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: Sensors, Vol. 18, Pages 2406: Adaptive Robust Unscented Kalman Filter via Fading Factor and Maximum Correntropy Criterion Sensors doi: 10.3390/s18082406 Authors: Zhihong Deng Lijian Yin Baoyu Huo Yuanqing Xia In most practical applications, the tracking process needs to update the data constantly. However, outliers may occur frequently in the process of sensors’ data collection and sending, which affects the performance of the system state estimate. In order to suppress the impact of observation outliers in the process of target tracking, a novel filtering algorithm, namely a robust adaptive unscented Kalman filter, is proposed. The cost function of the proposed filtering algorithm is derived based on fading factor and maximum correntropy criterion. In this paper, the derivations of cost function and fading factor are given in detail, which enables the proposed algorithm to be robust. Finally, the simulation results show that the presented algorithm has good performance, and it improves the robustness of a general unscented Kalman filter and solves the problem of outliers in system.

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: Forests, Vol. 9, Pages 448: Shifts in Growing Season of Tropical Deciduous Forests as Driven by El Niño and La Niña during 2001–2016 Forests doi: 10.3390/f9080448 Authors: Phan Kieu Diem Uday Pimple Asamaporn Sitthi Pariwate Varnakovida Katsunori Tanaka Sukan Pungkul Kumron Leadprathom Monique Y. LeClerc Amnat Chidthaisong This study investigated the spatiotemporal dynamics of tropical deciduous forest including dry dipterocarp forest (DDF) and mixed deciduous forest (MDF) and its phenological changes in responses to El Niño and La Niña during 2001–2016. Based on time series of Normalized Difference Vegetation Index (NDVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS), the start of growing season (SOS), the end of growing season (EOS), and length of growing season (LOS) were derived. In absence of climatic fluctuation, the SOS of DDF commonly started on 106 ± 7 DOY, delayed to 132 DOY in El Niño year (2010) and advanced to 87 DOY in La Niña year (2011). Thus, there was a delay of about 19 to 33 days in El Niño and an earlier onset of about 13 to 27 days in La Niña year. The SOS of MDF started almost same time as of DDF on the 107 ± 7 DOY during the neutral years and delayed to 127 DOY during El Niño, advanced to 92 DOY in La Niña year. The SOS of MDF was delayed by about 12 to 28 days in El Niño and was earlier about 8 to 22 days in La Niña. Corresponding to these shifts in SOS and LOS of both DDF and MDF were also induced by the El Niño–Southern Oscillation (ENSO).

Description: Forests, Vol. 9, Pages 446: Plant Hydraulic Trait Covariation: A Global Meta-Analysis to Reduce Degrees of Freedom in Trait-Based Hydrologic Models Forests doi: 10.3390/f9080446 Authors: A. Rio Mursinna Erica McCormick Katie Van Horn Lisa Sartin Ashley M. Matheny Current vegetation modeling strategies use broad categorizations of plants to estimate transpiration and biomass functions. A significant source of model error stems from vegetation categorizations that are mostly taxonomical with no basis in plant hydraulic strategy and response to changing environmental conditions. Here, we compile hydraulic traits from 355 species around the world to determine trait covariations in order to represent hydraulic strategies. Simple and stepwise regression analyses demonstrate the interconnectedness of multiple vegetative hydraulic traits, specifically, traits defining hydraulic conductivity and vulnerability to embolism with wood density and isohydricity. Drought sensitivity is strongly (Adjusted R2 = 0.52, p < 0.02) predicted by a stepwise linear model combining rooting depth, wood density, and isohydricity. Drought tolerance increased with increasing wood density and anisohydric response, but with decreasing rooting depth. The unexpected response to rooting depth may be due to other tradeoffs within the hydraulic system. Rooting depth was able to be predicted from sapwood specific conductivity and the water potential at 50% loss of conductivity. Interestingly, the influences of biome or growth form do not increase the accuracy of the drought tolerance model and were able to be omitted. Multiple regression analysis revealed 3D trait spaces and tradeoff axes along which species’ hydraulic strategies can be analyzed. These numerical trait spaces can reduce the necessary input to and parameterization of plant hydraulics modules, while increasing the physical representativeness of such simulations.

Description: Sensors, Vol. 18, Pages 2420: Strain Transfer Characteristics of Resistance Strain-Type Transducer Using Elastic-Mechanical Shear Lag Theory Sensors doi: 10.3390/s18082420 Authors: Yongqian Li Zhigang Wang Chi Xiao Yinming Zhao Yaxin Zhu Zili Zhou The strain transfer characteristics of resistance strain gauge are theoretically investigated. A resistance strain-type transducer is modeled to be a four-layer and two-glue (FLTG) structure model, which comprises successively the surface of an elastomer sensitive element, a ground adhesive glue, a film substrate layer, an upper adhesive glue, a sensitive grids layer, and a polymer cover. The FLTG model is studied in elastic–mechanical shear lag theory, and the strain transfer progress in a resistance strain-type transducer is described. The strain transitional zone (STZ) is defined and the strain transfer ratio (STR) of the FLTG structure is formulated. The dependences of the STR and STZ on both the dimensional sizes of the adhesive glue and structural parameters are calculated. The results indicate that the width, thickness and shear modulus of the ground adhesive glue have a greater influence on the STZ ratio. To ensure that the resistance strain gauge has excellent strain transfer performance and low hysteresis, it is recommended that the paste thickness should be strictly controlled, and the STZ ratio should be less than 10%. Moreover, the STR strongly depends on the length and width of the sensitive grids.

Description: Sensors, Vol. 18, Pages 2416: Design and Optimization of a Novel Three-Dimensional Force Sensor with Parallel Structure Sensors doi: 10.3390/s18082416 Authors: Guanyu Huang Dan Zhang Sheng Guo Haibo Qu To measure large external forces exerted on a loading platform, a novel three-dimensional force sensor is developed in this paper. The proposed sensor was designed with a parallel mechanism with three degrees of freedom. Kinematic analysis of this sensor was performed. Due to its structural characteristics, the working principle of the sensor was analyzed using a Jacobian matrix. The sensitivity diversity index and measuring capability were both calculated. The analysis showed that the proposed sensor is more suitable for measuring large forces than existing strain sensors. In addition, compared with existing strain sensors, this sensor is more suitable for measuring forces along the x and y axes. By changing the stiffness coefficients of the springs, the proposed sensor has reconfigurability. This sensor can change its measuring capability to meet different requirements. Next, the mode shapes and natural frequencies of the proposed sensor were performed. Finally, based on these performance indices, the design variables were optimized using a Multi-Objective Genetic Algorithm.

Description: Sensors, Vol. 18, Pages 2415: Cheeses Made from Raw and Pasteurized Cow’s Milk Analysed by an Electronic Nose and an Electronic Tongue Sensors doi: 10.3390/s18082415 Authors: Nuno I. P. Valente Alisa Rudnitskaya João A. B. P. Oliveira M. Teresa S. R. Gomes Elvira M. M. Gaspar Cheese prepared from whole milk, raw and pasteurized, were analysed by an electronic nose based on piezoelectric quartz crystals and an electronic tongue based on potentiometric sensors, immediately after their preparation and along ripening (after 7 and 21 days). Whey was also analysed by the potentiometric electronic tongue. Results obtained by the electronic nose and tongue were found to be complementary, with the electronic nose being more sensitive to differences in the milk and the electronic tongue being more sensitive to milk pasteurization. Electronic tongue was able to distinguish cheeses made from raw and pasteurized milk, both analysing the whey or the curd, with correct classification rate of 96% and 84%, respectively. Besides, the electronic nose was more sensitive than the electronic tongue to the ripening process, with large differences between samples after 7 and 21 days, while the electronic tongue was only sensitive to the initial maturation stages, with large difference between freshly prepared cheese and with seven days of maturation.

Description: Sensors, Vol. 18, Pages 2412: Validation of the Accuracy and Convergence Time of Real Time Kinematic Results Using a Single Galileo Navigation System Sensors doi: 10.3390/s18082412 Authors: Zbigniew Siejka For the last two decades, the American GPS and Russian GLONASS were the basic systems used in global positioning and navigation. In recent years, there has been significant progress in the development of positioning systems. New regional systems have been created, i.e., the Japanese Quasi-Zenith Satellite System (QZSS) and Indian Regional Navigational Satellite System (IRNSS). A plan to build its own regional navigation system named Korean Positioning System (KPS) was announced South Korea on 5 February 2018. Currently, two new global navigation systems are under development: the European Galileo and the Chinese BeiDou. The full operability of both systems by 2020 is planned. The paper deals with a possibility of determination of the user’s position from individual and independent global navigation satellite system (GNSS). The article is a broader concept aimed at independent determination of precise position from individual GPS, GLONASS, BeiDou and Galileo systems. It presents real time positioning results (Real Time Kinematic-RTK) using signals from Galileo satellites only. During the test, 14 Galileo satellites were used and the number of simultaneously observed Galileo satellites varied from five to seven. Real-time measurements were only possible in certain 24-h observation windows. However, their number was completed within 6 days at the end of 2017 and beginning of 2018, so there was possible to infer about the current availability, continuity, convergence time and accuracy of the RTK measurements. In addition, the systematic errors were demonstrated for the Galileo system.

Description: Sensors, Vol. 18, Pages 2409: The Bluetooth Mesh Standard: An Overview and Experimental Evaluation Sensors doi: 10.3390/s18082409 Authors: Mathias Baert Jen Rossey Adnan Shahid Jeroen Hoebeke Mesh networks enable a many-to-many relation between nodes, which means that each node in the network can communicate with every other node using multi-hop communication and path diversity. As it enables the fast roll-out of sensor and actuator networks, it is an important aspect within the Internet of Things (IoT). Utilizing Bluetooth Low Energy (BLE) as an underlying technology to implement such mesh networks has gained a lot of interest in recent years. The result was a variety of BLE meshing solutions that were not interoperable because of the lack of a common standard. This has changed recently with the advent of the Bluetooth Mesh standard. However, a detailed overview of how this standard operates, performs and how it tackles other issues concerning BLE mesh networking is missing. Therefore, this paper investigates this new technology thoroughly and evaluates its performance by means of three approaches, namely an experimental evaluation, a statistical approach and a graph-based simulation model, which can be used as the basis for future research. Apart from showing that consistent results are achieved by means of all three approaches, we also identify possible drawbacks and open issues that need to be dealt with.

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: Sensors, Vol. 18, Pages 2436: Bio-Inspired Covert Active Sonar Strategy Sensors doi: 10.3390/s18082436 Authors: Jiajia Jiang Xianquan Wang Fajie Duan Chunyue Li Xiao Fu Tingting Huang Lingran Bu Ling Ma Zhongbo Sun The covertness of the active sonar is a very important issue and the sonar signal waveform design problem was studied to improve covertness of the system. Many marine mammals produce call pulses for communication and echolocation, and existing interception systems normally classify these biological signals as ocean noise and filter them out. Based on this, a bio-inspired covert active sonar strategy was proposed. The true, rather than man-made sperm whale, call pulses were used to serve as sonar waveforms so as to ensure the camouflage ability of sonar waveforms. A range and velocity measurement combination (RVMC) was designed by using two true sperm whale call pulses which had excellent range resolution (RR) and large Doppler tolerance (DT). The range and velocity estimation methods were developed based on the RVMC. In the sonar receiver, the correlation technology was used to confirm the start and end time of sonar signals and their echoes, and then based on the developed range and velocity estimation method, the range and velocity of the underwater target were obtained. Then, the RVMC was embedded into the true sperm whale call-train to improve the camouflage ability of the sonar signal-train. Finally, experiment results were provided to verify the performance of the proposed method.

Description: Sensors, Vol. 18, Pages 2435: Quantitative Contact-Less Estimation of Energy Expenditure from Video and 3D Imagery Sensors doi: 10.3390/s18082435 Authors: Gregor Koporec Goran Vučković Radoje Milić Janez Perš Measurement of energy expenditure is an important tool in sport science and medicine, especially when trying to estimate the extent and intensity of physical activity. However, most approaches still rely on sensors or markers, placed directly on the body. In this paper, we present a novel approach using a fully contact-less, fully automatic method, that relies on computer vision algorithms and widely available and inexpensive imaging sensors. We rely on the estimation of the optical and scene flow to calculate Histograms of Oriented Optical Flow (HOOF) descriptors, which we subsequently augment with the Histograms of Absolute Flow Amplitude (HAFA). Descriptors are fed into regression model, which allows us to estimate energy consumption, and to a lesser extent, the heart rate. Our method has been tested both in lab environment and in realistic conditions of a sport match. Results confirm that these energy expenditures could be derived from purely contact-less observations. The proposed method can be used with different modalities, including near infrared imagery, which extends its future potential.

Description: Sensors, Vol. 18, Pages 2434: Smart Portable Devices Suitable for Cultural Heritage: A Review Sensors doi: 10.3390/s18082434 Authors: Federica Valentini Andrea Calcaterra Simonetta Antonaroli Maurizio Talamo This article reviews recent portable sensor technologies to apply in the Cultural Heritage (CH) fields. The review has been prepared in the form of a retrospective description of the sensor’s history and technological evolution, having: new nanomaterials for transducers, miniaturized, portable and integrated sensors, the wireless transmission of the analytical signals, ICT_Information Communication Technology and IoT_Internet of Things to apply to the cultural heritage field. In addition, a new trend of movable tattoo sensors devices is discussed, referred to in situ analysis, which is especially important when scientists are in the presence of un-movable and un-tangible Cultural Heritage and Art Work objects. The new proposed portable contact sensors (directly applied to art work objects and surfaces) are non-invasive and non-destructive to the different materials and surfaces of which cultural heritage is composed.

Description: Sensors, Vol. 18, Pages 2433: Multi-Camera Imaging System for UAV Photogrammetry Sensors doi: 10.3390/s18082433 Authors: Damian Wierzbicki In the last few years, it has been possible to observe a considerable increase in the use of unmanned aerial vehicles (UAV) equipped with compact digital cameras for environment mapping. The next stage in the development of photogrammetry from low altitudes was the development of the imagery data from UAV oblique images. Imagery data was obtained from side-facing directions. As in professional photogrammetric systems, it is possible to record footprints of tree crowns and other forms of the natural environment. The use of a multi-camera system will significantly reduce one of the main UAV photogrammetry limitations (especially in the case of multirotor UAV) which is a reduction of the ground coverage area, while increasing the number of images, increasing the number of flight lines, and reducing the surface imaged during one flight. The approach proposed in this paper is based on using several head cameras to enhance the imaging geometry during one flight of UAV for mapping. As part of the research work, a multi-camera system consisting of several cameras was designed to increase the total Field of View (FOV). Thanks to this, it will be possible to increase the ground coverage area and to acquire image data effectively. The acquired images will be mosaicked in order to limit the total number of images for the mapped area. As part of the research, a set of cameras was calibrated to determine the interior orientation parameters (IOPs). Next, the method of image alignment using the feature image matching algorithms was presented. In the proposed approach, the images are combined in such a way that the final image has a joint centre of projections of component images. The experimental results showed that the proposed solution was reliable and accurate for the mapping purpose. The paper also presents the effectiveness of existing transformation models for images with a large coverage subjected to initial geometric correction due to the influence of distortion.

Description: Sensors, Vol. 18, Pages 2432: A Terahertz CMOS V-Shaped Patch Antenna with Defected Ground Structure Sensors doi: 10.3390/s18082432 Authors: Hyeongjin Kim Wonseok Choe Jinho Jeong In this paper, a V-shaped patch antenna with defected ground structure is proposed at terahertz to overcome the limited performance of a standard complementary metal-oxide semiconductor (CMOS) patch antenna consisting of several metal layers and very thin interdielectric layers. The proposed V-shaped patch with slots allows the increased radiation resistance and broadband performance. In addition, the patch resonating at different frequency from the V-shaped patch is stacked on the top to broaden the impedance-matching bandwidth. More importantly, the slots are formed in the ground plane, which is called the defected ground structure, to further increase the radiation resistance and thus improve the bandwidth and efficiency. It is verified from electromagnetic simulations that the leakage waves from the defected ground can enhance the antenna directivity and gain by coherently interfering with the topside radiation. The proposed on-chip antenna is fabricated using a standard 65 nm CMOS process. The on-wafer measurement shows very wide bandwidth in input reflection coefficient (<−10 dB), greater than 28.7% from 240 to >320 GHz. The measured peak gain was as high as 5.48 dBi at 295 GHz. To the best of the authors’ knowledge, these results belong to the best performance among the terahertz CMOS on-chip antennas without using additional components or processes such as dielectric resonators, lens, or substrate thinning.

Description: Sensors, Vol. 18, Pages 2430: Relative Pose Based Redundancy Removal: Collaborative RGB-D Data Transmission in Mobile Visual Sensor Networks Sensors doi: 10.3390/s18082430 Authors: Xiaoqin Wang Y. Ahmet Şekercioğlu Tom Drummond Vincent Frémont Enrico Natalizio Isabelle Fantoni In this paper, the Relative Pose based Redundancy Removal (RPRR) scheme is presented, which has been designed for mobile RGB-D sensor networks operating under bandwidth-constrained operational scenarios. The scheme considers a multiview scenario in which pairs of sensors observe the same scene from different viewpoints, and detect the redundant visual and depth information to prevent their transmission leading to a significant improvement in wireless channel usage efficiency and power savings. We envisage applications in which the environment is static, and rapid 3D mapping of an enclosed area of interest is required, such as disaster recovery and support operations after earthquakes or industrial accidents. Experimental results show that wireless channel utilization is improved by 250% and battery consumption is halved when the RPRR scheme is used instead of sending the sensor images independently.

Description: Sensors, Vol. 18, Pages 2439: HemoKinect: A Microsoft Kinect V2 Based Exergaming Software to Supervise Physical Exercise of Patients with Hemophilia Sensors doi: 10.3390/s18082439 Authors: Fernando Mateo Emilio Soria-Olivas Juan Carrasco Santiago Bonanad Felipe Querol Sofía Pérez-Alenda Patients with hemophilia need to strictly follow exercise routines to minimize their risk of suffering bleeding in joints, known as hemarthrosis. This paper introduces and validates a new exergaming software tool called HemoKinect that intends to keep track of exercises using Microsoft Kinect V2’s body tracking capabilities. The software has been developed in C++ and MATLAB. The Kinect SDK V2.0 libraries have been used to obtain 3D joint positions from the Kinect color and depth sensors. Performing angle calculations and center-of-mass (COM) estimations using these joint positions, HemoKinect can evaluate the following exercises: elbow flexion/extension, knee flexion/extension (squat), step climb (ankle exercise) and multi-directional balance based on COM. The software generates reports and progress graphs and is able to directly send the results to the physician via email. Exercises have been validated with 10 controls and eight patients. HemoKinect successfully registered elbow and knee exercises, while displaying real-time joint angle measurements. Additionally, steps were successfully counted in up to 78% of the cases. Regarding balance, differences were found in the scores according to the difficulty level and direction. HemoKinect supposes a significant leap forward in terms of exergaming applicability to rehabilitation of patients with hemophilia, allowing remote supervision.

Description: Sensors, Vol. 18, Pages 2428: Narrowband Characterization of Near-Ground Radio Channel for Wireless Sensors Networks at 5G-IoT Bands Sensors doi: 10.3390/s18082428 Authors: Hicham Klaina Ana Vazquez Alejos Otman Aghzout Francisco Falcone In this contribution, a narrowband radio channel model is proposed for rural scenarios in which the radio link operates under near-ground conditions for application in wireless sensor networks dedicated to smart agriculture. The received power attenuation was measured for both transmitter and receiver antennas placed at two different heights above ground: 0.2 and 0.4 m. Three frequency ranges, proposed for future 5G-IoT use case in agriculture, were chosen: 868 MHz, 2.4 GHz and 5.8 GHz. Three ground coverings were tested in a rural scenario: soil, short and tall grass fields. The path loss was then estimated as dependent of the radio link range and a three-slope log-normal path loss model was tailored. Results are explained in terms of the first Fresnel zone obstruction. Commercial Zigbee sensor nodes operating at 2.4 GHz were used in a second experiment to estimate the link quality from the experimental Radio Signal Strength Indicator (RSSI) received values. Two sensor nodes were placed at the same elevation above ground as in the previous experiment, only for short grass field case. The Quality of Service performance was determined in terms of theoretical bit error rate achieved for different digital modulations—BPSK, 8PSK and 16QAM—concluding remarkable results for an obstructed radio link.

Description: Sensors, Vol. 18, Pages 2429: A PUF- and Biometric-Based Lightweight Hardware Solution to Increase Security at Sensor Nodes Sensors doi: 10.3390/s18082429 Authors: Rosario Arjona Miguel Ángel Prada-Delgado Javier Arcenegui Iluminada Baturone Security is essential in sensor nodes which acquire and transmit sensitive data. However, the constraints of processing, memory and power consumption are very high in these nodes. Cryptographic algorithms based on symmetric key are very suitable for them. The drawback is that secure storage of secret keys is required. In this work, a low-cost solution is presented to obfuscate secret keys with Physically Unclonable Functions (PUFs), which exploit the hardware identity of the node. In addition, a lightweight fingerprint recognition solution is proposed, which can be implemented in low-cost sensor nodes. Since biometric data of individuals are sensitive, they are also obfuscated with PUFs. Both solutions allow authenticating the origin of the sensed data with a proposed dual-factor authentication protocol. One factor is the unique physical identity of the trusted sensor node that measures them. The other factor is the physical presence of the legitimate individual in charge of authorizing their transmission. Experimental results are included to prove how the proposed PUF-based solution can be implemented with the SRAMs of commercial Bluetooth Low Energy (BLE) chips which belong to the communication module of the sensor node. Implementation results show how the proposed fingerprint recognition based on the novel texture-based feature named QFingerMap16 (QFM) can be implemented fully inside a low-cost sensor node. Robustness, security and privacy issues at the proposed sensor nodes are discussed and analyzed with experimental results from PUFs and fingerprints taken from public and standard databases.

Description: Algorithms, Vol. 11, Pages 112: A Novel Parallel Auto-Encoder Framework for Multi-Scale Data in Civil Structural Health Monitoring Algorithms doi: 10.3390/a11080112 Authors: Ruhua Wang Ling Li Jun Li In this paper, damage detection/identification for a seven-storey steel structure is investigated via using the vibration signals and deep learning techniques. Vibration characteristics, such as natural frequencies and mode shapes are captured and utilized as input for a deep learning network while the output vector represents the structural damage associated with locations. The deep auto-encoder with sparsity constraint is used for effective feature extraction for different types of signals and another deep auto-encoder is used to learn the relationship of different signals for final regression. The existing SAF model in a recent research study for the same problem processed all signals in one serial auto-encoder model. That kind of models have the following difficulties: (1) the natural frequencies and mode shapes are in different magnitude scales and it is not logical to normalize them in the same scale in building the models with training samples; (2) some frequencies and mode shapes may not be related to each other and it is not fair to use them for dimension reduction together. To tackle the above-mentioned problems for the multi-scale dataset in SHM, a novel parallel auto-encoder framework (Para-AF) is proposed in this paper. It processes the frequency signals and mode shapes separately for feature selection via dimension reduction and then combine these features together in relationship learning for regression. Furthermore, we introduce sparsity constraint in model reduction stage for performance improvement. Two experiments are conducted on performance evaluation and our results show the significant advantages of the proposed model in comparison with the existing approaches.

Description: Algorithms, Vol. 11, Pages 113: Improved Parameter Identification Method for Envelope Current Signals Based on Windowed Interpolation FFT and DE Algorithm Algorithms doi: 10.3390/a11080113 Authors: Xiangfeng Su Huaiqing Zhang Lin Chen Ling Qin Lili Yu Envelope current signals are increasingly emerging in power systems, and their parameter identification is particularly necessary for accurate measurement of electrical energy. In order to analyze the envelope current signal, the harmonic parameters, as well as the envelope parameters, need to be calculated. The interpolation fast Fourier transform (FFT) is a widely used approach which can estimate the signal frequency with high precision, but it cannot calculate the envelope parameters of the signal. Therefore, this paper proposes an improved method based on windowed interpolation FFT (WIFFT) and differential evolution (DE). The amplitude and phase parameters obtained through WIFFT and the envelope parameters estimated by the envelope analysis are optimized using the DE algorithm, which makes full use of the performance advantage of DE. The simulation results show that the proposed method can improve the accuracy of the harmonic parameters and the envelope parameter significantly. In addition, it has good anti-noise ability and high precision.

Description: Forests, Vol. 9, Pages 459: Pedunculate and Sessile Mixed Oak Forest Regeneration Process in Lithuania Forests doi: 10.3390/f9080459 Authors: Girmantė Jurkšienė Virginijus Baliuckas Pedunculate and sessile oak species are sympatric. These oaks hybridize with one another, and this process influences the development of undergrowth. The purpose of this study was to determine how different oak species influence the forest regeneration process. For this purpose, the forest was divided into eight transects of 300 m and 100 m widths, distinguished into temporary plots of 10 m in diameter covering the whole territory of the forest. The distribution of oak undergrowth was calculated by four oak height groups, determining the composition of the first storey, covering of underbrush and herbaceous plant, and forest site. We determined that the spread of oak differed depending on the first storey tree species and underbrush. Grass cover was the biggest influence on the sessile oak. The impurity of sessile oak in oak stands had a positive impact on the development of undergrowth, since the entire undergrowth develops faster than separate components of the undergrowth.

Description: Forests, Vol. 9, Pages 455: Measuring Eco-Efficiency of State-Owned Forestry Enterprises in Northeast China Forests doi: 10.3390/f9080455 Authors: Youliang Ning Zhen Liu Zekui Ning Han Zhang State-owned forestry enterprises (SOFEs) play an important role in the forestry economy in China. Understanding the eco-efficiency of their production is beneficial for the development of sustainable forestry and for achieving Goal 8 of the United Nations’ Sustainable Development Goals (SDGs): Decent Work and Economic Growth. This paper assesses SOFEs’ overall eco-efficiency by analyzing various undesirable outputs using the Slacks-Based Measure of efficiency in Data Envelopment Analysis (SBM-DEA) model. Using basic data from 87 SOFEs in Northeast China from 2003 to 2016, this paper evaluated the eco-efficiency development level and spatial patterns of that region. The results show that SOFEs’ low eco-efficiency was caused by low pure-technical efficiency. Regional differences in eco-efficiency were very significant and became larger, but a market-oriented reform might help to improve such efficiency. The eco-efficiency of SOFEs was in decline from 2003 to 2016 due to the implementation of the Natural Forest Protection Project (NFPP). However, due to a relative lack of production factor inputs, most SOFEs’ scale returns are now increasing. In the future, efforts should be made to promote market-oriented reforms and take the path of large-scale development.

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: Sensors, Vol. 18, Pages 2448: Application-Aware Anomaly Detection of Sensor Measurements in Cyber-Physical Systems Sensors doi: 10.3390/s18082448 Authors: Amin Ghafouri Aron Laszka Koutsoukos Detection errors such as false alarms and undetected faults are inevitable in any practical anomaly detection system. These errors can create potentially significant problems in the underlying application. In particular, false alarms can result in performing unnecessary recovery actions while missed detections can result in failing to perform recovery which can lead to severe consequences. In this paper, we present an approach for application-aware anomaly detection (AAAD). Our approach takes an existing anomaly detector and configures it to minimize the impact of detection errors. The configuration of the detectors is chosen so that application performance in the presence of detection errors is as close as possible to the performance that could have been obtained if there were no detection errors. We evaluate our result using a case study of real-time control of traffic signals, and show that the approach outperforms significantly several baseline detectors.

Description: Sensors, Vol. 18, Pages 2444: Utilization of Inexpensive Carbon-Based Substrates as Platforms for Sensing Sensors doi: 10.3390/s18082444 Authors: Minh Tran Ahmad Fallatah Alison Whale Sonal Padalkar Gold (Au) has been widely used as a material for Surface Enhanced Raman Spectroscopy (SERS) due to its plasmonic properties, stability and biocompatibility. Conventionally for SERS application, Au is deposited on a rigid substrate such as glass or silicon. The rigid substrates severely limit analyte collection efficiency as well as portability. Here, flexible substrates like carbon cloth and carbon paper were investigated as potential substrate candidates for SERS application. The flexible substrates were coated with Au nanostructures by electrodeposition. Model analyte, Rhodamine 6G was utilized to demonstrate the capabilities of the flexible SERS substrates. Additionally, the pesticide paraoxon was also detected on the flexible SERS substrates as well as on a real sample like the apple fruit.

Description: Sensors, Vol. 18, Pages 2441: A Label-Free Fluorescent Assay for the Rapid and Sensitive Detection of Adenosine Deaminase Activity and Inhibition Sensors doi: 10.3390/s18082441 Authors: Xinxing Tang Kefeng Wu Han Zhao Mingjian Chen Changbei Ma Adenosine deaminase (ADA), able to catalyze the irreversible deamination of adenosine into inosine, can be found in almost all tissues and plays an important role in several diseases. In this work, we developed a label-free fluorescence method for the detection of adenosine deaminase activity and inhibition. In the presence of ADA, ATP has been shown to be hydrolyzed. The ATP aptamer was shown to form a G-quadruplex/thioflavin T (ThT) complex with ThT and exhibited an obvious fluorescence signal. However, the ATP aptamer could bind with ATP and exhibited a low fluorescence signal because of the absence of ADA. This assay showed high sensitivity to ADA with a detection limit of 1 U/L based on an SNR of 3 and got a good linear relationship within the range of 1–100 U/L with R2 = 0.9909. The LOD is lower than ADA cutoff value (4 U/L) in the clinical requirement and more sensitive than most of the reported methods. This technique exhibited high selectivity for ADA against hoGG I, UDG, RNase H and λexo. Moreover, this strategy was successfully applied for assaying the inhibition of ADA using erythro-9-(2-hydroxy-3-nonyl) adenine (EHNA) and, as such, demonstrated great potential for the future use in the diagnosis of ADA-relevant diseases, particularly in advanced drug development.

Description: Sensors, Vol. 18, Pages 2440: A Privacy Preserving Scheme for Nearest Neighbor Query Sensors doi: 10.3390/s18082440 Authors: Yuhang Wang Zhihong Tian Hongli Zhang Shen Su Wei Shi In recent years, location privacy concerns that arise when using the nearest neighbor query services have gained increasing attention, as such services have become pervasive in mobile social networks devices and the IoT environments. State-of-the-art privacy preservation schemes focus on the obfuscation of the location information, which has suffered from various privacy attacks and the tradeoff of the quality of service. By noticing the fact that the user’s location could be replaced by their surrounding wireless sensor infrastructures in proximity, in this paper, we propose a wireless sensor access point-based scheme for the nearest neighbor query, without using the location of the user. Then, a noise-addition-based method that preserves user’s location privacy was proposed. To further strengthen the adaptability of the approach to real-world environments, several performance-enhancing methods are introduced, including an R-tree-based Noise-Data Retrieval Algorithm (RNR), and a nearest neighbor query method based on our research. Both performance and security evaluations are conducted to validate our approach. The results show the effectiveness and the practicality of our work.

Description: Algorithms, Vol. 11, Pages 114: Revisiting Chameleon Sequences in the Protein Data Bank Algorithms doi: 10.3390/a11080114 Authors: Mihaly Mezei The steady growth of the Protein Data Bank (PDB) suggests the periodic repetition of searches for sequences that form different secondary structures in different protein structures; these are called chameleon sequences. This paper presents a fast (nlog(n)) algorithm for such searches and presents the results on all protein structures in the PDB. The longest such sequence found consists of 20 residues.

Description: Algorithms, Vol. 11, Pages 115: Color-Based Image Retrieval Using Proximity Space Theory Algorithms doi: 10.3390/a11080115 Authors: Jing Wang Lidong Wang Xiaodong Liu Yan Ren Ye Yuan The goal of object retrieval is to rank a set of images by their similarity compared with a query image. Nowadays, content-based image retrieval is a hot research topic, and color features play an important role in this procedure. However, it is important to establish a measure of image similarity in advance. The innovation point of this paper lies in the following. Firstly, the idea of the proximity space theory is utilized to retrieve the relevant images between the query image and images of database, and we use the color histogram of an image to obtain the Top-ranked colors, which can be regard as the object set. Secondly, the similarity is calculated based on an improved dominance granule structure similarity method. Thus, we propose a color-based image retrieval method by using proximity space theory. To detect the feasibility of this method, we conducted an experiment on COIL-20 image database and Corel-1000 database. Experimental results demonstrate the effectiveness of the proposed framework and its applications.

Description: Sensors, Vol. 18, Pages 2450: Features of X-Band Radar Backscattering Simulation Based on the Ocean Environmental Parameters in China Offshore Seas Sensors doi: 10.3390/s18082450 Authors: Tao Wu Zhensen Wu Jiaji Wu Gwanggil Jeon Liwen Ma The X-band marine radar has been employed as a remote sensing tool for sea state monitoring. However, there are few literatures about sea spectra considering both the wave parameters and short wind-wave spectra in China Offshore Seas, which are of theoretical and practical significance. Based on the wave parameters acquired from the European Centre for Medium-Range Weather Forecasts reanalysis data (ERA-Interim reanalysis data) during 36 months from 2015 to 2017, a finite depth sea spectrum considering both wind speeds and ocean environmental parameters is established in this study. The wave spectrum is then built into a modified two-scale model, which can be related to the ocean environmental parameters (wind speeds and wave parameters). The final results are the mean backscattering coefficients over the variety of sea states at a given wind speed. As the model predicts, the monthly maximum backscattering coefficients in different seas change slowly (within 4 dB). In addition, the differences of the backscattering coefficients in different seas are quite small during azimuthal angles of 0° to 90° and 270° to 360° with a relative error within 1.5 dB at low wind speed (5 m/s) and 2 dB at high wind speed (10 m/s). With the method in the paper, a corrected result from the experiment can be achieved based on the relative error analysis in different conditions.

Description: Sensors, Vol. 18, Pages 2451: Interaction of Lamb Wave Modes with Weak Material Nonlinearity: Generation of Symmetric Zero-Frequency Mode Sensors doi: 10.3390/s18082451 Authors: Xiaoqiang Sun Xiangyan Ding Feilong Li Shijie Zhou Yaolu Liu Ning Hu Zhongqing Su Youxuan Zhao Jun Zhang Mingxi Deng The symmetric zero-frequency mode induced by weak material nonlinearity during Lamb wave propagation is explored for the first time. We theoretically confirm that, unlike the second harmonic, phase-velocity matching is not required to generate the zero-frequency mode and its signal is stronger than those of the nonlinear harmonics conventionally used, for example, the second harmonic. Experimental and numerical verifications of this theoretical analysis are conducted for the primary S0 mode wave propagating in an aluminum plate. The existence of a symmetric zero-frequency mode is of great significance, probably triggering a revolutionary progress in the field of non-destructive evaluation and structural health monitoring of the early-stage material nonlinearity based on the ultrasonic Lamb waves.

Description: Forests, Vol. 9, Pages 464: Payment for Targeted Grazing: Integrating Local Shepherds into Wildfire Prevention Forests doi: 10.3390/f9080464 Authors: Elsa Varela Elena Górriz-Mifsud Jabier Ruiz-Mirazo Feliu López-i-Gelats Wildfires are one of the most prominent risks for Mediterranean forests, reducing the flow of ecosystem services and representing a hazard for infrastructure and human lives. Several wildfire prevention programs in southern Europe are currently incorporating extensive livestock grazers in fire prevention activities to reduce the high costs of mechanical clearance. Among these the Andalusian network of grazed fuel breaks, the so-called RAPCA program, stands out for its dimension and stability over time. RAPCA currently works with 220 local shepherds who, with their guided flocks maintain low biomass levels in almost 6000 ha of fuel breaks in public forests to meet fire prevention standards. This work analyses the institutional design and performance of the RAPCA payment scheme under a payment for environmental services (PES) framework. Results show effectiveness of the payment scheme while efficiency is achieved through savings relative to the mainstream mechanized biomass removal, as well as through reduced information asymmetry. High-level and stable political commitment has been crucial for the emergence and consolidation of RAPCA. Moreover, key intermediaries and sound monitoring practices increased levels of trust amongst involved actors. Beneficial side-effects include social recognition of shepherds’ activities and reduction of their friction with forest managers.

Description: Forests, Vol. 9, Pages 462: Preferences of Tourists for the Service Quality of Taichung Calligraphy Greenway in Taiwan Forests doi: 10.3390/f9080462 Authors: Wan-Yu Liu Ching Chung This study explores preferences for a set of attributes that characterize the recreational value of Calligraphy Greenway, the most notable greenbelt in Taichung City, Taiwan. As an urban green space, the Calligraphy Greenway has its own recreational attributes and visitors’ preferences. This study uses the choice experiment method to determine visitors’ preference levels for five major attributes to improve the recreational quality. On average, each visitor visited there 9.15 times in the past year and spent 2.37 h per visit. Of the five recreational attributes, satisfaction with recreational activity opportunities had the highest score and satisfaction with cultural landscape resources had the lowest score. The importance is ranked in the order of recreational service quality, total recreational cost, environmental landscape resources, cultural landscape resources and recreational activity opportunities. Considering difference of groups, female visitors were more concerned with cost and activities but male visitors were more concerned with service quality and natural/cultural landscape resources. Local visitors were more concerned with cost and activities but non-local visitors were more concerned with environmental/cultural landscape resources. Both were concerned with service quality. Based on the results, this study makes the following recommendations: cultural landscape resources and quality of recreational services and facilities should be improved and more complete interpretative educational guidance should be provided to increase visitors’ willingness to visit. Additionally, it is suggested to set up various districts to cater for preferences of different visitor groups.

Description: Forests, Vol. 9, Pages 463: Implementing Participatory Processes in Forestry Training Using Social Network Analysis Techniques Forests doi: 10.3390/f9080463 Authors: Simone Blanc Federico Lingua Livio Bioglio Ruggero G. Pensa Filippo Brun Angela Mosso Public participation has become an important driver in increasing public acceptance of policy decisions, especially in the forestry sector, where conflicting interests among the actors are frequent. Stakeholder Analysis, complemented by Social Network Analysis techniques, was used to support the participatory process and to understand the complex relationships and the strong interactions among actors. This study identifies the forestry training sector stakeholders in the Western Italian Alps and describes their characteristics and priorities, in relation to training activities on entrepreneurial topics for forestry loggers. The hierarchy among actors has been identified, highlighting their respective roles and influence in decision-making processes. A lack of mutual communication among different and well-separated categories of actors has been identified, while good connections between stakeholders, operating in different territories, despite the presence of administrative and logistical barriers, have been observed. Training is a topic involving actors with different roles and interests. Nevertheless, all actors consider training about how to improve yields of forest operations and how to assess investments, particularly in innovative machinery, to be crucially important and conducive to a better comprehension of the wood supply chain and the enhancement of the raw material.

Description: Future Internet, Vol. 10, Pages 71: Hybrid Approach with Improved Genetic Algorithm and Simulated Annealing for Thesis Sampling Future Internet doi: 10.3390/fi10080071 Authors: Shardrom Johnson Jinwu Han Yuanchen Liu Li Chen Xinlin Wu Sampling inspection uses the sample characteristics to estimate that of the population, and it is an important method to describe the population, which has the features of low cost, strong applicability and high scientificity. This paper aims at the sampling inspection of the master’s degree thesis to ensure their quality, which is commonly estimated by random sampling. Since there are disadvantages in random sampling, a hybrid algorithm combined with an improved genetic algorithm and a simulated annealing algorithm is proposed in this paper. Furthermore, a novel mutation strategy is introduced according to the specialty of Shanghai’s thesis sampling to improve the efficiency of sampling inspection; the acceleration of convergence of the algorithm can also take advantage of this. The new algorithm features the traditional genetic algorithm, and it can obtain the global optimum in the optimization process and provide the fairest sampling plan under the constraint of multiple sampling indexes. The experimental results on the master’s thesis dataset of Shanghai show that the proposed algorithm well meets the requirements of the sampling inspection in Shanghai with a lower time-complexity.

Description: Future Internet, Vol. 10, Pages 70: Multidiscipline Integrated Platform Based on Probabilistic Analysis for Manufacturing Engineering Processes Future Internet doi: 10.3390/fi10080070 Authors: Lijun Zhang Kai Liu Jian Liu Researchers from different disciplines, such as materials science, computer science, safety science, mechanical engineering and controlling engineering, have aimed to improve the quality of manufacturing engineering processes. Considering the requirements of research and development of advanced materials, reliable manufacturing and collaborative innovation, a multidiscipline integrated platform framework based on probabilistic analysis for manufacturing engineering processes is proposed. The proposed platform consists of three logical layers: The requirement layer, the database layer and the application layer. The platform is intended to be a scalable system to gradually supplement related data, models and approaches. The main key technologies of the platform, encapsulation methods, information fusion approaches and the collaborative mechanism are also discussed. The proposed platform will also be gradually improved in the future. In order to exchange information for manufacturing engineering processes, scientists and engineers of different institutes of materials science and manufacturing engineering should strengthen their cooperation.

Description: Forests, Vol. 9, Pages 461: A Review on the Dynamics of Prescribed Fire, Tree Mortality, and Injury in Managing Oak Natural Communities to Minimize Economic Loss in North America Forests doi: 10.3390/f9080461 Authors: Daniel C. Dey Callie Jo Schweitzer The long history of fire in North America spans millennia and is recognized as an important driver in the widespread and long-term dominance of oak species and oak natural communities. Frequent wildfires from about 1850 to 1950 resulted in much forest damage, and gained fire a negative reputation. The lack of fire for the past nearly 100 years due to suppression programs is now indicted as a major cause of widespread oak regeneration failures and loss of fire-dependent natural communities. The use of prescribed fire is increasing in forest management and ecosystem restoration. An understanding of fire effects on trees can provide the basis for the silviculture of restoring and sustaining oak ecosystems. We present an overview of fire-tree wounding interactions, highlight important determinants of fire injury and damage, and discuss several practical situations where fire can be used to favor oak while minimizing damage and devaluation of the forest. We also identify stages in stand development, regeneration methods, and management objectives for which fire has the potential of causing substantial damage and recommend preferred alternative practices.

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: Sensors, Vol. 18, Pages 2472: Multiple Instances QoS Routing in RPL: Application to Smart Grids Sensors doi: 10.3390/s18082472 Authors: Jad Nassar Matthieu Berthomé Jérémy Dubrulle Nicolas Gouvy Nathalie Mitton Bruno Quoitin The Smart Grid (SG) aims to transform the current electric grid into a “smarter” network where the integration of renewable energy resources, energy efficiency and fault tolerance are the main benefits. This is done by interconnecting every energy source, storage point or central control point with connected devices, where heterogeneous SG applications and signalling messages will have different requirements in terms of reliability, latency and priority. Hence, data routing and prioritization are the main challenges in such networks. So far, RPL (Routing Protocol for Low-Power and Lossy networks) protocol is widely used on Smart Grids for distributing commands over the grid. RPL assures traffic differentiation at the network layer in wireless sensor networks through the logical subdivision of the network in multiple instances, each one relying on a specific Objective Function. However, RPL is not optimized for Smart Grids, as its main objective functions and their associated metric does not allow Quality of Service differentiation. To overcome this, we propose OFQS an objective function with a multi-objective metric that considers the delay and the remaining energy in the battery nodes alongside with the dynamic quality of the communication links. Our function automatically adapts to the number of instances (traffic classes) providing a Quality of Service differentiation based on the different Smart Grid applications requirements. We tested our approach on a real sensor testbed. The experimental results show that our proposal provides a lower packet delivery latency and a higher packet delivery ratio while extending the lifetime of the network compared to solutions in the literature.

Description: Sensors, Vol. 18, Pages 2465: Improving Classification Algorithms by Considering Score Series in Wireless Acoustic Sensor Networks Sensors doi: 10.3390/s18082465 Authors: Amalia Luque Javier Romero-Lemos Alejandro Carrasco Julio Barbancho The reduction in size, power consumption and price of many sensor devices has enabled the deployment of many sensor networks that can be used to monitor and control several aspects of various habitats. More specifically, the analysis of sounds has attracted a huge interest in urban and wildlife environments where the classification of the different signals has become a major issue. Various algorithms have been described for this purpose, a number of which frame the sound and classify these frames, while others take advantage of the sequential information embedded in a sound signal. In the paper, a new algorithm is proposed that, while maintaining the frame-classification advantages, adds a new phase that considers and classifies the score series derived after frame labelling. These score series are represented using cepstral coefficients and classified using standard machine-learning classifiers. The proposed algorithm has been applied to a dataset of anuran calls and its results compared to the performance obtained in previous experiments on sensor networks. The main outcome of our research is that the consideration of score series strongly outperforms other algorithms and attains outstanding performance despite the noisy background commonly encountered in this kind of application.

Description: Future Internet, Vol. 10, Pages 72: Context Analysis of Cloud Computing Systems Using a Pattern-Based Approach Future Internet doi: 10.3390/fi10080072 Authors: Ludger Goeke Nazila Gol Mohammadi Maritta Heisel Cloud computing services bring new capabilities for hosting and offering complex collaborative business operations. However, these advances might bring undesirable side-effects, e.g., introducing new vulnerabilities and threats caused by collaboration and data exchange over the Internet. Hence, users have become more concerned about security and privacy aspects. For secure provisioning of a cloud computing service, security and privacy issues must be addressed by using a risk assessment method. To perform a risk assessment, it is necessary to obtain all relevant information about the context of the considered cloud computing service. The context analysis of a cloud computing service and its underlying system is a difficult task because of the variety of different types of information that have to be considered. This context information includes (i) legal, regulatory and/or contractual requirements that are relevant for a cloud computing service (indirect stakeholders); (ii) relations to other involved cloud computing services; (iii) high-level cloud system components that support the involved cloud computing services; (iv) data that is processed by the cloud computing services; and (v) stakeholders that interact directly with the cloud computing services and/or the underlying cloud system components. We present a pattern for the contextual analysis of cloud computing services and demonstrate the instantiation of our proposed pattern with real-life application examples. Our pattern contains elements that represent the above-mentioned types of contextual information. The elements of our pattern conform to the General Data Protection Regulation. Besides the context analysis, our pattern supports the identification of high-level assets. Additionally, our proposed pattern supports the documentation of the scope and boundaries of a cloud computing service conforming to the requirements of the ISO 27005 standard (information security risk management). The results of our context analysis contribute to the transparency of the achieved security and privacy level of a cloud computing service. This transparency can increase the trust of users in a cloud computing service. We present results of the RestAssured project related to the context analysis regarding cloud computing services and their underlying cloud computing systems. The context analysis is the prerequisite to threat and control identification that are performed later in the risk management process. The focus of this paper is the use of a pattern at the time of design systematic context analysis and scope definition for risk management methods.

Description: Algorithms, Vol. 11, Pages 111: A Weighted Histogram-Based Tone Mapping Algorithm for CT Images Algorithms doi: 10.3390/a11080111 Authors: David Völgyes Anne Catrine Trægde Martinsen Arne Stray-Pedersen Dag Waaler Marius Pedersen Computed Tomography (CT) images have a high dynamic range, which makes visualization challenging. Histogram equalization methods either use spatially invariant weights or limited kernel size due to the complexity of pairwise contribution calculation. We present a weighted histogram equalization-based tone mapping algorithm which utilizes Fast Fourier Transform for distance-dependent contribution calculation and distance-based weights. The weights follow power-law without distance-based cut-off. The resulting images have good local contrast without noticeable artefacts. The results are compared to eight popular tone mapping operators.

Description: Forests, Vol. 9, Pages 447: Tradeoffs in Timber, Carbon, and Cash Flow under Alternative Management Systems for Douglas-Fir in the Pacific Northwest Forests doi: 10.3390/f9080447 Authors: David D. Diaz Sara Loreno Gregory J. Ettl Brent Davies Forest management choices offer significant potential to mitigate global climate change and biodiversity loss. To illuminate tradeoffs relevant to policymakers, forest sector stakeholders, and consumers of forest products, we utilize three Key Performance Indicators—average carbon storage in the forest and wood products; cumulative timber output; and discounted cash flow—to compare four alternative management scenarios for Douglas-fir forests on 64 parcels across western Oregon and Washington. These scenarios are designed to meet one of two alternative management objectives: (i) maximize Net Present Value; or (ii) maximize sustained timber yield; according to one of two alternative sets of forest practice constraints: (i) compliance with minimum Oregon/Washington Forest Practices Act (FPA) rules; or (ii) two key requirements (increased green tree retention and wider riparian buffers) of Forest Stewardship Council (FSC) certification. Improved performance in terms of carbon storage for these alternatives generally also corresponded with reduced Net Present Value and timber yields. The gap between FSC and FPA performance indicators was wider in Oregon than Washington, which is primarily attributed to the higher level of stream protection required under Washington versus Oregon FPA rules. We observed consistently higher average carbon storage per cumulative timber output among FSC scenarios relative to business-as-usual, indicating FSC-certified wood carries an embedded carbon benefit. Our findings highlight options for targeted policies to incentivize management that increases carbon storage and minimizes disruptions in timber output, as well as for narrowing the financial gap (or opportunity cost) that would be involved in a transition away from contemporary common practice on industrial timberlands in the coastal Douglas-fir forests of the Pacific Northwest.

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: Forests, Vol. 9, Pages 467: State of the Art on the Use of Trees as Supports and Anchors in Forest Operations Forests doi: 10.3390/f9080467 Authors: Luca Marchi Stefano Grigolato Omar Mologni Roberto Scotta Raffaele Cavalli Lucio Montecchio Tree stability assessment is fundamental to preserve the safety of both people and goods. This topic attributes high relevance to cable-supported harvesting where trees and stumps are used as supporting and anchoring elements. In this case, the applied external loads are characterized by higher magnitude and dynamic amplification effects than the typical forces acting on trees (e.g., those derived from meteorological events). Consequently, due to the higher forces involved on cable-supported harvesting on relatively young trees used as supports and anchors, the risk of uprooting and stem failures is real. Numerous studies have been conducted on tree stability and the impact of the external loads has been positively linked to the consequent tree failures, in terms of root-plate overturning and stem breakages, or parasite-mediated wood decay involving the root system, thus giving a better understanding of how different trees species deal with such occurrences. This review aims to synthetize and examine the main aspects covered by research works available in literature that, directly or indirectly, might be helpful in clarifying the behavior of standing trees or tree stumps used as supports and anchors in cable-supported forest operations. Lastly, areas that lack research in this particular topic as well as consequent operating suggestions are highlighted in the conclusions.

Description: Forests, Vol. 9, Pages 470: The Carbon Sequestration Potential of Degraded Agricultural Land in the Amhara Region of Ethiopia Forests doi: 10.3390/f9080470 Authors: Beyene Belay Elisabeth Pötzelsberger Hubert Hasenauer Forests are a key player within the global carbon cycle and reforestation is an important climate change mitigation mechanism. In this study, we identify potentially suitable areas for reforestation to assess the carbon sequestration potential in the highly deforested and degraded Amhara region of Ethiopia. We apply biogeochemical mechanistic ecosystem modelling to predict the amount of carbon that can be potentially sequestered within different time horizons. Since human intervention plays a key role within the Amhara region, three different forest management scenarios and five different rotation periods following reforestation are tested: (i) unthinned; (ii) removal of 5% of the stem carbon every 20 years (thinning 1); and (iii) removal of 10% stem carbon every 20 years (thinning 2), as well as a rotation period of 10, 30, 50, 100, and 150 years. Sustainable management of reforested land is addressed by implementing the so called ‘Normal-forest’ system (equal representation of every age class). This ensures the long term sequestration effect of reforested areas. The study shows that 3.4 Mha (Mha = Million hectare) of land, including bare land (0.7 Mha), grass land (1.2 Mha), and shrub land (1.5 Mha) can be considered as ecologically potentially suitable for reforestation. Assuming a 100 year rotation period in a ‘Normal-forest’ system, this shows that a total net carbon sequestration potential of 177 Tg C (10.8 Tg C in the soil and 165.9 Tg C aboveground; Teragram = 1012 g) is possible, if all 3.4 Mha are replanted. The highest total net carbon sequestration (soil and aboveground) was evident for the Highland-wet agro-ecological zone, whereas the lowest values are typically in the Midland-dry zone. The highest net aboveground carbon sequestration was predicted for reforestations on current grass land and shrub land versus bare land, whereas the highest net soil carbon sequestration was predicted on current bare land, followed by grass land and shrub land.

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: Sensors, Vol. 18, Pages 2534: A Gyroscope Bias Estimation Algorithm Based on Map Specific Information Sensors doi: 10.3390/s18082534 Authors: Tian Tan Ao Peng Junjun Huang Lingxiang Zheng Gang Ou In an inertial navigation system, especially in a pedestrian dead-reckoning system, gyroscope bias can demonstrably reduce positioning accuracy. A novel gyroscope bias estimation algorithm is proposed, which estimates the bias of a gyroscope under any set of angle observations. Moreover, a method for obtaining Euler angles using map corridor information is proposed. The heading information obtained from a map is used to estimate the bias, and the estimated bias is used to correct the trajectories. Experimental results show that it is feasible for the algorithm to estimate the bias of the gyroscope.

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: Sensors, Vol. 18, Pages 2578: An Outlook on Physical and Virtual Sensors for a Socially Interactive Internet Sensors doi: 10.3390/s18082578 Authors: Ngombo Armando André Rodrigues Vasco Pereira Jorge Sá Silva Fernando Boavida The Internet keeps changing at a rapid pace, driven mainly by the emerging concepts and applications that make it aware of the physical world and responsive to user context. The Internet of Things (IoT) concept is quickly giving way to more advanced and highly interactive environments that go well beyond the mere sensing of the physical world. Today, in addition to traditional electronic devices, IoT sensing/actuating includes both software and human-based entities. This paper provides an outlook on the future of sensing/actuating approaches on the Internet at large, which we see increasingly related to all kinds of socially interactive technologies. With these objectives in mind, we propose a taxonomy to deal with the heterogeneity of sensing/actuating approaches in IoT. We also analyse the state-of-the-art of Social Sensing. Finally, we identify open issues and associated research opportunities, the main ones being the integration of all sensing approaches, the combination of social sciences, engineering, and computing as enablers of context-aware, cognitive applications and, last but not least, the unified management of large sets of very heterogeneous sensors/actuators.

Description: Sensors, Vol. 18, Pages 2576: General Signal Model for Multiple-Input Multiple-Output GMTI Radar Sensors doi: 10.3390/s18082576 Authors: Fuyou Li Feng He Zhen Dong Manqing Wu Yongsheng Zhang Multiple-input multiple-output (MIMO) ground moving target indication (GMTI) radar has been studied recently because of its excellent performance. In this paper, a general signal model is established for the MIMO GMTI radar with both fast-time and slow-time waveforms. The general signal model can be used to evaluate the performance of the MIMO GMTI radar with arbitrary waveforms such as the ideal orthogonal, code division multiple access (CDMA), frequency-division multiple access (FDMA), time division multiple access (TDMA), and Doppler division multiple access (DDMA) waveforms. We proposed a range-compensation method to eliminate the range-dependence of the FDMA waveforms. The simulation results indicate that the improved performance of FDMA waveforms is achieved utilizing the range-compensation method.

Description: Sensors, Vol. 18, Pages 2572: Tunable Fabry-Perot Interferometer Designed for Far-Infrared Wavelength by Utilizing Electromagnetic Force Sensors doi: 10.3390/s18082572 Authors: Dong Geon Jung Jun Yeop Lee Jae Keon Kim Daewoong Jung Seong Ho Kong A tunable Fabry-Perot interferometer (TFPI)-type wavelength filter designed for the long-wavelength infrared (LWIR) region is fabricated using micro electro mechanical systems (MEMS) technology and the novel polydimethylsiloxane (PDMS) micro patterning technique. The structure of the proposed infrared sensor consists of a Fabry-Perot interferometer (FPI)-based optical filter and infrared (IR) detector. An amorphous Si-based thermal IR detector is located under the FPI-based optical filter to detect the IR-rays filtered by the FPI. The filtered IR wavelength is selected according to the air etalon gap between reflectors, which is defined by the thickness of the patterned PDMS. The 8 μm-thick PDMS pattern is fabricated on a 3 nm-thick Al layer used as a reflector. The air etalon gap is changed using the electromagnetic force between the permanent magnet and solenoid. The measured PDMS gap height is about 2 μm, ranging from 8 μm to 6 μm, with driving current varying from 0 mA to 600 mA, resulting in a tunable wavelength range of 4 μm. The 3-dB bandwidth (full width at half maximum, FWHM) of the proposed filter is 1.5 nm, while the Free Spectral Range (FSR) is 8 μm. Experimental results show that the proposed TFPI can detect a specific wavelength at the long LWIR region.

Description: Sensors, Vol. 18, Pages 2574: Modeling and Control of a Micro AUV: Objects Follower Approach Sensors doi: 10.3390/s18082574 Authors: Jesus Arturo Monroy-Anieva Cyril Rouviere Eduardo Campos-Mercado Tomas Salgado-Jimenez Luis Govinda Garcia-Valdovinos This work describes the modeling, control and development of a low cost Micro Autonomous Underwater Vehicle (μ-AUV), named AR2D2. The main objective of this work is to make the vehicle to detect and follow an object with defined color by means of the readings of a depth sensor and the information provided by an artificial vision system. A nonlinear PD (Proportional-Derivative) controller is implemented on the vehicle in order to stabilize the heave and surge movements. A formal stability proof of the closed-loop system using Lyapunov’s theory is given. Furthermore, the performance of the μ-AUV is validated through numerical simulations in MatLab and real-time experiments.

Description: Sensors, Vol. 18, Pages 2570: The Sensory Quality and Volatile Profile of Dark Chocolate Enriched with Encapsulated Probiotic Lactobacillus plantarum Bacteria Sensors doi: 10.3390/s18082570 Authors: Milica Mirković Sanja Seratlić Kieran Kilcawley David Mannion Nemanja Mirković Zorica Radulović Cocoa and dark chocolate have a wide variety of powerful antioxidants and other nutrients that can positively affect human health. Probiotic dark chocolate has the potential to be a new product in the growing number of functional foods. In this study, encapsulated potential probiotic Lactobacillus plantarum 564 and commercial probiotic Lactobacillus plantarum 299v were added in the production of dark chocolate. The results show very good survival of probiotic bacteria after production and during storage, reaching 108cfu/g in the first 60 days and over 106cfu/g up to 180 days. No statistically significant difference (p > 0.05) in chemical composition and no major differences in the volatile profiles between control and experimental chocolate samples were observed, indicating no impact of probiotic bacteria on compositional and sensory characteristics of dark chocolate. The sensory evaluation of control and both probiotic dark chocolate samples showed excellent sensory quality after 60 and 180 days of storage, demonstrating that probiotics did not affect aroma, texture and appearance of chocolate. Due to a high viability of bacterial cells and acceptable sensory properties, it can be concluded that encapsulated probiotics Lb. plantarum 564 and Lb. plantarum 299v could be successfully used in the production of probiotic dark chocolate.

Description: Sensors, Vol. 18, Pages 2564: Indirect Measurement of Ground Reaction Forces and Moments by Means of Wearable Inertial Sensors: A Systematic Review Sensors doi: 10.3390/s18082564 Authors: Andrea Ancillao Salvatore Tedesco John Barton Brendan O’Flynn In the last few years, estimating ground reaction forces by means of wearable sensors has come to be a challenging research topic paving the way to kinetic analysis and sport performance testing outside of labs. One possible approach involves estimating the ground reaction forces from kinematic data obtained by inertial measurement units (IMUs) worn by the subject. As estimating kinetic quantities from kinematic data is not an easy task, several models and protocols have been developed over the years. Non-wearable sensors, such as optoelectronic systems along with force platforms, remain the most accurate systems to record motion. In this review, we identified, selected and categorized the methodologies for estimating the ground reaction forces from IMUs as proposed across the years. Scopus, Google Scholar, IEEE Xplore, and PubMed databases were interrogated on the topic of Ground Reaction Forces estimation based on kinematic data obtained by IMUs. The identified papers were classified according to the methodology proposed: (i) methods based on direct modelling; (ii) methods based on machine learning. The methods based on direct modelling were further classified according to the task studied (walking, running, jumping, etc.). Finally, we comparatively examined the methods in order to identify the most reliable approaches for the implementation of a ground reaction force estimator based on IMU data.

Description: Sensors, Vol. 18, Pages 2563: Joint Center Estimation Using Single-Frame Optimization: Part 2: Experimentation Sensors doi: 10.3390/s18082563 Authors: Eric Frick Salam Rahmatalla Human motion capture is driven by joint center location estimates, and error in their estimation can be compounded by subsequent kinematic calculations. Soft tissue artifact (STA), the motion of tissue relative to the underlying bones, is a primary cause of error in joint center calculations. A method for mitigating the effects of STA, single-frame optimization (SFO), was introduced and numerically verified in Part 1 of this work, and the purpose of this article (Part 2) is to experimentally compare the results of SFO with a marker-based solution. The experimentation herein employed a single-degree-of-freedom pendulum to simulate human joint motion, and the effects of STA were simulated by affixing the inertial measurement unit to the pendulum indirectly through raw, vacuum-sealed meat. The inertial sensor was outfitted with an optical marker adapter so that its location could be optically determined by a camera-based motion-capture system. During the motion, inertial effects and non-rigid attachment of the inertial sensor caused the simulated STA to manifest via unrestricted motion (six degrees of freedom) relative to the rigid pendulum. The redundant inertial and optical instrumentation allowed a time-varying joint center solution to be determined both by optical markers and by SFO, allowing for comparison. The experimental results suggest that SFO can achieve accuracy comparable to that of state-of-the-art joint center determination methods that use optical skin markers (root mean square error of 7.87–37.86 mm), and that the time variances of the SFO solutions are correlated (r =  0.58–0.99) with the true, time-varying joint center solutions. This suggests that SFO could potentially help to fill a gap in the existing literature by improving the characterization and mitigation of STA in human motion capture.

Description: Sensors, Vol. 18, Pages 2562: A Real-Time Imaging Algorithm Based on Sub-Aperture CS-Dechirp for GF3-SAR Data Sensors doi: 10.3390/s18082562 Authors: Guang-Cai Sun Yanbin Liu Mengdao Xing Shiyu Wang Liang Guo Jun Yang Conventional synthetic aperture radar (SAR) imaging algorithms usually require a period of time to process data that is longer than the time it takes to record one synthetic aperture or that corresponding to an adequate azimuth resolution. That is to say, the real-time processing system is idle during the long data recording time and the utilization of computational resources is low. To deal with this problem, a real-time imaging algorithm based on sub-aperture chirp scaling dechirp (CS-dechirp) is proposed in this paper. With CS-dechirp, the sub-aperture data could be processed to form an image with relatively low resolution. Subsequently, a few low-resolution images are generated as longer azimuth data are recorded. At the stage of full-resolution image generation, a coherent combination method for the low-resolution complex-value images is developed. As the low-resolution complex-value images are coherently combined one by one, the resolution is gradually improved and the full-resolution image is finally obtained. The results of a simulation and real data from the GF3-SAR validate the effectiveness of the proposed algorithm.

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: Algorithms, Vol. 11, Pages 119: An Opportunistic Network Routing Algorithm Based on Cosine Similarity of Data Packets between Nodes Algorithms doi: 10.3390/a11080119 Authors: Yucheng Lin Zhigang Chen Jia Wu Leilei Wang The mobility of nodes leads to dynamic changes in topology structure, which makes the traditional routing algorithms of a wireless network difficult to apply to the opportunistic network. In view of the problems existing in the process of information forwarding, this paper proposed a routing algorithm based on the cosine similarity of data packets between nodes (cosSim). The cosine distance, an algorithm for calculating the similarity between text data, is used to calculate the cosine similarity of data packets between nodes. The data packet set of nodes are expressed in the form of vectors, thereby facilitating the calculation of the similarity between the nodes. Through the definition of the upper and lower thresholds, the similarity between the nodes is filtered according to certain rules, and finally obtains a plurality of relatively reliable transmission paths. Simulation experiments show that compared with the traditional opportunistic network routing algorithm, such as the Spray and Wait (S&W) algorithm and Epidemic algorithm, the cosSim algorithm has a better transmission effect, which can not only improve the delivery ratio, but also reduce the network transmission delay and decline the routing overhead.

Description: Algorithms, Vol. 11, Pages 120: Probabilistic Interval-Valued Hesitant Fuzzy Information Aggregation Operators and Their Application to Multi-Attribute Decision Making Algorithms doi: 10.3390/a11080120 Authors: Wenying Wu Ying Li Zhiwei Ni Feifei Jin Xuhui Zhu Based on the probabilistic interval-valued hesitant fuzzy information aggregation operators, this paper investigates a novel multi-attribute group decision making (MAGDM) model to address the serious loss of information in a hesitant fuzzy information environment. Firstly, the definition of probabilistic interval-valued hesitant fuzzy set will be introduced, and then, using Archimedean norm, some new probabilistic interval-valued hesitant fuzzy operations are defined. Secondly, based on these operations, the generalized probabilistic interval-valued hesitant fuzzy ordered weighted averaging (GPIVHFOWA) operator, and the generalized probabilistic interval-valued hesitant fuzzy ordered weighted geometric (GPIVHFOWG) operator are proposed, and their desirable properties are discussed. We further study their common forms and analyze the relationship among these proposed operators. Finally, a new probabilistic interval-valued hesitant fuzzy MAGDM model is constructed, and the feasibility and effectiveness of the proposed model are verified by using an example of supplier selection.

Description: Forests, Vol. 9, Pages 478: Effects of Leaf Age and Exogenous Hormones on Callus Initiation, Rooting Formation, Bud Germination, and Plantlet Formation in Chinese Fir Leaf Cuttings Forests doi: 10.3390/f9080478 Authors: Lili Zhou Shubin Li Peng Huang Sizu Lin Shalom Daniel Addo-Danso Zhihui Ma Guochang Ding To guide the cultivation of superior Chinese fir plantlets, we designed an L16(4)4 orthogonal experiment to determine how leaf age and exogenous hormones influence key growth processes in leaf cuttings. Hormone concentration and treatment duration significantly affected leaf cuttings in all three age categories; 6-benzylaminopurine (6-BA), 1-naphthaleneacetic acid (NAA), and treatment time exerted the strongest effects on callus initiation rates. Additionally, NAA had the largest effect on the rooting rate across all cuttings, and all three hormones significantly influenced the bud germination rate. Based on our experimental results, expected optimal treatments for callus initiation were 10 mg∙L−1 indole-3-butyric acid (IBA) for 10 min, 30 mg∙L−1 NAA for 15 min, and 10 mg∙L−1 NAA plus 30 mg∙L−1 IBA for 10 min. For the rooting rate, the expected optimal treatment was 50 mg∙L−1 NAA and 40 mg∙L−1 IBA for 5–20 min. Finally, for bud germination, optimal treatments were 20 min of immersion in water, 30 mg∙L−1 6-BA plus 50 mg∙L−1 NAA for 15 min, and 30 mg∙L−1 6-BA for 5 min. Plantlet formation only occurred in the <one-year-old leaves, and at very low rates (maximum 5.8%); this outcome is likely attributable to the mother plant’s relatively old age (five years). Plantlet formation from cuttings is dependent on ensuring the rooting rate after callus initiation. Therefore, to promote rooting rates and bud germination, we recommend leaving more xylem at the base of leaf cuttings.

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: Sensors, Vol. 18, Pages 2589: Design of Novel Ceramic Preconcentrator and Integration in Gas Chromatographic System for Detection of Ethylene Gas from Ripening Bananas Sensors doi: 10.3390/s18082589 Authors: Nayyer Zaidi Muhammad Tahir Micheal Vellekoop Walter Lang In this paper, a novel ceramic preconcentrator is manufactured using aluminum nitride (ALN) ceramics. The preconcentrator consists of a heater, a preconcentrator body, a gas inlet and a gas outlet. The adsorption material, Carbosieve SII, is loaded into the preconcentrator. The preconcentrator is integrated with a previously developed micro gas chromatographic system filled with ethylene. When operated, adequate ethylene gas is adsorbed into the preconcentrator. The application of heat pulse also successfully desorbs the ethylene gas. Tests are conducted with ethylene gas at concentrations of 10 ppm, 5 ppm and 2.5 ppm and 400 ppb, respectively. The system is also tested with ethylene gas from ripening bananas over a period of three days. No interference signal is observed in the chromatogram because of other ripening gases (e.g., carbon dioxide, oxygen, alcohol) and humidity. A detection limit of 25 ppb is realized with this system. The developed preconcentrator has several applications, e.g., in food industry and environmental monitoring.

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: Sensors, Vol. 18, Pages 2580: Evaluation of Water Indices for Surface Water Extraction in a Landsat 8 Scene of Nepal Sensors doi: 10.3390/s18082580 Authors: Tri Dev Acharya Anoj Subedi Dong Ha Lee Accurate and frequent updates of surface water have been made possible by remote sensing technology. Index methods are mostly used for surface water estimation which separates the water from the background based on a threshold value. Generally, the threshold is a fixed value, but can be challenging in the case of environmental noise, such as shadow, forest, built-up areas, snow, and clouds. One such challenging scene can be found in Nepal where no such evaluation has been done. Taking that in consideration, this study evaluates the performance of the most widely used water indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), and Automated Water Extraction Index (AWEI) in a Landsat 8 scene of Nepal. The scene, ranging from 60 m to 8848 m, contains various types of water bodies found in Nepal with different forms of environmental noise. The evaluation was conducted based on measures from a confusion matrix derived using validation points. Comparing visually and quantitatively, not a single method was able to extract surface water in the entire scene with better accuracy. Upon selecting optimum thresholds, the overall accuracy (OA) and kappa coefficient (kappa) was improved, but not satisfactory. NDVI and NDWI showed better results for only pure water pixels, whereas MNDWI and AWEI were unable to reject snow cover and shadows. Combining NDVI with NDWI and AWEI with shadow improved the accuracy but inherited the NDWI and AWEI characteristics. Segmenting the test scene with elevations above and below 665 m, and using NDVI and NDWI for detecting water, resulted in an OA of 0.9638 and kappa of 0.8979. The accuracy can be further improved with a smaller interval of categorical characteristics in one or multiple scenes.

Description: Sensors, Vol. 18, Pages 2581: The Shared Bicycle and Its Network—Internet of Shared Bicycle (IoSB): A Review and Survey Sensors doi: 10.3390/s18082581 Authors: Shu Shen Zhao-Qing Wei Li-Juan Sun Yang-Qing Su Ru-Chuan Wang Han-Ming Jiang With the expansion of Intelligent Transport Systems (ITS) in smart cities, the shared bicycle has developed quickly as a new green public transportation mode, and is changing the travel habits of citizens heavily across the world, especially in China. The purpose of the current paper is to provide an inclusive review and survey on shared bicycle besides its benefits, history, brands and comparisons. In addition, it proposes the concept of the Internet of Shared Bicycle (IoSB) for the first time, as far as we know, to find a feasible solution for those technical problems of the shared bicycle. The possible architecture of IoSB in our opinion is presented, as well as most of key IoT technologies, and their capabilities to merge into and apply to the different parts of IoSB are introduced. Meanwhile, some challenges and barriers to IoSB’s implementation are expressed thoroughly too. As far as the advice for overcoming those barriers be concerned, the IoSB’s potential aspects and applications in smart city with respect to technology development in the future provide another valuable further discussion in this paper.

Description: Forests, Vol. 9, Pages 321: Dynamic Patterns of Trees Species in Miombo Forest and Management Perspectives for Sustainable Production—Case Study in Huambo Province, Angola Forests doi: 10.3390/f9060321 Authors: Vasco Chiteculo Peter Surovy This paper aims to assess important forest parameters, including tree density, diameter at breast height (DBH), and age distribution, investigate the dynamic growth of miombo tree species, and employ this information to design a management framework in miombo forests. The delineation of the management zones was based on unsupervised land cover classification that began with three zones where ground data was collected and increased to five zones. Eighteen circular plots (25.2 m radius) were randomly distributed over the study areas to assess the current situation and potential growth patterns for each species. The patterns of the six most representative tree species of miombo in Angola were described and we used KORFiT 2.4 software to fit data and develop growth curves for at least three miombo species. Growth function fitness was evaluated by root mean squared error (RMSE), coefficient of determination (R2), significance of the parameters (p < 0.05), and Akaike’s information criterion (AIC). The diameter distribution of miombo tree species resembled a typical distribution of uneven-aged forest stands; higher DBH classes had lower abundances of tree species. Logistic and Gompertz growth functions were the best fits for miombo tree species. Brachystegia spiciformis Benth., is suggested as a potential species for timber management in the region because they displayed high growth potential to more quickly reach an assumed minimum DBH of 20 cm. This study concluded that miombo forest stands present an irregular structure in which DBH distribution illustrated only two patterns: many small stems and a bimodal forest structure.

Description: Future Internet, Vol. 10, Pages 46: A Tiered Control Plane Model for Service Function Chaining Isolation Future Internet doi: 10.3390/fi10060046 Authors: Håkon Gunleifsen Vasileios Gkioulos Thomas Kemmerich This article presents an architecture for encryption automation in interconnected Network Function Virtualization (NFV) domains. Current NFV implementations are designed for deployment within trusted domains, where overlay networks with static trusted links are utilized for enabling network security. Nevertheless, within a Service Function Chain (SFC), Virtual Network Function (VNF) flows cannot be isolated and end-to-end encrypted because each VNF requires direct access to the overall SFC data-flow. This restricts both end-users and Service Providers from enabling end-to-end security, and in extended VNF isolation within the SFC data traffic. Encrypting data flows on a per-flow basis results in an extensive amount of secure tunnels, which cannot scale efficiently in manual configurations. Additionally, creating secure data plane tunnels between NFV providers requires secure exchange of key parameters, and the establishment of an east–west control plane protocol. In this article, we present an architecture focusing on these two problems, investigating how overlay networks can be created, isolated, and secured dynamically. Accordingly, we propose an architecture for automated establishment of encrypted tunnels in NFV, which introduces a novel, tiered east–west communication channel between network controllers in a multi-domain environment.

Description: Forests, Vol. 9, Pages 324: Response of Black Ash Wetland Gaseous Soil Carbon Fluxes to a Simulated Emerald Ash Borer Infestation Forests doi: 10.3390/f9060324 Authors: Matthew Van Grinsven Joseph Shannon Nicholas Bolton Joshua Davis Nam Jin Noh Joseph Wagenbrenner Randall Kolka Thomas Pypker The rapid and extensive expansion of emerald ash borer (EAB) in North America since 2002 may eliminate most existing ash stands, likely affecting critical ecosystem services associated with water and carbon cycling. To our knowledge, no studies have evaluated the coupled response of black ash (Fraxinus nigra Marsh.) wetland water tables, soil temperatures, and soil gas fluxes to an EAB infestation. Water table position, soil temperature, and soil CO2 and CH4 fluxes were monitored in nine depressional headwater black ash wetlands in northern Michigan. An EAB disturbance was simulated by girdling (girdle) or felling (ash-cut) all black ash trees with diameters greater than 2.5 cm within treated wetlands (n = 3 per treatment). Soil gas fluxes were sensitive to water table position, temperature, and disturbance. Soil CO2 fluxes were significantly higher, and high soil CH4 fluxes occurred more frequently in disturbed sites. Soil CH4 fluxes in ash-cut were marginally significantly higher than girdle during post-treatment, yet both were similar to control sites. The strong connection between depressional black ash wetland study sites and groundwater likely buffered the magnitude of disturbance-related impact on water tables and carbon cycling.

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: Sensors, Vol. 18, Pages 1915: Measurement Uncertainty Calculations for pH Value Obtained by an Ion-Selective Electrode Sensors doi: 10.3390/s18061915 Authors: Józef Wiora Alicja Wiora An assessment of measurement uncertainty is a task, which has to be the final step of every chemical assay. Apart from a commonly applied typical assessment method, Monte Carlo (MC) simulations may be used. The simulations are frequently performed by a computer program, which has to be written, and therefore some programming skills are required. It is also possible to use a commonly known spreadsheet and perform such simulations without writing any code. Commercial programs dedicated for the purpose are also available. In order to show the advantages and disadvantages of the ways of uncertainty evaluation, i.e., the typical method, the MC method implemented in a program and in a spreadsheet, and commercial programs, a case of pH measurement after two-point calibration is considered in this article. The ways differ in the required mathematical transformations, degrees of software usage, the time spent for the uncertainty calculations, and cost of software. Since analysts may have different mathematical and coding skills and practice, it is impossible to point out the best way of uncertainty assessment—all of them are just as good and give comparable assessments.

Description: Sensors, Vol. 18, Pages 1916: Automatic Railway Traffic Object Detection System Using Feature Fusion Refine Neural Network under Shunting Mode Sensors doi: 10.3390/s18061916 Authors: Tao Ye Baocheng Wang Ping Song Juan Li Many accidents happen under shunting mode when the speed of a train is below 45 km/h. In this mode, train attendants observe the railway condition ahead using the traditional manual method and tell the observation results to the driver in order to avoid danger. To address this problem, an automatic object detection system based on convolutional neural network (CNN) is proposed to detect objects ahead in shunting mode, which is called Feature Fusion Refine neural network (FR-Net). It consists of three connected modules, i.e., the depthwise-pointwise convolution, the coarse detection module, and the object detection module. Depth-wise-pointwise convolutions are used to improve the detection in real time. The coarse detection module coarsely refine the locations and sizes of prior anchors to provide better initialization for the subsequent module and also reduces search space for the classification, whereas the object detection module aims to regress accurate object locations and predict the class labels for the prior anchors. The experimental results on the railway traffic dataset show that FR-Net achieves 0.8953 mAP with 72.3 FPS performance on a machine with a GeForce GTX1080Ti with the input size of 320 × 320 pixels. The results imply that FR-Net takes a good tradeoff both on effectiveness and real time performance. The proposed method can meet the needs of practical application in shunting mode.

Description: Sensors, Vol. 18, Pages 1910: Data Fusion Architectures for Orthogonal Redundant Inertial Measurement Units Sensors doi: 10.3390/s18061910 Authors: Eric Gagnon Alexandre Vachon Yanick Beaudoin This work looks at the exploitation of large numbers of orthogonal redundant inertial measurement units. Specifically, the paper analyses centralized and distributed architectures in the context of data fusion algorithms for those sensors. For both architectures, data fusion algorithms based on Kalman filter are developed. Some of those algorithms consider sensors location, whereas the others do not, but all estimate the sensors bias. A fault detection algorithm, based on residual analysis, is also proposed. Monte-Carlo simulations show better performance for the centralized architecture with an algorithm considering sensors location. Due to a better estimation of the sensors bias, the latter provides the most precise and accurate estimates and the best fault detection. However, it requires a much longer computational time. An analysis of the sensors bias correlation is also done. Based on the simulations, the biases correlation has a small effect on the attitude rate estimation, but a very significant one on the acceleration estimation.

Description: Forests, Vol. 9, Pages 352: Amount and Location of Damage to Residual Trees from Cut-to-Length Thinning Operations in a Young Redwood Forest in Northern California Forests doi: 10.3390/f9060352 Authors: Kyungrok Hwang Han-Sup Han Susan E. Marshall Deborah S. Page-Dumroese A cut-to-length (CTL) harvest system using a harvester and forwarder has been recently introduced in northern California (USA) for thinning young (<25 years old) redwood forests (Sequoia sempervirens (Lamb. ex D. Don) Endl.). However, the severity of CTL damage to residual trees in this forest type are unknown. The goals of this study were to (1) determine the location, size, and number of scars resulting from CTL harvesting and (2) compare scar size differences between redwood clumps and individual trees in two units. Most scars occurred on trees located near the forwarding trails. Wider and longer scars were associated with clumped trees (9.1–12.2 cm wide and 28.1–46.2 cm long) as compared to scars on individual trees (8.1–9.5 cm wide and 16.7–31.3 cm long), and 16–32% of the residual trees were scarred. Determining a minimum scar size will define the severity of stand damage; larger scars result in a longer time until closure. However, counting all the smaller scars that result from CTL harvesting will result in a large number of counted damaged trees. Therefore, we suggest that scars smaller than 5–10 cm width are acceptable on coastal redwood after CTL thinning.

Description: Forests, Vol. 9, Pages 350: Palaeoecological Evidence for Survival of Scots Pine through the Late Holocene in Western Ireland: Implications for Ecological Management Forests doi: 10.3390/f9060350 Authors: Jenni R. Roche Fraser J. G. Mitchell Steve Waldren Bettina S. Stefanini The dynamics of Scots pine (Pinus sylvestris L.) in Europe during the Holocene have been spatially and temporally complex. The species underwent extirpation and reintroduction in several north-west European countries. This study investigated the late Holocene vegetation history of a present-day pinewood in western Ireland, to test the widely accepted hypothesis that P. sylvestris became extinct in Ireland c. AD 400. Palaeoecological, chronological and loss-on-ignition analyses were conducted on a sediment core extracted from an adjacent lake. The pollen profile showed no major Pinus decline and a Pinus macrofossil occurred c. AD 840, indicating localised survival of P. sylvestris from c. AD 350 to the present. The available archival maps and historical literature provide supporting evidence for continuity of forest cover. The hypothesis that P. sylvestris became extinct in Ireland is rejected. The implications for ecological management are significant. We argue that P. sylvestris should be considered native to Ireland, at least at this site. As Ireland’s only putative native P. sylvestris population and the western limit of the species’ native range, this site is of high conservation value and must be carefully managed and monitored. Seed-sourcing for ex-situ forest restoration must be compatible with the long-term viability of the population in-situ.

Description: Sensors, Vol. 18, Pages 1898: Coastline Detection with Gaofen-3 SAR Images Using an Improved FCM Method Sensors doi: 10.3390/s18061898 Authors: Meng An Qian Sun Jun Hu Yuqi Tang Ziwei Zhu The coastline detection is one of the main applications of the Gaofen-3 satellite in the ocean field. However, the capability of Gaofen-3 SAR image in coastline detection has not yet been validated. In this paper, two Gaofen-3 SAR images, acquired in 2016, were used to extract the coastlines of the regions of Bohai and Taihu in China, respectively. The classical Fuzzy C-means (FCM) method was used in the coastline detection, but had been improved by combining the Wavelet decomposition algorithm to better suppress the inherent speckle noises of SAR image. Coastline detection results obtained from two Sentinel-1 SAR images acquired on the same regions were compared with those of the Gaofen-3 images. By using the manually delineated coastlines as the standards in the qualitative evaluations, improvements of about 12.0%, 8.3%, 23.8%, and 9.4% can be achieved by the improved FCM method with respect to the indicators of mean, RMSE, PGSD, and P90%, respectively; demonstrating that the Gaofen-3 data is superior to the Sentinel-1 data in the detection of coastline.

Description: Sensors, Vol. 18, Pages 1897: An IBeacon-Based Location System for Smart Home Control Sensors doi: 10.3390/s18061897 Authors: Qinghe Liu Xinshuang Yang Lizhen Deng Indoor location and intelligent control system can bring convenience to people’s daily life. In this paper, an indoor control system is designed to achieve equipment remote control by using low-energy Bluetooth (BLE) beacon and Internet of Things (IoT) technology. The proposed system consists of five parts: web server, home gateway, smart terminal, smartphone app and BLE beacons. In the web server, fingerprint matching based on RSSI stochastic characteristic and posture recognition model based on geomagnetic sensing are used to establish a more efficient equipment control system, combined with Pedestrian Dead Reckoning (PDR) technology to improve the accuracy of location. A personalized menu of remote “one-click” control is finally offered to users in a smartphone app. This smart home control system has been implemented by hardware, and precision and stability tests have been conducted, which proved the practicability and good user experience of this solution.

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: Sensors, Vol. 18, Pages 1815: Sparse Method for Direction of Arrival Estimation Using Denoised Fourth-Order Cumulants Vector Sensors doi: 10.3390/s18061815 Authors: Yangyu Fan Jianshu Wang Rui Du Guoyun Lv Fourth-order cumulants (FOCs) vector-based direction of arrival (DOA) estimation methods of non-Gaussian sources may suffer from poor performance for limited snapshots or difficulty in setting parameters. In this paper, a novel FOCs vector-based sparse DOA estimation method is proposed. Firstly, by utilizing the concept of a fourth-order difference co-array (FODCA), an advanced FOCs vector denoising or dimension reduction procedure is presented for arbitrary array geometries. Then, a novel single measurement vector (SMV) model is established by the denoised FOCs vector, and efficiently solved by an off-grid sparse Bayesian inference (OGSBI) method. The estimation errors of FOCs are integrated in the SMV model, and are approximately estimated in a simple way. A necessary condition regarding the number of identifiable sources of our method is presented that, in order to uniquely identify all sources, the number of sources K must fulfill K ≤ ( M 4 − 2 M 3 + 7 M 2 − 6 M ) / 8 . The proposed method suits any geometry, does not need prior knowledge of the number of sources, is insensitive to associated parameters, and has maximum identifiability O ( M 4 ) , where M is the number of sensors in the array. Numerical simulations illustrate the superior performance of the proposed method.

Description: Sensors, Vol. 18, Pages 1818: Dynamics and Embedded Internet of Things Input Shaping Control for Overhead Cranes Transporting Multibody Payloads Sensors doi: 10.3390/s18061818 Authors: Gerardo Peláez Joshua Vaugan Pablo Izquierdo Higinio Rubio Juan García-Prada Input shaping is an Optimal Control feedforward strategy whose ability to define how and when a flexible dynamical system defined by Ordinary Differential Equations (ODEs) and computer controlled would move into its operative space, without command induced unwanted dynamics, has been exhaustively demonstrated. This work examines the issue of Embedded Internet of Things (IoT) Input Shaping with regard to real time control of multibody oscillatory systems whose dynamics are better described by differential algebraic equations (DAEs). An overhead crane hanging a double link multibody payload has been appointed as a benchmark case; it is a multibody, multimode system. This might be worst scenario to implement Input Shaping. The reasons can be found in the wide array of constraints that arise. Firstly, the reliability of the multibody model was tested on a Functional Mock-Up Interface (FMI) with the two link payload suspended from the trolley by comparing the experimental video tapping signals in time domain faced with the signals extracted from the multibody model. The FFTs of the simulated and the experimental signal contain the same frequency harmonics only with somewhat different power due to the real world light damping in the joints. The application of this approach may be extended to other cases i.e., the usefulness of mobile hydraulic cranes is limited because the payload is supported by an overhead cable under tension that allows oscillation to occur during crane motion. If the payload size is not negligible small when compared with the cable length may introduce an additional oscillatory mode that creates a multibody double pendulum. To give the insight into the double pendulum dynamics by Lagrangian methods two slender rods as payloads are analyzed dealing with the overhead crane and a composite revolute-revolute joint is proposed to model the cable of the hydraulic crane, both assumptions facilitates an affordable analysis. This allows developing a general study of this type of multibody payloads dynamics including its normal modes, modes ratios plus ranges of frequencies expected. Input Shapers were calculated for those multimodes of vibration by convolving Specified Insensitivity (SI) shapers for each mode plus a novel Direct SI-SI shaper well suited to reduce the computational requirements, i.e., the number of the shaper taps, to carry out the convolution sum in real time by the IoT device based on a single microcontroller working as the command generator. Several comparisons are presented for the shaped and unshaped responses using both the multibody model, the experimental FMI set-up and finally a real world hydraulic crane under slewing motion commanded by an analog Joystick connected by two RF modules 802.15.4 to the IoT device that carry out the convolution sum in real time. Input Shaping improves the performances for all the cases.

Description: Sensors, Vol. 18, Pages 1810: A Comparison between the Decimated Padé Approximant and Decimated Signal Diagonalization Methods for Leak Detection in Pipelines Equipped with Pressure Sensors Sensors doi: 10.3390/s18061810 Authors: Aimé Lay-Ekuakille Laura Fabbiano Gaetano Vacca Joël Kidiamboko Kitoko Patrice Bibala Kulapa Vito Telesca Pipelines conveying fluids are considered strategic infrastructures to be protected and maintained. They generally serve for transportation of important fluids such as drinkable water, waste water, oil, gas, chemicals, etc. Monitoring and continuous testing, especially on-line, are necessary to assess the condition of pipelines. The paper presents findings related to a comparison between two spectral response algorithms based on the decimated signal diagonalization (DSD) and decimated Padé approximant (DPA) techniques that allow to one to process signals delivered by pressure sensors mounted on an experimental pipeline.

Description: Sensors, Vol. 18, Pages 1813: An Overview of High-k Oxides on Hydrogenated-Diamond for Metal-Oxide-Semiconductor Capacitors and Field-Effect Transistors Sensors doi: 10.3390/s18061813 Authors: Jiangwei Liu Yasuo Koide Thanks to its excellent intrinsic properties, diamond is promising for applications of high-power electronic devices, ultraviolet detectors, biosensors, high-temperature tolerant gas sensors, etc. Here, an overview of high-k oxides on hydrogenated-diamond (H-diamond) for metal-oxide-semiconductor (MOS) capacitors and MOS field-effect transistors (MOSFETs) is demonstrated. Fabrication routines for the H-diamond MOS capacitors and MOSFETs, band configurations of oxide/H-diamond heterointerfaces, and electrical properties of the MOS and MOSFETs are summarized and discussed. High-k oxide insulators are deposited using atomic layer deposition (ALD) and sputtering deposition (SD) techniques. Electrical properties of the H-diamond MOS capacitors with high-k oxides of ALD-Al2O3, ALD-HfO2, ALD-HfO2/ALD-Al2O3 multilayer, SD-HfO2/ALD-HfO2 bilayer, SD-TiO2/ALD-Al2O3 bilayer, and ALD-TiO2/ALD-Al2O3 bilayer are discussed. Analyses for capacitance-voltage characteristics of them show that there are low fixed and trapped charge densities for the ALD-Al2O3/H-diamond and SD-HfO2/ALD-HfO2/H-diamond MOS capacitors. The k value of 27.2 for the ALD-TiO2/ALD-Al2O3 bilayer is larger than those of the other oxide insulators. Drain-source current versus voltage curves show distinct pitch-off and p-type channel characteristics for the ALD-Al2O3/H-diamond, SD-HfO2/ALD-HfO2/H-diamond, and ALD-TiO2/ALD-Al2O3/H-diamond MOSFETs. Understanding of fabrication routines and electrical properties for the high-k oxide/H-diamond MOS electronic devices is meaningful for the fabrication of high-performance H-diamond MOS capacitor and MOSFET gas sensors.

Description: Sensors, Vol. 18, Pages 1819: Sensor Design Optimization for Ultrasonic Spectroscopy Cure Monitoring Sensors doi: 10.3390/s18061819 Authors: Christian Pommer Michael Sinapius In the field of cure monitoring, resonant ultrasonic cure monitoring is a unique technique to measure the progression of cure of composites in fully or partially closed tools. It allows for the use of electronic hardware that is less sophisticated than traditional pulse-based ultrasonic systems to obtain accurate results. While this technique is not new, it has been used very rarely. One reason for this is the lack of optimized sensors. Commercially available sensors are optimized for pulse-based ultrasonic testing. This paper establishes a possible optimized sensor design for resonant ultrasound cure monitoring using a multi-parameter FE model.

Description: Sensors, Vol. 18, Pages 1808: Tailored Algorithm for Sensitivity Enhancement of Gas Concentration Sensors Based on Tunable Laser Absorption Spectroscopy Sensors doi: 10.3390/s18061808 Authors: Everardo Vargas-Rodriguez Ana Dinora Guzman-Chavez Roberto Baeza-Serrato In this work, a novel tailored algorithm to enhance the overall sensitivity of gas concentration sensors based on the Direct Absorption Tunable Laser Absorption Spectroscopy (DA-ATLAS) method is presented. By using this algorithm, the sensor sensitivity can be custom-designed to be quasi constant over a much larger dynamic range compared with that obtained by typical methods based on a single statistics feature of the sensor signal output (peak amplitude, area under the curve, mean or RMS). Additionally, it is shown that with our algorithm, an optimal function can be tailored to get a quasi linear relationship between the concentration and some specific statistics features over a wider dynamic range. In order to test the viability of our algorithm, a basic C 2 H 2 sensor based on DA-ATLAS was implemented, and its experimental measurements support the simulated results provided by our algorithm.

Description: Sensors, Vol. 18, Pages 1809: Cooperative Feedback Bits Allocation and Transmit Power Control in Underlay Cognitive Radio Networks Sensors doi: 10.3390/s18061809 Authors: Deokhui Lee Jaewoo So In this paper, we consider an underlay cognitive radio network where the spectrum is shared with the primary network. Due to the coexistence of primary and secondary networks, primary users (PUs) are interfered with by the inter-network interference, at the same time secondary users (SUs) counteract the intra-network (inter-user) interference. Based on the cooperative feedback between the primary network and the secondary network, the secondary transmitter (ST) applies the cognitive beamforming to suppress the interference to PUs while improving the sum rate of SUs. We herein propose an adaptive feedback bits allocation among multiple PUs and SUs where the quantized channel direction information (CDI) for the interference channel is forwarded to the ST in order to utilize the beamforming. Moreover, based on the cognitive beamforming, we adjust the transmit power of the ST under the constraint of the average interference at PUs. To jointly solve the feedback bits allocation and the transmit power control problems, we formulate an optimization problem which requires a little iterations compared with the separated feedback bits allocation and the transmit power control problems. Numerical results show that the proposed scheme significantly improves the sum rate of SUs while satisfying the average interference constraint at PUs.