for multimodal remote sensing image fusion. Meanwhile, it is also the technical basis for change detection, image stitching and target recognition. The demands of subpixel level registration accuracy can be rarely satisfied with a multimodal image registration method based on feature matching. In light of this, we propose a Generic and automatic Markov Random Field (MRF)-based registration framework of multimodal image using grayscale and gradient information. The proposed approach performs non-rigid registration and formulates an MRF model while grayscale and gradient statistical information of a multimodal image is employed for the evaluation of similarity while the spatial weighting function is optimized simultaneously. Besides, the value space is discretized to improve the convergence speed. The developed automatic approach was validated both qualitatively and quantitatively, demonstrating its potential for a variety of multimodal remote sensing datasets and scenes. As for the registration accuracy, the average target registration error of the proposed framework is less than 1 pixel, while the maximum displacement error is less than 1 pixel. Compared with the polynomial model registration based on manual selection, the registration accuracy has been significantly improved. In the meantime, the proposed approach had the partial applicability for the multimodal image registration of large deformation scenes. It is also proved that the proposed registration framework using grayscale and gradient information outperforms the MRF-based registration using only grayscale information and only gradient information while the proposed registration framework using Gaussian function as spatial weighting function is superior to that using distance inverse weight method.

Description: Minerals, Vol. 8, Pages 337: The Compressive Strength and Microstructure of Alkali-Activated Binary Cements Developed by Combining Ceramic Sanitaryware with Fly Ash or Blast Furnace Slag Minerals doi: 10.3390/min8080337 Authors: Juan Cosa Lourdes Soriano María Victoria Borrachero Lucía Reig Jordi Payá José María Monzó The properties of a binder developed by the alkali-activation of a single waste material can improve when it is blended with different industrial by-products. This research aimed to investigate the influence of blast furnace slag (BFS) and fly ash (FA) (0–50 wt %) on the microstructure and compressive strength of alkali-activated ceramic sanitaryware (CSW). 4 wt % Ca(OH)2 was added to the CSW/FA blended samples and, given the high calcium content of BFS, the influence of BFS was analyzed with and without adding Ca(OH)2. Mortars were used to assess the compressive strength of the blended cements, and their microstructure was investigated in pastes by X-ray diffraction, thermogravimetry, and field emission scanning electron microscopy. All the samples were cured at 20 °C for 28 and 90 days and at 65 °C for 7 days. The results show that the partial replacement of CSW with BFS or FA allowed CSW to be activated at 20 °C. The CSW/BFS systems exhibited better mechanical properties than the CSW/FA blended mortars, so that maximum strength values of 54.3 MPa and 29.4 MPa were obtained in the samples prepared with 50 wt % BFS and FA, respectively, cured at 20 °C for 90 days.

Description: Remote Sensing, Vol. 10, Pages 1242: Ocean Wave Measurement Using Short-Range K-Band Narrow Beam Continuous Wave Radar Remote Sensing doi: 10.3390/rs10081242 Authors: Jian Cui Ralf Bachmayer Brad deYoung Weimin Huang We describe a technique to measure ocean wave period, height and direction. The technique is based on the characteristics of transmission and backscattering of short-range K-band narrow beam continuous wave radar at the sea surface. The short-range K-band radar transmits and receives continuous signals close to the sea surface at a low-grazing angle. By sensing the motions of a dominant facet at the sea surface that strongly scatters signals back and is located directly in front of the radar, the wave orbital velocity can be measured from the Doppler shift of the received radar signal. The period, height and direction of ocean wave are determined from the relationships among wave orbital velocity, ocean wave characteristics and the Doppler shift. Numerical simulations were performed to validate that the dominant facet exists and ocean waves are measured by sensing its motion. Validation experiments were conducted in a wave tank to verify the feasibility of the proposed ocean wave measurement method. The results of simulations and experiments demonstrate the effectiveness of the short-range K-band narrow beam continuous wave radar for the measurement of ocean waves.

Description: Remote Sensing, Vol. 10, Pages 1241: Troposphere Water Vapour Tomography: A Horizontal Parameterised Approach Remote Sensing doi: 10.3390/rs10081241 Authors: Qingzhi Zhao Yibin Yao Wanqiang Yao Global Navigation Satellite System (GNSS) troposphere tomography has become one of the most cost-effective means to obtain three-dimensional (3-d) image of the tropospheric water vapour field. Traditional methods divide the tomography area into a number of 3-d voxels and assume that the water vapour density at any voxel is a constant during the given period. However, such behaviour breaks the spatial continuity of water vapour density in a horizontal direction and the number of unknown parameters needing to be estimated is very large. This is the focus of the paper, which tries to reconstruct the water vapor field using the tomographic technique without imposing empirical horizontal and vertical constraints. The proposed approach introduces the layered functional model in each layer vertically and only an a priori constraint is imposed for the water vapor information at the location of the radiosonde station. The elevation angle mask of 30° is determined according to the distribution of intersections between the satellite rays and different layers, which avoids the impact of ray bending and the error in slant water vapor (SWV) at low elevation angles on the tomographic result. Additionally, an optimal weighting strategy is applied to the established tomographic model to obtain a reasonable result. The tomographic experiment is performed using Global Positioning System (GPS) data of 12 receivers derived from the Satellite Positioning Reference Station Network (SatRef) in Hong Kong. The quality of the established tomographic model is validated under different weather conditions and compared with the conventional tomography method using 31-day data, respectively. The numerical result shows that the proposed method is applicable and superior to the traditional one. Comparisons of integrated water vapour (IWV) of the proposed method with that derived from radiosonde and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim data show that the root mean square (RMS)/Bias of their differences are 3.2/−0.8 mm and 3.3/−1.7 mm, respectively, while the values of traditional method are 5.1/−3.9 mm and 6.3/−5.9 mm, respectively. Furthermore, the water vapour density profiles are also compared with radiosonde and ECMWF data, and the values of RMS/Bias error for the proposed method are 0.88/0.06 g/m3 and 0.92/−0.08 g/m3, respectively, while the values of the traditional method are 1.33/0.38 g/m3 and 1.59/0.40 g/m3, respectively.

Description: Remote Sensing, Vol. 10, Pages 1237: Detection of Methane Plumes Using Airborne Midwave Infrared (3–5 µm) Hyperspectral Data Remote Sensing doi: 10.3390/rs10081237 Authors: Rebecca Del’ Papa Moreira Scafutto Carlos Roberto de Souza Filho Methane (CH4) display spectral features in several regions of the infrared range (0.75–14 µm), which can be used for the remote mapping of emission sources through the detection of CH4 plumes from natural seeps and leaks. Applications of hyperspectral remote sensing techniques for the detection of CH4 in the near and shortwave infrared (NIR-SWIR: 0.75–3 µm) and longwave infrared (LWIR: 7–14 µm) have been demonstrated in the literature with multiple sensors and scenarios. However, the acquisition and processing of hyperspectral data in the midwave infrared (MWIR: 3–5 µm) for this application is rather scarce. Here, a controlled field experiment was used to evaluate the potential for CH4 plume detection in the MWIR based on hyperspectral data acquired with the SEBASS airborne sensor. For comparison purposes, LWIR data were also acquired simultaneously with the same instrument. The experiment included surface and undersurface emission sources (ground stations), with flow rates ranging between 0.6–40 m3/h. The data collected in both ranges were sequentially processed using the same methodology. The CH4 plume was detected, variably, in both datasets. The gas plume was detected in all LWIR images acquired over nine gas leakage stations. In the MWIR range, the plume was detected in only four stations, wherein 18 m3/h was the lowest flux sensed. We demonstrate that the interference of target reflectance, the low contrast between plume and background and a low signal of the CH4 feature in the MWIR at ambient conditions possibly explain the inferior results observed for this range when compared to LWIR. Furthermore, we show that the acquisition time and weather conditions, including specific limits of temperature, humidity, and wind speed, proved critical for plume detection using daytime MWIR hyperspectral data.

Description: Remote Sensing, Vol. 10, Pages 1238: Refining Land Cover Classification Maps Based on Dual-Adaptive Majority Voting Strategy for Very High Resolution Remote Sensing Images Remote Sensing doi: 10.3390/rs10081238 Authors: Guoqing Cui Zhiyong Lv Guangfei Li Jón Atli Benediktsson Yudong Lu Land cover classification that uses very high resolution (VHR) remote sensing images is a topic of considerable interest. Although many classification methods have been developed, the accuracy and usability of classification systems can still be improved. In this paper, a novel post-processing approach based on a dual-adaptive majority voting strategy (D-AMVS) is proposed to improve the performance of initial classification maps. D-AMVS defines a strategy for refining each label of a classified map that is obtained by different classification methods from the same original image, and fusing the different refined classification maps to generate a final classification result. The proposed D-AMVS contains three main blocks. (1) An adaptive region is generated by gradually extending the region around a central pixel based on two predefined parameters (T1 and T2) to utilize the spatial feature of ground targets in a VHR image. (2) For each classified map, the label of the central pixel is refined according to the majority voting rule within the adaptive region. This is defined as adaptive majority voting. Each initial classified map is refined in this manner pixel by pixel. (3) Finally, the refined classified maps are used to generate a final classification map, and the label of the central pixel in the final classification map is determined by applying AMV again. Each entire classified map is scanned and refined pixel by pixel based on the proposed D-AMVS. The accuracies of the proposed D-AMVS approach are investigated with two remote sensing images with high spatial resolutions of 1.0 m and 1.3 m. Compared with the classical majority voting method and a relatively new post-processing method called the general post-classification framework, the proposed D-AMVS can achieve a land cover classification map with less noise and higher classification accuracies.

Description: Geosciences, Vol. 8, Pages 213: A Mathematics Inspired Notation of Scales in the Climate System Geosciences doi: 10.3390/geosciences8060213 Authors: Jörn Behrens Conducting integrated climate research with involvement of such diverse disciplines as mathematics, meteorology, oceanography, economics, geology, biology, social, and communication sciences poses great challenges to the underlying nomenclature and methodology. In this article, we give a definition of the notion of scales, which is a central term in the geosciences, but not so familiar to social sciences or economics. We start with defining agents, involved in a specific subject of study, determined by their attributes or states. We move on to understand processes and phenomena as maps and subsets of image sets. With this and the introduction of metrics, we can measure sizes of phenomena and processes and finally define scales. Several examples illustrate our definition. An attempt is made to motivate a notion of scale interaction. This concept has proved useful in an interdisciplinary teaching project.

Description: Remote Sensing, Vol. 10, Pages 929: Intercomparison and Validation of SAR-Based Ice Velocity Measurement Techniques within the Greenland Ice Sheet CCI Project Remote Sensing doi: 10.3390/rs10060929 Authors: John Peter Merryman Boncori Morten Langer Andersen Jørgen Dall Anders Kusk Martijn Kamstra Signe Bech Andersen Noa Bechor Suzanne Bevan Christian Bignami Noel Gourmelen Ian Joughin Hyung-Sup Jung Adrian Luckman Jeremie Mouginot Julia Neelmeijer Eric Rignot Kilian Scharrer Thomas Nagler Bernd Scheuchl Tazio Strozzi Ice velocity is one of the products associated with the Ice Sheets Essential Climate Variable. This paper describes the intercomparison and validation of ice-velocity measurements carried out by several international research groups within the European Space Agency Greenland Ice Sheet Climate Change Initiative project, based on space-borne Synthetic Aperture Radar (SAR) data. The goal of this activity was to survey the best SAR-based measurement and error characterization approaches currently in practice. To this end, four experiments were carried out, related to different processing techniques and scenarios, namely differential SAR interferometry, multi aperture SAR interferometry and offset-tracking of incoherent as well as of partially-coherent data. For each task, participants were provided with common datasets covering areas located on the Greenland ice-sheet margin and asked to provide mean velocity maps, quality characterization and a description of processing algorithms and parameters. The results were then intercompared and validated against GPS data, revealing in several cases significant differences in terms of coverage and accuracy. The algorithmic steps and parameters influencing the coverage, accuracy and spatial resolution of the measurements are discussed in detail for each technique, as well as the consistency between quality parameters and validation results. This allows several recommendations to be formulated, in particular concerning procedures which can reduce the impact of analyst decisions, and which are often found to be the cause of sub-optimal algorithm performance.

Description: Remote Sensing, Vol. 10, Pages 926: Comparison of SNAP-Derived Sentinel-2A L2A Product to ESA Product over Europe Remote Sensing doi: 10.3390/rs10060926 Authors: Najib Djamai Richard Fernandes Sentinel-2 is a constellation of two satellites launched by the European Space Agency (ESA), respectively on 23 June 2015 and 7 March 2017, to map geophysical parameters over land surfaces. ESA provides Level 2 bottom-of-atmosphere reflectance (BOA) products (ESA-L2A) for Europe, with plans for operational global coverage, as well as the Sen2Cor (S2C) offline processor. In this study, aerosol optical thickness (AOT), precipitable water vapour (WVP) and surface reflectance from ESA-L2A products are compared with S2C output when using identical input Level 1 radiance products. Additionally, AOT and WVP are validated against reference measurement. As ESA and S2C share the same input and atmospheric correction algorithm, it was hypothesized that they should show identical validation performance and that differences between products should be negligible in comparison to the uncertainty of retrieved geophysical parameters due to radiometric uncertainty alone. Validation and intercomparison was performed for five clear-sky growing season dates for each of three ESA-L2A tiles selected to span a range of vegetation and topography as well as to be close to the AERONET measurement site. Validation of S2C (ESA) products using AERONET site measurements indicated an overall root mean square error (RMSE) of 0.06 (0.07) and a bias of 0.05 (0.09) for AOT and 0.20 cm (0.22 cm) and the bias was −0.02 cm (−0.10 cm) for WVP. Intercomparison of S2C-L2A and ESA-L2A showed an overall agreement higher than 99% for scene classification (SCL) maps and negligible differences for WVP (RMSE under 0.09 and R2 above 0.99). Larger disagreement was observed for aerosol optical thickness (AOT) (RMSE up to 0.04 and R2 as low as 0.14). For BOA reflectance, disagreement between products depends on vegetation cover density, topography slope and spectral band. The largest differences were observed for red-edge and infrared bands in mountainous vegetated areas (RMSE up to 4.9% reflectance and R2 as low as 0.53). These differences are of similar magnitude to the radiometric calibration requirements for the Sentinel 2 imager. The differences had minimal impact of commonly used vegetation indices (NDVI, NDWI, EVI), but application of the Sentinel Level 2 biophysical processor generally resulted in proportional differences in most derived vegetation parameters. It is recommended that the consistency of ESA and S2C products should be improved by the developers of the ESA and S2C processors.

Description: Atmosphere, Vol. 9, Pages 229: Influences of the North Pacific Victoria Mode on the South China Sea Summer Monsoon Atmosphere doi: 10.3390/atmos9060229 Authors: Ruiqiang Ding Jianping Li Yu-heng Tseng Lijuan Li Cheng Sun Fei Xie Using the reanalysis data and the numerical experiments of a coupled general circulation model (CGCM), we illustrated that perturbations in the second dominant mode (EOF2) of springtime North Pacific sea surface temperature (SST) variability, referred to as the Victoria mode (VM), are closely linked to variations in the intensity of the South China Sea summer monsoon (SCSSM). The underlying physical mechanism through which the VM affects the SCSSM is similar to the seasonal footprinting mechanism (SFM). Thermodynamic ocean–atmosphere coupling helps the springtime SST anomalies in the subtropics associated with the VM to persist into summer and to develop gradually toward the equator, leading to a weakened zonal SST gradient across the western North Pacific (WNP) to central equatorial Pacific, which in turn induces an anomalous cyclonic flow over the WNP and westerly anomalies in the western equatorial Pacific that tend to strengthen the WNP summer monsoon (WNPSM) as well as the SCSSM. The VM influence on both the WNPSM and SCSSM is intimately tied to its influence on ENSO through westerly anomalies in the western equatorial Pacific.

Description: Minerals, Vol. 8, Pages 250: Effect of Ammonium Chloride on the Efficiency with Which Copper Sulfate Activates Marmatite: Change in Solution Composition and Regulation of Surface Composition Minerals doi: 10.3390/min8060250 Authors: Shengdong Zhang Dongxia Feng Xiong Tong Bo Yang Xian Xie Zinc sulfide minerals are the primary choice for zinc extraction and marmatite is one of the two most common zinc sulphide minerals (sphalerite and marmatite), therefore it is of great significance to study and optimize the flotation of marmatite. To improve the activation of copper sulfate on marmatite, a method involving the addition of ammonium chloride is devised. The method has been proven to be an effective way of improving the activation efficiency of copper sulfate towards marmatite under alkaline conditions. The strengthening mechanism was studied using micro-flotation, adsorption test, X-ray photoelectron spectroscopy, and by analyzing changes in solution composition. Flotation test results show that the activation effect of the copper sulfate towards marmatite is enhanced with the addition of ammonium chloride. According to the results of the adsorption measurements and X-ray photoelectron spectroscopy analysis, when the marmatite surface is activated using copper sulfate with added ammonia chloride, it adsorbs more copper sulfide and less copper hydroxide and zinc hydroxide. These changes in surface composition are believed to occur via the following process: NH3(aq) promotes the dissolution of zinc hydroxide and then facilitates the conversion of surface copper hydroxide to copper sulfide. In addition, the occurrence of Cu(NH3)n2+ can promote the adsorption of copper ions (Cu2+ can be stored as Cu(NH3)n2+ via complexation, and then, when the concentration of copper ions decreases, Cu2+ can be released through the decompositionof Cu(NH3)n2+. Hence, the copper ion concentration can be maintained and this can facilitate the adsorption of Cu2+ on marmatite). Based on a comprehensive analysis of all our results, we propose that adding ammonium chloride to the copper sulfate changes the solution components (i.e., the presence of NH3(aq) and Cu(NH3)n2+) and then regulates the surface composition of marmatite. The change in surface composition improves the hydrophobicity of mineral surface and this leads to an improvement in activation of marmatite.

Description: Remote Sensing, Vol. 10, Pages 870: Low-Frequency Sea Surface Radar Doppler Echo Remote Sensing doi: 10.3390/rs10060870 Authors: Yury Yu. Yurovsky Vladimir N. Kudryavtsev Semyon A. Grodsky Bertrand Chapron The sea surface normalized radar backscatter cross-section (NRCS) and Doppler velocity (DV) exhibit energy at low frequencies (LF) below the surface wave peak. These NRCS and DV variations are coherent and thus may produce a bias in the DV averaged over large footprints, which is important for interpretation of Doppler scatterometer measurements. To understand the origin of LF variations, the platform-borne Ka-band radar measurements with well-pronounced LF variations at frequencies below wave peak (0.19 Hz) are analyzed. These data show that the LF NRCS is coherent with wind speed at 21 m height while the LF DV is not. The NRCS-wind correlation is significant only at frequencies below 0.01 Hz indicating either differences between near-surface wind (affecting radar signal) and 21-m height wind (actually measured) or contributions of other mechanisms of LF radar signal variations. It is shown that non-linearity in NRCS-wave slope Modulation Transfer Function (MTF) and inherent averaging within radar footprint account for NRCS and DV LF variance, with the exception of VV NRCS for which almost half of the LF variance is unexplainable by these mechanisms and perhaps attributable to wind fluctuations. Although the distribution of radar DV is quasi-Gaussian, suggesting virtually little impact of non-linearity, the LF DV variations arise due to footprint averaging of correlated local DV and non-linear NRCS. Numerical simulations demonstrate that MTF non-linearity weakly affects traditional linear MTF estimate (less than 10% for typical MTF magnitudes less than 20). Thus the linear MTF is a good approximation to evaluate the DV averaged over large footprints typical of satellite observations.

Description: Remote Sensing, Vol. 10, Pages 869: The Potential and Challenges of Using Soil Moisture Active Passive (SMAP) Sea Surface Salinity to Monitor Arctic Ocean Freshwater Changes Remote Sensing doi: 10.3390/rs10060869 Authors: Wenqing Tang Simon Yueh Daqing Yang Alexander Fore Akiko Hayashi Tong Lee Severine Fournier Benjamin Holt Sea surface salinity (SSS) links various components of the Arctic freshwater system. SSS responds to freshwater inputs from river discharge, sea ice change, precipitation and evaporation, and oceanic transport through the open straits of the Pacific and Atlantic oceans. However, in situ SSS data in the Arctic Ocean are very sparse and insufficient to depict the large-scale variability to address the critical question of how climate variability and change affect the Arctic Ocean freshwater. The L-band microwave radiometer on board the NASA Soil Moisture Active Passive (SMAP) mission has been providing SSS measurements since April 2015, at approximately 60 km resolution with Arctic Ocean coverage in 1–2 days. With improved land/ice correction, the SMAP SSS algorithm that was developed at the Jet Propulsion Laboratory (JPL) is able to retrieve SSS in ice-free regions 35 km of the coast. SMAP observes a large-scale contrast in salinity between the Atlantic and Pacific sides of the Arctic Ocean, while retrievals within the Arctic Circle vary over time, depending on the sea ice coverage and river runoff. We assess the accuracy of SMAP SSS through comparative analysis with in situ salinity data collected by Argo floats, ships, gliders, and in field campaigns. Results derived from nearly 20,000 pairs of SMAP and in situ data North of 50°N collocated within a 12.5-km radius and daily time window indicate a Root Mean Square Difference (RMSD) less than ~1 psu with a correlation coefficient of 0.82 and a near unity regression slope over the entire range of salinity. In contrast, the Hybrid Coordinate Ocean Model (HYCOM) has a smaller RMSD with Argo. However, there are clear systematic biases in the HYCOM for salinity in the range of 25–30 psu, leading to a regression slope of about 0.5. In the region North of 65°N, the number of collocated samples drops more than 70%, resulting in an RMSD of about 1.2 psu. SMAP SSS in the Kara Sea shows a consistent response to discharge anomalies from the Ob’ and Yenisei rivers between 2015 and 2016, providing an assessment of runoff impact in a region where no in situ salinity data are available for validation. The Kara Sea SSS anomaly observed by SMAP is missing in the HYCOM SSS, which assimilates climatological runoffs without interannual changes. We explored the feasibility of using SMAP SSS to monitor the sea surface salinity variability at the major Arctic Ocean gateways. Results show that although the SMAP SSS is limited to about 1 psu accuracy, many large salinity changes are observable. This may lead to the potential application of satellite SSS in the Arctic monitoring system as a proxy of the upper ocean layer freshwater exchanges with subarctic oceans.

Description: Remote Sensing, Vol. 10, Pages 934: Concentric Circle Pooling in Deep Convolutional Networks for Remote Sensing Scene Classification Remote Sensing doi: 10.3390/rs10060934 Authors: Kunlun Qi Qingfeng Guan Chao Yang Feifei Peng Shengyu Shen Huayi Wu Convolutional neural networks (CNNs) have been increasingly used in remote sensing scene classification/recognition. The conventional CNNs are sensitive to the rotation of the image scene, which will inevitably result in the misclassification of remote sensing scene images that belong to the same category. In this work, we equip the networks with a new pooling strategy, “concentric circle pooling”, to alleviate the above problem. The new network structure, called CCP-net can generate a concentric circle-based spatial-rotation-invariant representation of an image, hence improving the classification accuracy. The square kernel is adopted to approximate the circle kernels in concentric circle pooling, which is much more efficient and suitable for CNNs to propagate gradients. We implement the training of the proposed network structure with standard back-propagation, thus CCP-net is an end-to-end trainable CNNs. With these advantages, CCP-net should in general improve CNN-based remote sensing scene classification methods. Experiments using two publicly available remote sensing scene datasets demonstrate that using CCP-net can achieve competitive classification results compared with the state-of-art methods.

Description: Geosciences, Vol. 8, Pages 203: Response of Soils and Soil Ecosystems to the Pennsylvanian–Permian Climate Transition in the Upper Fluvial Plain of the Dunkard Basin, Southeastern Ohio, USA Geosciences doi: 10.3390/geosciences8060203 Authors: Daniel Hembree Jennifer Carnes Direct exposure of paleosols to the atmosphere during formation make them ideal for reconstructing paleoclimate. Paleosol and ichnofossil properties are dependently linked making it important to study them in tandem, to avoid errors in interpretation. Small scale studies (<1 km) yield high resolution data that can be used to assess allogenic processes through comparison of spatial and temporal trends. This study used field and laboratory analyses to gather data from Late Pennsylvanian to Early Permian Upper Monongahela and Lower Dunkard group paleosols on Ohio Route 33 in Meigs County, OH, USA. The physical and geochemical properties of the paleosols from the field sites indicate that channel migration was the primary control on paleosol formation in the study area, however, a clear climate signal was observed. The change in paleosol type and calculated mean annual precipitation (MAP) values indicate that the climate became more strongly seasonal and drier over the course of the Pennsylvanian–Permian transition with a temporary excursion to a more ever-wet climate with higher MAP, marked by the occurrence of the Waynesburg Coal at the Pennsylvanian–Permian boundary.

Description: IJGI, Vol. 7, Pages 218: A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7060218 Authors: Shifen Cheng Feng Lu Peng Peng Sheng Wu Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs) have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and, between 53.80% and 90.29%, for the expressway dataset. The results suggest that multi-view learning merits further attention for traffic-related data mining under such a dynamic and data-intensive environment, which owes to its comprehensive consideration of spatial correlation and heterogeneity as well as temporal fluctuation and regularity in road traffic.

Description: IJGI, Vol. 7, Pages 217: Deep Belief Networks Based Toponym Recognition for Chinese Text ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7060217 Authors: Shu Wang Xueying Zhang Peng Ye Mi Du In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is the foundation of mining this useful geo-referenced information by identifying words as toponyms in text. In this paper, we propose an adapted toponym recognition approach based on deep belief network (DBN) by exploring two key issues: word representation and model interpretation. A Skip-Gram model is used in the word representation process to represent words with contextual information that are ignored by current word representation models. We then determine the core hyper-parameters of the DBN model by illustrating the relationship between the performance and the hyper-parameters, e.g., vector dimensionality, DBN structures and probability thresholds. The experiments evaluate the performance of the Skip-Gram model implemented by the Word2Vec open-source tool, determine stable hyper-parameters and compare our approach with a conditional random field (CRF) based approach. The experimental results show that the DBN model outperforms the CRF model with smaller corpus. When the corpus size is large enough, their statistical metrics become approaching. However, their recognition results express differences and complementarity on different kinds of toponyms. More importantly, combining their results can directly improve the performance of toponym recognition relative to their individual performances. It seems that the scale of the corpus has an obvious effect on the performance of toponym recognition. Generally, there is no adequate tagged corpus on specific toponym recognition tasks, especially in the era of Big Data. In conclusion, we believe that the DBN-based approach is a promising and powerful method to extract geo-referenced information from text in the future.

Description: Atmosphere, Vol. 9, Pages 233: Snow Level Characteristics and Impacts of a Spring Typhoon-Originating Atmospheric River in the Sierra Nevada, USA Atmosphere doi: 10.3390/atmos9060233 Authors: Benjamin J. Hatchett On 5–7 April 2018, a landfalling atmospheric river resulted in widespread heavy precipitation in the Sierra Nevada of California and Nevada. Observed snow levels during this event were among the highest snow levels recorded since observations began in 2002 and exceeded 2.75 km for 31 h in the northern Sierra Nevada and 3.75 km for 12 h in the southern Sierra Nevada. The anomalously high snow levels and over 80 mm of precipitation caused flooding, debris flows, and wet snow avalanches in the upper elevations of the Sierra Nevada. The origin of this atmospheric river was super typhoon Jelawat, whose moisture remnants were entrained and maintained by an extratropical cyclone in the northeast Pacific. This event was notable due to its April occurrence, as six other typhoon remnants that caused heavy precipitation with high snow levels (mean = 2.92 km) in the northern Sierra Nevada all occurred during October.

Description: Remote Sensing, Vol. 10, Pages 961: Temporal and Spatial Characteristics of EVI and Its Response to Climatic Factors in Recent 16 years Based on Grey Relational Analysis in Inner Mongolia Autonomous Region, China Remote Sensing doi: 10.3390/rs10060961 Authors: Dong He Guihua Yi Tingbin Zhang Jiaqing Miao Jingji Li Xiaojuan Bie The Inner Mongolia Autonomous Region (IMAR) is a major source of rivers, catchment areas, and ecological barriers in the northeast of China, related to the nation’s ecological security and improvement of the ecological environment. Therefore, studying the response of vegetation to climate change has become an important part of current global change research. Since existing studies lack detailed descriptions of the response of vegetation to different climatic factors using the method of grey correlation analysis based on pixel, the temporal and spatial patterns and trends of enhanced vegetation index (EVI) are analyzed in the growing season in IMAR from 2000 to 2015 based on moderate resolution imaging spectroradiometer (MODIS) EVI data. Combined with the data of air temperature, relative humidity, and precipitation in the study area, the grey relational analysis (GRA) method is used to study the time lag of EVI to climate change, and the study area is finally zoned into different parts according to the driving climatic factors for EVI on the basis of lag analysis. The driving zones quantitatively show the characteristics of temporal and spatial differences in response to different climatic factors for EVI. The results show that: (1) The value of EVI generally features in spatial distribution, increasing from the west to the east and the south to the north. The rate of change is 0.22/10°E from the west to the east, 0.28/10°N from the south to the north; (2) During 2000–2015, the EVI in IMAR showed a slightly upward trend with a growth rate of 0.021/10a. Among them, the areas with slight and significant improvement accounted for 21.1% and 7.5% of the total area respectively, ones with slight and significant degradation being 24.6% and 4.3%; (3) The time lag analysis of climatic factors for EVI indicates that vegetation growth in the study area lags behind air temperature by 1–2 months, relative humidity by 1–2 months, and precipitation by one month respectively; (4) During the growing season, the EVI of precipitation driving zone (21.8%) in IMAR is much larger than that in the air temperature driving zone (8%) and the relative humidity driving zone (11.6%). The growth of vegetation in IMAR generally has the closest relationship with precipitation. The growth of vegetation does not depend on the change of a single climatic factor. Instead, it is the result of the combined action of multiple climatic factors and human activities.

Description: Remote Sensing, Vol. 10, Pages 959: The Temperature Vegetation Dryness Index (TVDI) Based on Bi-Parabolic NDVI-Ts Space and Gradient-Based Structural Similarity (GSSIM) for Long-Term Drought Assessment Across Shaanxi Province, China (2000–2016) Remote Sensing doi: 10.3390/rs10060959 Authors: Ying Liu Hui Yue Traditional NDVI-Ts space is triangular or trapezoidal, but Liu et al. (2015) discovered that the NDVI-Ts space was bi-parabolic when the study area was covered with low biomass vegetation. Moreover, the numerical value of the indicator was considered in most of the study when the drought conditions in the space domain were evaluated. In addition, quantitatively assessing the spatial-temporal changes of the drought was not enough. In this study, first, we used MODIS NDVI and Ts data to reexamine if the NDVI-Ts space with “time” and a single pixel domain is bi-parabolic in the Shaanxi province of China, which is vegetated with low biomass to high biomass. This is compared with the triangular NDVI-Ts space and one of the well-known drought indexes called the temperature-vegetation index (TVX). The results demonstrated that dry and wet edges exhibited a parabolic shape again in scatter plots of Ts and NDVI in the Shaanxi province, which was linear in the triangular NDVI-Ts space. The Temperature Vegetation Dryness Index (TVDIc) was obtained from bi-parabolic NDVI-Ts andTVDIt was obtained from the triangular NDVI-Ts space and TVX were compared with 10-cm depth relative soil moisture. By estimating the 10-cm depth soil moisture, TVDIc was better than TVDIt, which were all apparently better than TVX. Second, combined with MODIS data, the drought conditions of the study area were assessed by TVDIc between 2000 to 2016. Spatially, the drought in the Shaanxi Province between 2000 to 2016 were mainly distributed in the northwest, North Shaanxi, and the North and East Guanzhong plain. The drought area of the Shaanxi province accounted for 31.95% in 2000 and 27.65% in 2016, respectively. Third, we quantitatively evaluated the variation of the drought status by using Gradient-based Structural Similarity (GSSIM) methods. The area of the drought conditions significantly changed and moderately changed at 5.34% and 40.22%, respectively, between 2000 and 2016. Finally, the possible reasons for drought change were discussed. The change of precipitation, temperature, irrigation, destruction or betterment of vegetation, and the enlargement of opening mining, etc., can lead to the variations of drought.

Description: Remote Sensing, Vol. 10, Pages 963: A Seismic Capacity Evaluation Approach for Architectural Heritage Using Finite Element Analysis of Three-Dimensional Model: A Case Study of the Limestone Hall in the Ming Dynasty Remote Sensing doi: 10.3390/rs10060963 Authors: Siliang Chen Shaohua Wang Chen Li Qingwu Hu Hongjun Yang A lot of architectural heritage in China are urgently in need to carry out seismic assessment for further conservation. In this paper, a seismic capacity evaluation approach for architectural heritage using finite element analysis with precision three-dimensional data was proposed. The Limestone Hall of Shaanxi Province was taken as an example. First, low attitude unmanned aerial vehicle photogrammetry and a close-range photogrammetry camera were used to collect multiple view images to obtain the precision three-dimensional current model of the Limestone. Second, the dimensions of internal structures of Limestone Hall are obtained by means of structural analysis; re-establishing the ideal model of Limestone Hall based on the modeling software. Third, a finite element analysis was conducted to find out the natural frequency and seismic stress in various conditions with the 3D model using ANSYS software. Finally, the seismic capacity analysis results were comprehensively evaluated for the risk assessment and simulation. The results showed that for architectural heritage with a multilayer structure, utilizing photogrammetric surveying and mapping, 3D software modeling, finite element software simulation, and seismic evaluation for simulation was feasible where the precision of the modeling and parameters determine the accuracy of the simulation. The precise degree of the three-dimensional model, the accurate degree of parameter measurement and estimation, the setting of component attributes in the finite element model and the strategy of finite element analysis have an important effect on the result of seismic assessment. The main body structure of the Limestone Hall could resist an VII-degree earthquake at most, and the ridge of the second floor could not resist a V-degree earthquake due to unsupported conditions. The maximum deformation of the Limestone Hall during the earthquake occurred in the tabia layer below the second roof.

Description: Geosciences, Vol. 8, Pages 220: Clay Mineral Suites in Submarine Mud Volcanoes in the Kumano Forearc Basin, Nankai Trough: Constraints on the Origin of Mud Volcano Sediments Geosciences doi: 10.3390/geosciences8060220 Authors: Akira Ijiri Koichi Iijima Urumu Tsunogai Juichiro Ashi Fumio Inagaki Clay mineralogy is an important characteristic of mud volcano sediments. This study determined the clay mineral compositions of sediment from two submarine mud volcanoes in the Kumano forearc basin, Nankai Trough, by X-ray diffraction analysis. Similar compositions dominated by smectite in the two mud volcanoes indicate that the mud volcanoes in the basin are rooted in the same source sequence. These clay mineral compositions differed from those in Pleistocene basin sediment, suggesting that the mud volcano sediment originated beneath the Pleistocene sediment. The illite content in the illite–smectite mixed layer averaged 32% in the mud volcano sediment, which implies that the sediment experienced temperatures above 60 °C that promoted the smectite-to-illite transformation. However, porewater extracted from the mud volcano sediment had Cl‒ concentrations roughly half that of seawater and proportional enrichment in 18O and depletion in D, indicating that dehydration reactions of clay minerals had previously occurred in a deeply buried sedimentary layer. The smectite and illite contents (<60%) in the clay-size fraction rule out in situ smectite dewatering as the cause of the dilution of Cl‒ in porewater. Thus, fluids derived from clay dewatering must have originated from deeper than the source of the mud volcano sediment.

Description: IJGI, Vol. 7, Pages 222: A Citizen Science Approach for Collecting Toponyms ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7060222 Authors: Aji Putra Perdana Frank O. Ostermann The emerging trends and technologies of surveying and mapping potentially enable local experts to contribute and share their local geographical knowledge of place names (toponyms). We can see the increasing numbers of toponyms in digital platforms, such as OpenStreetMap, Facebook Place Editor, Swarm Foursquare, and Google Local Guide. On the other hand, government agencies keep working to produce concise and complete gazetteers. Crowdsourced geographic information and citizen science approaches offer a new paradigm of toponym collection. This paper addresses issues in the advancing toponym practice. First, we systematically examined the current state of toponym collection and handling practice by multiple stakeholders, and we identified a recurring set of problems. Secondly, we developed a citizen science approach, based on a crowdsourcing level of participation, to collect toponyms. Thirdly, we examined the implementation in the context of an Indonesian case study. The results show that public participation in toponym collection is an approach with the potential to solve problems in toponym handling, such as limited human resources, accessibility, and completeness of toponym information. The lessons learnt include the knowledge that the success of this approach depends on the willingness of the government to advance their workflow, the degree of collaboration between stakeholders, and the presence of a communicative approach in introducing and sharing toponym guidelines with the community.

Description: Geosciences, Vol. 8, Pages 222: Potential Indicator Value of Subfossil Gastropods in Assessing the Ecological Health of the Middle and Lower Reaches of the Yangtze River Floodplain System (China) Geosciences doi: 10.3390/geosciences8060222 Authors: Giri Kattel Yongjiu Cai Xiangdong Yang Ke Zhang Xu Hao Rong Wang Xuhui Dong The lakes across China’s middle and lower reaches of the Yangtze River system have a long history of sustaining human pressures. These aquatic resources have been exploited for fisheries and irrigation over millennia at a magnitude of scales, with the result that many lakes have lost their ecological integrity. The consequences of these changes in the ecosystem health of lakes are not fully understood; therefore, a long-term investigation is urgently needed. Gastropods (aquatic snails) are powerful bio-indicators that link primary producers, herbivores, and detritivores associated with macrophytes and grazers of periphyton and higher-level consumers. They are sensitive to abrupt environmental change such as eutrophication, dehydration, flooding, and proliferation of toxicity in floodplain lake systems. The use of the remains of gastropod shells (subfossils) preserved in the sedimentary archives of the floodplain lakes of the middle and lower reaches of the Yangtze River system holds high significance, as their potential in environmental change has not been studied in detail in the past. Here, we aim to test the hypothesis that modern and sub-fossil gastropods in the sediments of the middle and lower reaches of the Yangtze River floodplains systems have significant value as bioindicators, as they have the ability to reveal health-gradients of lake-ecosystem change in the region.

Description: Remote Sensing, Vol. 10, Pages 975: A Hybrid Analytic Network Process and Artificial Neural Network (ANP-ANN) Model for Urban Earthquake Vulnerability Assessment Remote Sensing doi: 10.3390/rs10060975 Authors: Mohsen Alizadeh Ibrahim Ngah Mazlan Hashim Biswajeet Pradhan Amin Beiranvand Pour Vulnerability assessment is one of the prerequisites for risk analysis in disaster management. Vulnerability to earthquakes, especially in urban areas, has increased over the years due to the presence of complex urban structures and rapid development. Urban vulnerability is a result of human behavior which describes the extent of susceptibility or resilience of social, economic, and physical assets to natural disasters. The main aim of this paper is to develop a new hybrid framework using Analytic Network Process (ANP) and Artificial Neural Network (ANN) models for constructing a composite social, economic, environmental, and physical vulnerability index. This index was then applied to Tabriz City, which is a seismic-prone province in the northwestern part of Iran with recurring devastating earthquakes and consequent heavy casualties and damages. A Geographical Information Systems (GIS) analysis was used to identify and evaluate quantitative vulnerability indicators for generating an earthquake vulnerability map. The classified and standardized indicators were subsequently weighed and ranked using an ANP model to construct the training database. Then, standardized maps coupled with the training site maps were presented as input to a Multilayer Perceptron (MLP) neural network for producing an Earthquake Vulnerability Map (EVM). Finally, an EVM was produced for Tabriz City and the level of vulnerability in various zones was obtained. South and southeast regions of Tabriz City indicate low to moderate vulnerability, while some zones of the northeastern tract are under critical vulnerability conditions. Furthermore, the impact of the vulnerability of Tabriz City on population during an earthquake was included in this analysis for risk estimation. A comparison of the result produced by EVM and the Population Vulnerability (PV) of Tabriz City corroborated the validity of the results obtained by ANP-ANN. The findings of this paper are useful for decision-makers and government authorities to obtain a better knowledge of a city’s vulnerability dimensions, and to adopt preparedness strategies in the future for Tabriz City. The developed hybrid framework of ANP and ANN Models can easily be replicated and applied to other urban regions around the world for sustainability and environmental management.

Description: Atmosphere, Vol. 9, Pages 237: Macro- and Microphysical Characteristics of Precipitating and Non-Precipitating Stratocumulus Clouds over Eastern China Atmosphere doi: 10.3390/atmos9070237 Authors: Sicong Li Yunying Li Guorong Sun Zhixian Lu Stratocumulus (Sc) is the most common cloud type in China. Sc clouds may or may not be accompanied by various types of precipitation that are representative of different macro- and microphysical characteristics. The finely resolved CloudSat data products are used in this study to quantitatively investigate the macro- and microphysical characteristics of precipitating and non-precipitating Sc (PS and NPS, respectively) clouds over Eastern China (EC). Based on statistical information extracted from the CloudSat data, Sc clouds are highly likely to occur alone, in association with liquid precipitation, or in association with drizzle over 25% of EC. The cloud bases of NPS clouds are higher than those of PS clouds, although the latter display higher cloud top heights and thicker cloud thicknesses. The spatial distributions of microphysical characteristics differ between PS and NPS clouds. The magnitudes of microphysical characteristics in NPS clouds are relatively small, whereas the magnitudes of microphysical characteristics in PS clouds are relatively large and peak in response to certain circulation patterns and over certain terrain. In NPS clouds, condensation is the primary mechanism for hydrometeor particle growth, and the liquid water content and effective radius increase with height. Once the particles are too large to be supported by the updrafts, cloud droplets form raindrops. In PS clouds, raindrops increase continuously in size via collision-coalescence processes as they fall, leading to an increase in the liquid water content and effective radius from cloud top to cloud base. The CFRHDs (contoured frequency by relative height diagrams) of radar reflectivity in different cloud thickness indicate the cloud evolution and the precipitation formation process. In thinner clouds, downward particle growth by coalescence and upward particle growth by condensation occur in the upper and lower layers of clouds, respectively. With the increases in cloud thickness, the collision-coalescence process becomes apparent in all cloud layers, and the upward condensation process is less pronounced near the cloud base. Particles can grow for a long period of time and increase to larger sizes in thicker clouds, resulting in increased precipitation frequency. In clouds thicker than 1.92 km, the continuous transition from cloud to drizzle to rain by the collision-coalescence process takes place mostly in the upper layers.

Description: IJGI, Vol. 7, Pages 232: A RSSI/PDR-Based Probabilistic Position Selection Algorithm with NLOS Identification for Indoor Localisation ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7060232 Authors: Ke Han Huashuai Xing Zhongliang Deng Yichen Du In recent years, location-based services have been receiving increasing attention because of their great development prospects. Researchers from all over the world have proposed many solutions for indoor positioning over the past several years. However, owing to the dynamic and complex nature of indoor environments, accurately and efficiently localising targets in indoor environments remains a challenging problem. In this paper, we propose a novel indoor positioning algorithm based on the received signal strength indication and pedestrian dead reckoning. In order to enhance the accuracy and reliability of our proposed probabilistic position selection algorithm in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) environments, a low-complexity identification approach is proposed to identify the change in the channel situation between NLOS and LOS. Numerical experiment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional methods in mixed LOS and NLOS indoor environments.

Description: IJGI, Vol. 7, Pages 229: Automated Orthorectification of VHR Satellite Images by SIFT-Based RPC Refinement ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7060229 Authors: Hakan Kartal Ugur Alganci Elif Sertel Raw remotely sensed images contain geometric distortions and cannot be used directly for map-based applications, accurate locational information extraction or geospatial data integration. A geometric correction process must be conducted to minimize the errors related to distortions and achieve the desired location accuracy before further analysis. A considerable number of images might be needed when working over large areas or in temporal domains in which manual geometric correction requires more labor and time. To overcome these problems, new algorithms have been developed to make the geometric correction process autonomous. The Scale Invariant Feature Transform (SIFT) algorithm is an image matching algorithm used in remote sensing applications that has received attention in recent years. In this study, the effects of the incidence angle, surface topography and land cover (LC) characteristics on SIFT-based automated orthorectification were investigated at three different study sites with different topographic conditions and LC characteristics using Pleiades very high resolution (VHR) images acquired at different incidence angles. The results showed that the location accuracy of the orthorectified images increased with lower incidence angle images. More importantly, the topographic characteristics had no observable impacts on the location accuracy of SIFT-based automated orthorectification, and the results showed that Ground Control Points (GCPs) are mainly concentrated in the “Forest” and “Semi Natural Area” LC classes. A multi-thread code was designed to reduce the automated processing time, and the results showed that the process performed 7 to 16 times faster using an automated approach. Analyses performed on various spectral modes of multispectral data showed that the arithmetic data derived from pan-sharpened multispectral images can be used in automated SIFT-based RPC orthorectification.

Description: Geosciences, Vol. 8, Pages 226: Geophysical Input to Improve the Conceptual Model of the Hydrogeological Framework of a Coastal Karstic Aquifer: Uley South Basin, South Australia Geosciences doi: 10.3390/geosciences8070226 Authors: Nara Somaratne Glyn Ashman Michelle Irvine Simon Mann A lack of closely spaced datasets on layer elevations, aquifer parameters, identification of areas with high recharge potential, dominant conduit porosity zones, and well defined boundary conditions hampers the ability of groundwater models to produce a reliable water balance. Typically, geological structure, aquifer properties, and groundwater heads are obtained from point measurements which are sparse. The drillhole information in aquifers is usually available at locations far apart, distances ranging from hundreds to thousands of meters. Furthermore, pump tests are usually conducted at limited locations and generalized to the aquifer. This limited knowledge leads to errors in the conceptual understanding of the aquifer. In this study, Airborne Electromagnetic Survey (AEM) was used to define base elevations of the aquifers where drillhole information was lacking. Surface Nuclear Magnetic Resonance (sNMR), borehole NMR, Transient Electromagnetic (TEM), and downhole geophysical surveys have given new insight to the conceptualization of hydrogeological framework. These methods are relatively low in cost compared to traditional well drilling and provide information on layer elevations, aquifer parameters, point and diffuse recharge zones, and conduit porosity zones in the profile, which improves our definition of the boundary conditions. From a practical point of view, combining drillhole information with a variety of geophysical techniques provides sound datasets to develop a comprehensive conceptual model. This in turn can be used to build a robust groundwater model.

Description: Remote Sensing, Vol. 10, Pages 976: Physical Retrieval of Land Surface Emissivity Spectra from Hyper-Spectral Infrared Observations and Validation with In Situ Measurements Remote Sensing doi: 10.3390/rs10060976 Authors: Guido Masiello Carmine Serio Sara Venafra Giuliano Liuzzi Laurent Poutier Frank-M. Göttsche A fully physical retrieval scheme for land surface emissivity spectra is presented, which applies to high spectral resolution infrared observations from satellite sensors. The surface emissivity spectrum is represented with a suitably truncated Principal Component Analysis (PCA) transform and PCA scores are simultaneously retrieved with surface temperature and atmospheric parameters. The retrieval methodology has been developed within the general framework of Optimal Estimation and, in this context, is the first physical scheme based on a PCA representation of the emissivity spectrum. The scheme has been applied to IASI (Infrared Atmospheric Sounder Interferometer) and the retrieved emissivities have been validated with in situ observations acquired during a field experiment carried out in 2017 at Gobabeb (Namib desert) validation station. It has been found that the retrieved emissivity spectra are independent of background information and in good agreement with in situ observations.

Description: IJGI, Vol. 7, Pages 244: Shaking Maps Based on Cumulative Absolute Velocity and Arias Intensity: The Cases of the Two Strongest Earthquakes of the 2016–2017 Central Italy Seismic Sequence ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7070244 Authors: Antonio Costanzo By referring to the two strongest earthquakes of the 2016–2017 Central Italy seismic sequence, this paper presents a procedure to make shaking maps through empirical relationships between macroseismic intensity and ground-motion parameters. Hundreds of waveforms were processed to obtain instrumental ground-motion features which could be correlated with the potential damage intensities. To take into account peak value, frequency, duration, and energy content, which all contribute to damage, cumulative absolute velocity and Arias intensity were used to quantify the features of the ground motion. Once these parameters had been calculated at the recording sites, they were interpolated through geostatistical techniques on the whole struck area. Finally, empirical relationships were used for mapping intensities, i.e., potential effects on the built environment. The results referred to both earthquake scenarios that were analyzed and were also used for assessing the influence of the spatial coverage of the instrumental network. In fact, after the first events, the Italian seismic network was subjected to the addition and thickening of sensors in the epicentral area, especially. The results obtained by models only dependent on ground-motion parameters or even on the epicentral distance were compared with the official ShakeMaps and the observed intensities for assessing their reliability. Finally, some suggestions are proposed to improve the procedure that could be used for rapidly assessing ground shaking and mapping damage potential producing useful information for non-expert audience.

Description: IJGI, Vol. 7, Pages 242: Seamless Upscaling of the Field-Measured Grassland Aboveground Biomass Based on Gaussian Process Regression and Gap-Filled Landsat 8 OLI Reflectance ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7070242 Authors: Gaofei Yin Ainong Li Chaoyang Wu Jiyan Wang Qiaoyun Xie Zhengjian Zhang Xi Nan Huaan Jin Jinhu Bian Guangbin Lei The spatially explicit aboveground biomass (AGB) generated through upscaling field measurements is critical for carbon cycle simulation and optimized management of grasslands. However, the spatial gaps that exist in the optical remote sensing data, underutilization of the multispectral data cube and unavailability of uncertainty information hinder the generation of seamless and accurate AGB maps. This study proposes a novel framework to address the above challenges. The proposed framework filled the spatial gaps in the remote sensing data via the consistent adjustment of the climatology to actual observations (CACAO) method. Gaussian process regression (GPR) was used to fully exploit the multispectral data cube and generated the pixelwise uncertainty concurrent with the AGB estimation. A case study in a 100 km × 100 km area located in the Zoige Plateau, China was used to evaluate this framework. The results show that the CACAO method can fill almost all of the gaps, accounting for 93.1% of the study area, with satisfactory accuracy. The generated AGB map from the GPR was characterized by a relatively high accuracy (R2 = 0.64, RMSE = 48.13 g/m2) compared to vegetation index-derived ones, and was accompanied by a corresponding uncertainty map that provides a new source of information on the credibility of each pixel. This study demonstrates the potential of the joint use of gap-filling and machine-learning methods to generate spatially explicit AGB.

Description: Remote Sensing, Vol. 10, Pages 993: Landslide Identification and Monitoring along the Jinsha River Catchment (Wudongde Reservoir Area), China, Using the InSAR Method Remote Sensing doi: 10.3390/rs10070993 Authors: Chaoying Zhao Ya Kang Qin Zhang Zhong Lu Bin Li Landslide identification and monitoring are two significant research aspects for landslide analysis. In addition, landslide mode deduction is key for the prevention of landslide hazards. Surface deformation results with different scales can serve for different landslide analysis. L-band synthetic aperture radar (SAR) data calculated with Interferometric Point Target Analysis (IPTA) are first employed to detect potential landslides at the catchment-scale Wudongde reservoir area. Twenty-two active landslides are identified and mapped over more than 2500 square kilometers. Then, for one typical landslide, Jinpingzi landslide, its spatiotemporal deformation characteristics are analyzed with the small baseline subsets (SBAS) interferometric synthetic aperture radar (InSAR) technique. High-precision surface deformation results are obtained by comparing with in-situ georobot measurements. The spatial deformation pattern reveals the different stabilities among five different sections of Jinpingzi landslide. InSAR results for Section II of Jinpingzi landslide show that this active landslide is controlled by two boundaries and geological structure, and its different landslide deformation magnitudes at different sections on the surface companying with borehole deformation reveals the pull-type landslide mode. Correlation between time series landslide motion and monthly precipitation, soil moisture inverted from SAR intensity images and water level fluctuations suggests that heavy rainfall is the main trigger factor, and the maximum deformation of the landslide was highly consistent with the peak precipitation with a time lag of about 1 to 2 months, which gives us important guidelines to mitigate and prevent this kind of hazard.

Description: Minerals, Vol. 8, Pages 263: Effect of TiO2 on the Sintering Behavior of Chromium-Bearing Vanadium–Titanium Magnetite Minerals doi: 10.3390/min8070263 Authors: Weidong Tang Songtao Yang Gongjin Cheng Zixian Gao He Yang Xiangxin Xue The sintering pot test was used to investigate the effect of TiO2 on the sintering behavior of chromium-bearing vanadium–titanium magnetite (CVTM) sinter. The main characterization methods of X-ray fluorescence (XRF), X-ray diffraction (XRD), scanning electron microscopy-energy disperse spectroscopy (SEM-EDS), and metallographic microscopy were employed. In this study, yield, tumbler index (TI), vertical sintering speed, productivity, reduction degradation index (RDI), and reduction index (RI) were tested and calculated. The yield first increases from 82.87% to 84.37% and then decreases to 83.65%, vertical sintering speed first increases from 17.00 mm·min−1 to 23.45 mm·min−1 and then decreases to 20.61 mm·min−1, and productivity first increases from 2.33 t·m−2·h−1 to 3.14 t·m−2·h−1 and then decreases to 2.69 t·m−2·h−1 with increasing TiO2 content. The TI increases from 45.81% to 52.09%, and RDI increases from 74.99% to 96.74%, while RI decreases from 67.92% to 47.15% with increasing TiO2 content.

Description: Remote Sensing, Vol. 10, Pages 1000: Post-Fire Vegetation Succession and Surface Energy Fluxes Derived from Remote Sensing Remote Sensing doi: 10.3390/rs10071000 Authors: Xuedong Li Hongyan Zhang Guangbin Yang Yanling Ding Jianjun Zhao The increasing frequency of fires inhibits the estimation of carbon reserves in boreal forest ecosystems because fires release significant amounts of carbon into the atmosphere through combustion. However, less is known regarding the effects of vegetation succession processes on ecosystem C-flux that follow fires. This paper describes intra- and inter-annual vegetation restoration trajectories via MODIS time-series and Landsat data. The temporal and spatial characteristics of the natural succession were analyzed from 2000 to 2016. Finally, we regressed post-fire MODIS EVI, LST and LSWI values onto GPP and NPP values to identify the main limiting factors during post-fire carbon exchange. The results show immediate variations after the fire event, with EVI and LSWI decreasing by 0.21 and 0.31, respectively, and the LST increasing to 6.89 °C. After this initial variation, subsequent fire-induced variations were significantly smaller; instead, seasonality began governing the change characteristics. The greatest differences in EVI, LST and LSWI were observed in August and September compared to those in other months (0.29, 6.9 and 0.35, respectively), including July, which was the second month after the fire. We estimated the mean EVI recovery periods under different fire intensities (approximately 10, 12 and 16 years): the LST recovery time is one year earlier than that of the EVI. GPP and NPP decreased after the fire by 22–45 g C·m−2·month−1 (30–80%) and 0.13–0.35 kg C·m−2·year−1 (20–60%), respectively. Excluding the winter period, when no photosynthesis occurred, the correlation between the EVI and GPP was the strongest, and the correlation coefficient varied with the burn intensity. When changes in EVI, LST and LSWI after the fire in the boreal forest were more significant, the severity of the fire determined the magnitude of the changes, and the seasonality aggravated these changes. On the other hand, the seasonality is another important factor that affects vegetation restoration and land-surface energy fluxes in boreal forests. The strong correlations between EVI and GPP/NPP reveal that the C-flux can be simply and directly estimated on a per-pixel basis from EVI data, which can be used to accurately estimate land-surface energy fluxes during vegetation restoration and reduce uncertainties in the estimation of forests’ carbon reserves.

Description: Geosciences, Vol. 8, Pages 233: Site Effect Assessment of the Gros-Morne Hill Area in Port-au-Prince, Haiti, Part B: Mapping and Modelling Results Geosciences doi: 10.3390/geosciences8070233 Authors: Sophia Ulysse Dominique Boisson Claude Prépetit Hans-Balder Havenith This paper presents the general results in terms of maps, as well as geological and numerical models of a site effect study, that aimed at a better understanding of the ground motion amplification on the Gros-Morne hill, in the southeastern part of Port-au-Prince, Haiti, which might have influenced the 2010 event damage pattern in that area. These maps and models are based on multiple geophysical–seismological survey outputs that are presented, in detail, in Part A of this publication. Those outputs include electrical resistivity tomography sections, P-wave velocity profiles, S-wave logs, estimates of the fundamental resonance frequency for many locations, as well as earthquake recordings at three sites and associated site amplification assessment for the top of the hill. Related results are discussed in Part A with respect to outputs and interpretations that had been published earlier by other research teams for the same site. Our results only partly confirm the strong seismic amplification effects highlighted by some of the previous studies for this hill site, which had been attributed to the influence of local topographic and soil characteristics on seismic ground motion. Here, we focus on the imaging of different site effect components over the entire survey area; we present maps of shear wave velocity variations, of changing fundamental resonance frequencies, and of related estimates of soft soil/rock thickness, of peak spectral amplitudes, and of ambient ground motion polarization. Results have also been compiled within a 3D surface–subsurface model of the hill, which helps visualize the geological characteristics of the area, which are relevant for site effect analyses. From the 3D geomodel, we extracted one 2D geological section along the short-axis of the hill, crossing it near the location of Hotel Montana on top of the hill, which had been destroyed during the earthquake, and has now been rebuilt. This cross-section was used for dynamic numerical modelling of seismic ground motion, and for related site amplification calculation. The numerical results are compared with the site amplification characteristics that had been estimated from the ambient vibration measurements and the earthquake recordings.

Description: Atmosphere, Vol. 9, Pages 241: Comment on “Spatial and Temporal Trends in the Location of the Lifetime Maximum Intensity of Tropical Cyclones” by Tennille and Ellis Atmosphere doi: 10.3390/atmos9070241 Authors: James Kossin The latitude where tropical cyclones (TCs) reach their peak intensity has migrated poleward in some regions [...]

Description: Minerals, Vol. 8, Pages 270: Multi-Stage Deformation of the Khangalas Ore Cluster (Verkhoyansk-Kolyma Folded Region, Northeast Russia): Ore-Controlling Reverse Thrust Faults and Post-Mineral Strike-Slip Faults Minerals doi: 10.3390/min8070270 Authors: Valery Y. Fridovsky Maxim V. Kudrin Lena I. Polufuntikova This study reports the results of the analysis of multi-stage deformation structures of the Khangalas gold ore cluster, northeast Russia. Four Late Mesozoic-Early Eocene deformation stages were identified. The first deformation event (D1) was characterized by the development of NW-striking tight to isoclinal folds of the first generation (F1) and interstratal detachment thrusts. Major folds, extensive thrusts, boudinage, cleavage, auriferous mineralized fault zones and quartz-vein gold mineralization were formed in the reverse and thrust fault stress field during the progressive deformation stage (D1), with NE-SW-oriented σ1. Post-ore deformation is widely manifested in the region. Structures D2 and D3 are coaxial. Sinistral strike-slip motions (D2 and D3) occurred along NW-trending faults under prevailing W-E compression. They were accompanied by the formation of NS- and NE-striking F2–3 folds with steep hinges and by bending of the earlier formed structures, among them ore-controlling ones. The last deformation event (D4) was represented by normal-dextral strike-slip faulting, refolding of rocks, pre-existing structures and ore bodies and by the development of folds with steep hinges. Key structural elements of varying age are described, the chronology of deformation events and mineralization reconstructed and their relation to geodynamic events in northeast Asia established.

Description: Remote Sensing, Vol. 10, Pages 1018: An Appraisal of the Potential of Landsat 8 in Estimating Chlorophyll-a, Ammonium Concentrations and Other Water Quality Indicators Remote Sensing doi: 10.3390/rs10071018 Authors: Vassiliki Markogianni Dionissios Kalivas George P. Petropoulos Elias Dimitriou In-situ monitoring of lake water quality in synergy with satellite remote sensing represents the latest scientific trend in many water quality monitoring programs worldwide. This study investigated the suitability of the Operational Land Imager (OLI) instrument onboard the Landsat 8 satellite platform in accurately estimating key water quality parameters such as chlorophyll-a and nutrient concentrations. As a case study the largest freshwater body of Greece (Trichonis Lake) was used. Two Landsat 8 images covering the study site were acquired on 30 October 2013 and 30 August 2014 respectively. Near concurrent in-situ observations from two water sampling campaigns were also acquired from 22 stations across the lake under study. In-situ measurements (nutrients and chlorophyll-a concentrations) were statistically correlated with various spectral band combinations derived from the Landsat imagery of year 2014. Subsequently, the most statistically promising predictive models were applied to the satellite image of 2013 and validation was conducted using in-situ data of 2013 as reference. Results showed a relatively variable statistical relationship between the in-situ and reflectances (R logchl-a: 0.58, R NH4+: 0.26, R chl-a: 0.44). Correlation coefficient (R) values reported of up to 0.7 for ammonium concentrations and also up to 0.5 and up to 0.4 for chl-a concentration and chl-a concentrations respectively. These results represent a higher accuracy of Landsat 8 in comparison to its predecessors in the Landsat satellites series, as evidenced in the literature. Our findings suggest that Landsat 8 has a promising capability in estimating water quality components in an oligotrophic freshwater body characterized by a complete absence of any quantitative, temporal and spatial variance, as is the case of Trichonis lake. Yet, even with the presence of a lot of ground information as was the case in our study, a quantitatively accurate estimation of water quality constituents in coastal/inland waters remains a great challenge. The launch of sophisticated spaceborne sensing systems, such as that of Landsat 8, can assist in improving our ability to estimate freshwater lake properties from space.

Description: IJGI, Vol. 7, Pages 251: Optical Satellite Image Geo-Positioning with Weak Convergence Geometry ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7070251 Authors: Yang Wu Yongsheng Zhang Donghong Wang Delin Mo High-resolution optical satellites are widely used in environmental monitoring. With the aim to observe the largest possible coverage, the overlapping areas and intersection angles of respective optical satellite images are usually small. However, the conventional bundle adjustment method leads to erroneous results or even failure under conditions of weak geometric convergence. By transforming the traditional stereo adjustment to a planar adjustment and combining it with linear programming (LP) theory, a new method that can solve the bias compensation parameters of all satellite images is proposed in this paper. With the support of freely available open source digital elevation models (DEMs) and sparse ground control points (GCPs), the method can not only ensure the consistent inner precision of all images, but also the absolute geolocation accuracy of the ground points. Tests of the two data sets covering different landscapes validated the effectiveness and feasibility of the method. The results showed that the geo-positioning performance of the method was better in regions of smaller topographic relief or for satellite images with a larger imaging altitude angle. The best accuracy of image geolocation with weak convergence geometry was as high as to 3.693 m in the horizontal direction and 6.510 m in the vertical direction, which is a level of accuracy equal to that of images with good intersection conditions.

Description: Remote Sensing, Vol. 10, Pages 1022: Improving the Estimation of Daily Aerosol Optical Depth and Aerosol Radiative Effect Using an Optimized Artificial Neural Network Remote Sensing doi: 10.3390/rs10071022 Authors: Wenmin Qin Lunche Wang Aiwen Lin Ming Zhang Muhammad Bilal Aerosols can absorb and scatter surface solar radiation (SSR), which is called the aerosol radiative forcing effect (ARF). Great efforts have been made for the estimation of the aerosol optical depth (AOD), SSR and ARF using meteorological measurements and satellite observations. However, the accuracy, and spatial and temporal resolutions of these existing AOD, SSR and ARF models should be improved to meet the application requirements, due to the uncertainties and gaps of input parameters. In this study, an optimized back propagation (BP) artificial neural network (Genetic_BP) was developed for improving the estimation of the AOD values. The retrieved AOD values using the Genetic_BP model and meteorological measurements at China Meteorological Administration (CMA) stations were used to calculate SSR and bottom of the atmosphere (BOA) ARF (ARFB) using Yang’s Hybrid model (YHM). The result show that the Genetic_BP could be used for estimating AOD values with high accuracy (R = 0.866 for CASNET (China Aerosol Remote Sensing Network) stations and R = 0.865 for AERONET (Aerosol Robotic Network) stations). The estimated SSR also showed a good agreement with SSR measurements at 96 CMA radiation stations, with RMSE, MAE, R and R2 of 29.27%, 23.77%, 0.948, and 0.899, respectively. The estimated ARFB values are also highly correlated with the AERONET ARFB ones with RMSE, MAE, R and R2 of −35.47%, −25.33%, 0.843, and 0.711, respectively. Finally, the spatial and temporal variations of AOD, SSR, and ARFB values over Mainland China were investigated. Both AOD and SSR values are generally higher in summer than in other seasons. The ARFB are generally stronger in spring and summer than in other seasons. The ranges for the monthly mean AOD, SSR and ARFB values over Mainland China are 0.183–0.333, 10.218–24.196 MJ m−2day−1 and −2.986 to −1.244 MJ m−2day−1, respectively. The Qinghai-Tibetan Plateau has always been an area with the highest SSR, the lowest AOD and the weakest ARFB. In contrast, the Sichuan Basin has always been an area with low SSR, high AOD, and strong ARFB. The newly proposed AOD model may be of vital importance for improving the accuracy and computational efficiency of AOD, SSR and ARFB estimations for solar energy applications, ecological modeling, and energy policy.

Description: IJGI, Vol. 7, Pages 299: Drift-Aware Monocular Localization Based on a Pre-Constructed Dense 3D Map in Indoor Environments ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080299 Authors: Guanyuan Feng Lin Ma Xuezhi Tan Danyang Qin Recently, monocular localization has attracted increased attention due to its application to indoor navigation and augmented reality. In this paper, a drift-aware monocular localization system that performs global and local localization is presented based on a pre-constructed dense three-dimensional (3D) map. In global localization, a pixel-distance weighted least squares algorithm is investigated for calculating the absolute scale for the epipolar constraint. To reduce the accumulative errors that are caused by the relative position estimation, a map interaction-based drift detection method is introduced in local localization, and the drift distance is computed by the proposed line model-based maximum likelihood estimation sample consensus (MLESAC) algorithm. The line model contains a fitted line segment and some visual feature points, which are used to seek inliers of the estimated feature points for drift detection. Taking advantage of the drift detection method, the monocular localization system switches between the global and local localization modes, which effectively keeps the position errors within an expected range. The performance of the proposed monocular localization system is evaluated on typical indoor scenes, and experimental results show that compared with the existing localization methods, the accuracy improvement rates of the absolute position estimation and the relative position estimation are at least 30.09% and 65.59%, respectively.

Description: IJGI, Vol. 7, Pages 297: The Negative Effects of Alcohol Establishment Size and Proximity on the Frequency of Violent and Disorder Crime across Block Groups of Victoria, British Columbia ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080297 Authors: Jessica L. Fitterer Trisalyn A. Nelson Timothy Stockwell Multiple studies have associated the density of alcohol establishments with crime. What is not well understood is the influence of establishment patron capacity on the magnitude of crime in an area, or how the spacing of liquor primary establishments impacts crime levels. Using a Poisson spatial lag model, we estimated how patron capacity of on-premises licenses and the total number of off-premises licenses were associated with the frequency of violent and disorder crime occurring on Friday and Saturday nights in Victoria, British Columbia. To identify how the distance between bars and pubs was associated with the frequency of crime within 200 m of each establishment, we applied bivariate curve fitting and change detection techniques. Our model explained 76% percent of the variance in crime frequencies. Bars and pubs within block groups, and in neighboring block groups, had a significant positive association (p < 0.05) with the frequency of crime compared to other on-premises licenses (e.g., restaurants, theatres, clubs, hotels), and off-premises liquor stores. For every additional 1111 bar or pub patron seats the crime frequency per block group is expected to double over a 17 month period (factor of 1.0009 per patron seat). Crime frequency significantly dropped (p < 0.05) around (200 m) bars and pubs that are spaced greater than 300 m apart. Our results provide the first evidenced-based information for evaluating the size and spacing of on-premises licenses in Canada.

Description: IJGI, Vol. 7, Pages 298: Grid-Based Crime Prediction Using Geographical Features ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080298 Authors: Ying-Lung Lin Meng-Feng Yen Liang-Chih Yu Machine learning is useful for grid-based crime prediction. Many previous studies have examined factors including time, space, and type of crime, but the geographic characteristics of the grid are rarely discussed, leaving prediction models unable to predict crime displacement. This study incorporates the concept of a criminal environment in grid-based crime prediction modeling, and establishes a range of spatial-temporal features based on 84 types of geographic information by applying the Google Places API to theft data for Taoyuan City, Taiwan. The best model was found to be Deep Neural Networks, which outperforms the popular Random Decision Forest, Support Vector Machine, and K-Near Neighbor algorithms. After tuning, compared to our design’s baseline 11-month moving average, the F1 score improves about 7% on 100-by-100 grids. Experiments demonstrate the importance of the geographic feature design for improving performance and explanatory ability. In addition, testing for crime displacement also shows that our model design outperforms the baseline.

Description: Minerals, Vol. 8, Pages 329: The Impact of Secondary Phyllosilicate Minerals on the Engineering Properties of Various Igneous Aggregates from Greece Minerals doi: 10.3390/min8080329 Authors: Petros Petrounias Panagiota P. Giannakopoulou Aikaterini Rogkala Paraskevi Lampropoulou Eleni Koutsopoulou Dimitrios Papoulis Basilios Tsikouras Konstantin Hatzipanagiotou This paper investigates the effect of alteration on the physicomechanical properties of igneous rocks used as aggregates, from various areas from Greece. The studied lithologies include serpentinized dunites, serpentinized harzburgites, serpentinized lherzolites, metamorphic gabbros, diabases, dacites and andesites. Quantitative petrographic analysis shows that the tested samples display various percentages of secondary phyllosilicate minerals. Mineral quantification of the studied rock samples was performed by using the Rietveld method on X-ray diffraction patterns. The samples were also tested to assign moisture content (w (%)), total porosity (nt (%)), uniaxial compressive strength (UCS (MPa)) and Los Angeles abrasion test (LA (%)). The influence of secondary phyllosilicate minerals on the physicomechanical behavior of the tested samples was determined using regression analysis and their derived equations. Regression analysis shows a positive relationship between the percentage of the phyllosilicate minerals of the rocks and the moisture content as well as with the total porosity values. In mafic and ultramafic rock samples, the relationships between the secondary phyllosilicate minerals and their physicomechanical properties have shown that the total amount of the secondary phyllosilicate minerals results negatively on their physicomechanical properties. On the other hand, the low percentage of phyllosilicate minerals in volcanic rocks can’t be able to define their engineering properties.

Description: IJGI, Vol. 7, Pages 306: Satellite-Derived Bathymetry for Improving Canadian Hydrographic Service Charts ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080306 Authors: René Chénier Marc-André Faucher Ryan Ahola Approximately 1000 Canadian Hydrographic Service (CHS) charts cover Canada’s oceans and navigable waters. Many charts use information collected with techniques that predate the more advanced technologies available to Hydrographic Offices (HOs) today. Furthermore, gaps in survey data, particularly in the Canadian Arctic where only 6% of waters are surveyed to modern standards, are also problematic. Through a Canadian Space Agency (CSA) Government Related Initiatives Program (GRIP) project, CHS is exploring remote sensing techniques to assist with the improvement of Canadian navigational charts. Projects exploring optical/Synthetic Aperture Radar (SAR) shoreline extraction and change detection, as well as optical Satellite-Derived Bathymetry (SDB), are currently underway. This paper focuses on SDB extracted from high-resolution optical imagery, highlighting current results as well as the challenges and opportunities CHS will encounter when implementing SDB within its operational chart production process. SDB is of particular interest to CHS due to its ability to supplement depths derived from traditional hydrographic surveys. This is of great importance in shallow and/or remote Canadian waters where achieving wide-area depth coverage through traditional surveys is costly, time-consuming and a safety risk to survey operators. With an accuracy of around 1 m, SDB could be used by CHS to fill gaps in survey data and to provide valuable information in dynamic areas.

Description: IJGI, Vol. 7, Pages 305: Prioritizing Abandoned Mine Lands Rehabilitation: Combining Landscape Connectivity and Pattern Indices with Scenario Analysis Using Land-Use Modeling ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080305 Authors: Liping Zhang Shiwen Zhang Yajie Huang An Xing Zhiqing Zhuo Zhongxiang Sun Zhen Li Meng Cao Yuanfang Huang Connectivity modeling approaches for abandoned mine lands (AML) patches are limited in post-mining landscape restoration, especially where great land use changes might be expected due to large-scale land reclamation. This study presents a novel approach combining AML patch sizes with a proximity index to characterize patch-scaled connectivity for determining the spatial positions of patches with huge sizes and high connectivity. Then this study propose a scenario-based method coupled with landscape-scale metrics for quantifying landscape-scaled connectivity, which aims at exploring the optimal reclamation scheme with the highest connectivity. Using the Mentougou District in Beijing, China, as a case study, this paper confirmed which patches should be reclaimed first to meet the predetermined reclamation numbers; then this paper tested three different reclamation scenarios (i.e., cultivated land-oriented, forest-oriented, and construction land-oriented scenarios) to describe the impact of the different development strategies on landscape connectivity. The research found that the forest-oriented scenario increased connectivity quantitatively, showing an increase in the integral index of connectivity (IIC) and other landscape-scale metrics. Therefore, this paper suggests that future land-use policies should emphasize converting AML into more forest to blend in with the surrounding land-use categories. The findings presented here can contribute to better understanding the quantitative analysis of the connectivity of AML patches at both the patch scale and the landscape scale, thus providing scientific support for AML management in mine-site rehabilitation.

Description: Minerals, Vol. 8, Pages 327: Assessment of the Mineral Resource Potential of Atlantic Ferromanganese Crusts Based on Their Growth History, Microstructure, and Texture Minerals doi: 10.3390/min8080327 Authors: Isobel A. Yeo Kate Dobson Pierre Josso Richard B. Pearce Sarah A. Howarth Paul A. J. Lusty Tim P. Le Bas Bramley J. Murton The decarbonisation of our energy supply is reliant on new technologies that are raw material intensive and will require a significant increase in the production of metals to sustain them. Ferromanganese (FeMn) crusts are seafloor precipitates, enriched in metals such as cobalt and tellurium, both of which have a predicted future demand above current production rates. In this study, we investigate the texture and composition of FeMn crusts on Tropic Seamount, a typical Atlantic guyot off the coast of western Africa, as a basis for assessing the future mineral resource potential of Atlantic Seamounts. The majority of the summit is flat and covered by FeMn crusts with average thicknesses of 3–4 cm. The crusts are characterized by two dominant textures consisting of either massive pillared growth or more chaotic, cuspate sections of FeMn oxides, with an increased proportion of detrital and organic material. The Fe, Mn, and Co contents in the FeMn oxide layers are not affected by texture. However, detrital material and bioclasts can form about 50% of cuspate areas, and the dilution effect of this entrained material considerably reduces the Fe, Mn, and Co concentrations if the bulk samples are analyzed. Whilst Tropic Seamount meets many of the prerequisites for a crust mining area, the thickness of the crusts and their average metal composition means extraction is unlikely to be viable in the near future. The ability to exploit more difficult terrains or multiple, closely spaced edifices would make economic feasibility more likely.

Description: Minerals, Vol. 8, Pages 328: Mesozoic High- and Low-SiO2 Adakites and A-Type Granites in the Lower Yangtze River Belt, Eastern China: Implications for Petrogenesis and Metallogeny Minerals doi: 10.3390/min8080328 Authors: Lei Liu Geng Chu Yanguang Li Xiaoyong Yang Madhava Warrier Santosh Qing Hu The Lower Yangtze River Belt (LYRB) is one of the important magmatic and metallogenic belts in China and hosts abundant Mesozoic calc-alkaline magmatic rocks and economic mineral deposits. Anqing orefield in the southwestern of the LYRB received less attention during the last two decades. Here, we present an integrated study of whole-rock major and trace elements, zircon U-Pb dating and Lu-Hf isotopes on late Mesozoic adakites and A-type granites from the Anqing orefield. The adakites emplaced during 138–136 Ma and can be further subdivided into two types: high-SiO2 adakites (HSA) with SiO2 >60 wt % from the Zongpu intrusion, and low-SiO2 adakites (LSA) <60 wt % from the Yueshan intrusion. The rocks display mid- to high-K calc-alkaline features and have consistent arc-like trace element characteristics with enrichment in LREE and LILE, and depletion in HREE and HFSE. The distinct zircon εHf(t) values for the LSA (from −27 to −20) and HSA (from −15 to −5) preclude a magma mixing model, yet suggest a subduction-related setting with partial melting of the subducted slab and overlying metasomatic mantle wedge. The A-type granites dated at 124 Ma from the Dalongshan intrusion characterized by LILE and LREE enrichment and slightly negative Eu anomalies, with lower MgO, CaO but higher K2O and Na2O contents. Their zircon εHf(t) values and geochemical features suggest that the parent magma was produced by the partial melting of Neoproterozoic crustal components, followed by variable degrees of fractional crystallization under a back-arc extensional setting, together with minor juvenile crust input. The adakites and A-type granites investigated in this study record a tectonic transition from compressive to extensional setting during 138–124 Ma. The transitional magmatic pulses are associated with distinct metallogenic signature with the adakites hosting copper deposits and the A-type granites linked to uranium mineralization.

Description: Remote Sensing, Vol. 10, Pages 1205: Examining the Accuracy of GlobCurrent Upper Ocean Velocity Data Products on the Northwestern Atlantic Shelf Remote Sensing doi: 10.3390/rs10081205 Authors: Hui Feng Douglas Vandemark Julia Levin John Wilkin This study provides a regional coastal ocean assessment of global upper ocean current data developed by the GlobCurrent (GC) project. These gridded data synthesize multiple satellite altimeter and wind model inputs to estimate both Geostrophic and Ekman-layer velocities. While the GC product was mostly devised and intended for open ocean studies, the present objective is to assess whether its data quality nearer the coast is suitable for other applications. The key ground truth sources are long-term mean and time series observations on the Northwestern Atlantic (NWA) shelf derived from Acoustic Doppler Current Profilers (ADCP) and high frequency (HF) radar networks in both the Mid-Atlantic Bight (MAB) and the Gulf of Maine (GoM). Results indicate that mean geostrophic currents across the MAB and the offshore GoM agree to roughly 10% in speed and 10 degree in direction with the in situ depth-averaged currents, with correlation levels of 0.5–0.8 at seasonal and longer time scales. Interior GoM comparisons at 5 coastal buoys show much less agreement. One likely source of GoM error is shown to be the GC mean dynamic topography near the coast. Comparison to near-surface MAB HF radar current measurements on the MAB shelf shows significant GC data improvement when including the surface Ekman term. Overall, the study results imply that application of GlobCurrent data may prove useful in coastal seas with broad continental shelves such as the MAB or Scotian shelf, but that large inaccuracies inside the GoM diminish its utility there.

Description: IJGI, Vol. 7, Pages 293: Shp2graph: Tools to Convert a Spatial Network into an Igraph Graph in R ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080293 Authors: Binbin Lu Huabo Sun Paul Harris Miaozhong Xu Martin Charlton In this study, we introduce the R package shp2graph, which provides tools to convert a spatial network into an ‘igraph’ graph of the igraphR package. This conversion greatly empowers a spatial network study, as the vast array of graph analytical tools provided in igraph are then readily available to the network analysis, together with the inherent advantages of being within the R statistical computing environment and its vast array of statistical functions. Through three urban road network case studies, the calculation of road network distances with shp2graph and with igraph is demonstrated through four key stages: (i) confirming the connectivity of a spatial network; (ii) integrating points/locations with a network; (iii) converting a network into a graph; and (iv) calculating network distances (and travel times). Throughout, the required R commands are given to provide a useful tutorial on the use of shp2graph.

Description: IJGI, Vol. 7, Pages 292: Optimized Location-Allocation of Earthquake Relief Centers Using PSO and ACO, Complemented by GIS, Clustering, and TOPSIS ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080292 Authors: Bahram Saeidian Mohammad Saadi Mesgari Biswajeet Pradhan Mostafa Ghodousi After an earthquake, it is required to establish temporary relief centers in order to help the victims. Selection of proper sites for these centers has a significant effect on the processes of urban disaster management. In this paper, the location and allocation of relief centers in district 1 of Tehran are carried out using Geospatial Information System (GIS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision model, a simple clustering method and the two meta-heuristic algorithms of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). First, using TOPSIS, the proposed clustering method and GIS analysis tools, sites satisfying initial conditions with adequate distribution in the area are chosen. Then, the selection of proper centers and the allocation of parcels to them are modelled as a location/allocation problem, which is solved using the meta-heuristic optimization algorithms. Also, in this research, PSO and ACO are compared using different criteria. The implementation results show the general adequacy of TOPSIS, the clustering method, and the optimization algorithms. This is an appropriate approach to solve such complex site selection and allocation problems. In view of the assessment results, the PSO finds better answers, converges faster, and shows higher consistency than the ACO.

Description: Atmosphere, Vol. 9, Pages 302: Surface and Tropospheric Water Vapor Variability and Decadal Trends at Two Supersites of CO-PDD (Cézeaux and Puy de Dôme) in Central France Atmosphere doi: 10.3390/atmos9080302 Authors: Dani Hadad Jean-Luc Baray Nadège Montoux Joël Van Baelen Patrick Fréville Jean-Marc Pichon Pierre Bosser Michel Ramonet Camille Yver Kwok Nelson Bègue Valentin Duflot We present an analysis of decadal in situ and remote sensing observations of water vapor over the Cézeaux and puy de Dôme, located in central France (45° N, 3° E), in order to document the variability, cycles and trends of surface and tropospheric water vapor at different time scales and the geophysical processes responsible for the water vapor distributions. We use meteorological stations, GPS (Global Positioning System), and lidar datasets, supplemented with three remote sources of water vapor (COSMIC-radio-occultation, ERA-interim-ECMWF numerical model, and AIRS-satellite). The annual cycle of water vapor is clearly established for the two sites of different altitudes and for all types of measurement. Cezeaux and puy de Dôme present almost no diurnal cycle, suggesting that the variability of surface water vapor at this site is more influenced by a sporadic meteorological system than by regular diurnal variations. The lidar dataset shows a greater monthly variability of the vertical distribution than the COSMIC and AIRS satellite products. The Cézeaux site presents a positive trend for the GPS water vapor total column (0.42 ± 0.45 g·kg−1/decade during 2006–2017) and a significant negative trend for the surface water vapor mixing ratio (−0.16 ± 0.09 mm/decade during 2002–2017). The multi-linear regression analysis shows that continental forcings (East Atlantic Pattern and East Atlantic-West Russia Pattern) have a greater influence than oceanic forcing (North Atlantic Oscillation) on the water vapor variations.

Description: IJGI, Vol. 7, Pages 308: Identifying Modes of Driving Railway Trains from GPS Trajectory Data: An Ensemble Classifier-Based Approach ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080308 Authors: Han Zheng Zanyang Cui Xingchen Zhang Recognizing Modes of Driving Railway Trains (MDRT) can help to solve railway freight transportation problems in driver behavior research, auto-driving system design and capacity utilization optimization. Previous studies have focused on analyses and applications of MDRT, but there is currently no approach to automatically and effectively identify MDRT in the context of big data. In this study, we propose an integrated approach including data preprocessing, feature extraction, classifiers modeling, training and parameter tuning, and model evaluation to infer MDRT using GPS data. The highlights of this study are as follows: First, we propose methods for extracting Driving Segmented Standard Deviation Features (DSSDF) combined with classical features for the purpose of improving identification performances. Second, we find the most suitable classifier for identifying MDRT based on a comparison of performances of K-Nearest Neighbor, Support Vector Machines, AdaBoost, Random Forest, Gradient Boosting Decision Tree, and XGBoost. From the real-data experiment, we conclude that: (i) The ensemble classifier XGBoost produces the best performance with an accuracy of 92.70%; (ii) The group of DSSDF plays an important role in identifying MDRT with an accuracy improvement of 11.2% (using XGBoost). The proposed approach has been applied in capacity utilization optimization and new driver training for the Baoshen Railway.

Description: Remote Sensing, Vol. 10, Pages 1215: Filtering Stems and Branches from Terrestrial Laser Scanning Point Clouds Using Deep 3-D Fully Convolutional Networks Remote Sensing doi: 10.3390/rs10081215 Authors: Zhouxin Xi Chris Hopkinson Laura Chasmer Terrestrial laser scanning (TLS) can produce precise and detailed point clouds of forest environment, thus enabling quantitative structure modeling (QSM) for accurate tree morphology and wood volume allocation. Applying QSM to plot-scale wood delineation is highly dependent on wood visibility from forest scans. A common problem is to filter wood point from noisy leafy points in the crowns and understory. This study proposed a deep 3-D fully convolution network (FCN) to filter both stem and branch points from complex plot scans. To train the 3-D FCN, reference stem and branch points were delineated semi-automatically for 14 sampled areas and three common species. Among seven testing areas, agreements between reference and model prediction, measured by intersection over union (IoU) and overall accuracy (OA), were 0.89 (stem IoU), 0.54 (branch IoU), 0.79 (mean IoU), and 0.94 (OA). Wood filtering results were further incorporated to a plot-scale QSM to extract individual tree forms, isolated wood, and understory wood from three plot scans with visual assessment. The wood filtering experiment provides evidence that deep learning is a powerful tool in 3-D point cloud processing and parsing.

Description: Remote Sensing, Vol. 10, Pages 1208: Seabed Mapping in Coastal Shallow Waters Using High Resolution Multispectral and Hyperspectral Imagery Remote Sensing doi: 10.3390/rs10081208 Authors: Javier Marcello Francisco Eugenio Javier Martín Ferran Marqués Coastal ecosystems experience multiple anthropogenic and climate change pressures. To monitor the variability of the benthic habitats in shallow waters, the implementation of effective strategies is required to support coastal planning. In this context, high-resolution remote sensing data can be of fundamental importance to generate precise seabed maps in coastal shallow water areas. In this work, satellite and airborne multispectral and hyperspectral imagery were used to map benthic habitats in a complex ecosystem. In it, submerged green aquatic vegetation meadows have low density, are located at depths up to 20 m, and the sea surface is regularly affected by persistent local winds. A robust mapping methodology has been identified after a comprehensive analysis of different corrections, feature extraction, and classification approaches. In particular, atmospheric, sunglint, and water column corrections were tested. In addition, to increase the mapping accuracy, we assessed the use of derived information from rotation transforms, texture parameters, and abundance maps produced by linear unmixing algorithms. Finally, maximum likelihood (ML), spectral angle mapper (SAM), and support vector machine (SVM) classification algorithms were considered at the pixel and object levels. In summary, a complete processing methodology was implemented, and results demonstrate the better performance of SVM but the higher robustness of ML to the nature of information and the number of bands considered. Hyperspectral data increases the overall accuracy with respect to the multispectral bands (4.7% for ML and 9.5% for SVM) but the inclusion of additional features, in general, did not significantly improve the seabed map quality.