ALBERT

Description / Table of Contents: Watershed Hydrology: Scientific Advances and Environmental Assessments / Water 2018, 10(3), 288; https://doi.org/10.3390/w10030288 --- Debris Flow Susceptibility Assessment in the Wudongde Dam Area, China Based on Rock Engineering System and Fuzzy C-Means Algorithm / Water 2017, 9(9), 669; https://doi.org/10.3390/w9090669 --- Evaluating the Effects of Low Impact Development Practices on Urban Flooding under Different Rainfall Intensities / Water 2017, 9(7), 548; https://doi.org/10.3390/w9070548 --- Flooding in Delta Areas under Changing Climate: Response of Design Flood Level to Non-Stationarity in Both Inflow Floods and High Tides in South China / Water 2017, 9(7), 471; https://doi.org/10.3390/w9070471 --- Variability of Spatially Grid-Distributed Precipitation over the Huaihe River Basin in China / Water 2017, 9(7), 489; https://doi.org/10.3390/w9070489 --- Estimation of Active Stream Network Length in a Hilly Headwater Catchment Using Recession Flow Analysis / Water 2017, 9(5), 348; https://doi.org/10.3390/w9050348 --- Hydrological Modeling of the Upper Indus Basin: A Case Study from a High-Altitude Glacierized Catchment Hunza / Water 2017, 9(1), 17; https://doi.org/10.3390/w9010017 --- Characterizing Changes in Streamflow and Sediment Supply in the Sacramento River Basin, California, Using Hydrological Simulation Program—FORTRAN (HSPF) / Water 2016, 8(10), 432; https://doi.org/10.3390/w8100432 --- Assessment of the Impact of Subsurface Agricultural Drainage on Soil Water Storage and Flows of a Small Watershed / Water 2016, 8(8), 326; https://doi.org/10.3390/w8080326 --- Effects of Model Spatial Resolution on Ecohydrologic Predictions and Their Sensitivity to Inter-Annual Climate Variability / Water 2016, 8(8), 321; https://doi.org/10.3390/w8080321 --- Hydrologic Alteration Associated with Dam Construction in a Medium-Sized Coastal Watershed of Southeast China / Water 2016, 8(8), 317; https://doi.org/10.3390/w8080317 --- Using High-Resolution Data to Test Parameter Sensitivity of the Distributed Hydrological Model HydroGeoSphere / Water 2016, 8(5), 202; https://doi.org/10.3390/w8050202 --- Multi-Site Validation of the SWAT Model on the Bani Catchment: Model Performance and Predictive Uncertainty / Water 2016, 8(5), 178; https://doi.org/10.3390/w8050178 --- An Eco-Hydrological Model-Based Assessment of the Impacts of Soil and Water Conservation Management in the Jinghe River Basin, China / Water 2015, 7(11), 6301-6320; https://doi.org/10.3390/w7116301

Description / Table of Contents: Preface: Morphology and Internal Mixing of Atmospheric Particles / Atmosphere 2018, 9(7), 249; https://doi.org/10.3390/atmos9070249 --- PDF Full-text (692 KB) | HTML Full-text | XML Full-text / Immersion Freezing of Total Ambient Aerosols and Ice Residuals / Atmosphere 2018, 9(2), 55; https://doi.org/10.3390/atmos9020055 --- Influence of Common Assumptions Regarding Aerosol Composition and Mixing State on Predicted CCN Concentration / Atmosphere 2018, 9(2), 54; https://doi.org/10.3390/atmos9020054 --- Physicochemical Characteristics of Individual Aerosol Particles during the 2015 China Victory Day Parade in Beijing / Atmosphere 2018, 9(2), 40; https://doi.org/10.3390/atmos9020040 --- Quantifying Impacts of Aerosol Mixing State on Nucleation-Scavenging of Black Carbon Aerosol Particles / Atmosphere 2018, 9(1), 17; https://doi.org/10.3390/atmos9010017 --- Machine Learning to Predict the Global Distribution of Aerosol Mixing State Metrics / Atmosphere 2018, 9(1), 15; https://doi.org/10.3390/atmos9010015 --- Elemental Mixing State of Aerosol Particles Collected in Central Amazonia during GoAmazon2014/15 / Atmosphere 2017, 8(9), 173; https://doi.org/10.3390/atmos8090173 --- Effect of Thermodenuding on the Structure of Nascent Flame Soot Aggregates / Atmosphere 2017, 8(9), 166; https://doi.org/10.3390/atmos8090166 --- The Impact of Sampling Medium and Environment on Particle Morphology / Atmosphere 2017, 8(9), 162; https://doi.org/10.3390/atmos8090162 --- Temperature-Dependent Diffusion of H2SO4 in Air at Atmospherically Relevant Conditions: Laboratory Measurements Using Laminar Flow Technique / Atmosphere 2017, 8(7), 132; https://doi.org/10.3390/atmos8070132 --- Monthly and Diurnal Variation of the Concentrations of Aerosol Surface Area in Fukuoka, Japan, Measured by Diffusion Charging Method / Atmosphere 2017, 8(7), 114; https://doi.org/10.3390/atmos8070114 --- Q-Space Analysis of the Light Scattering Phase Function of Particles with Any Shape / Atmosphere 2017, 8(4), 68; https://doi.org/10.3390/atmos8040068 --- Morphology, Composition, and Mixing State of Individual Aerosol Particles in Northeast China during Wintertime / Atmosphere 2017, 8(3), 47; https://doi.org/10.3390/atmos8030047

Description / Table of Contents: Forecasting is a vital tool for local health and air quality managers to make informed short-term decisions on remedial and mitigation measures to reduce exposure risks for their residents. Forecasting tools enable them to issue air quality advisories to curb pollution by limiting vehicular traffic by encouraging car-pooling and offering free public transportation. Air quality monitoring from the perspective of air managers serves a dual purpose of evaluating the skill of their forecasting tools and deriving long-term trends of major air pollutants that impact their constituents. Epidemiologists also use long term monitored data to understand air pollution related diseases and mortality rates to support public health policy decisions. This Special Issue reinforces the importance of these tools by leveraging their collective strengths. Public health is under a constant threat by air pollution across the world in various degrees and manifestations. In some countries with rapid economic growth the abrupt increased occurrences of poor air quality over cities and their downwind regions are attracting worldwide attention. The adverse health effects suffered by the public are reflected in billions of dollars in lost productivity, hospital admissions due to contraction and exacerbation of respiratory, asthmatic and cardiovascular diseases, and increases in mortality rates. This is especially true in rapidly developing countries. On the other hand, many cities in developed countries are seeing changes in their atmospheric chemical regimes from nitrogen oxide (NOx) saturated regimes towards NOx limiting regimes. Furthermore, ozone and ozone precursors transported from areas upwind become important source of “background ozone” as local generation of ozone plays a lesser role due to reduced NOx emissions in the developed countries. It is now clear that air pollution is a global problem and that air quality monitoring, forecasting and mitigation should be a local effort conducted in concert with global partners.

Description / Table of Contents: The goal of this Special Issue of Geosciences is to gather high-quality original research articles and reviews on the use of Earth Observation (EO) data and technologies to image and monitor geohazards from space. Geohazards, such as landslides, volcanoes, earthquakes, tsunamis, ground subsidence and heave, pose significant risks to human life and property. Even when not with catastrophic consequences, or when characterised by relatively slow onset and evolution, these processes may be damaging over long time periods. Human interaction with the environment may also combine with natural processes, and thus trigger, induce acceleration or exacerbate the impacts of geohazards on built environment. With a wide spectrum of imaging capabilities—from optical to radar sensors, low to very high resolution, continental to local scale, single-image to multi-temporal approaches, yearly to sub-daily acquisition repeat cycles—nowadays, EO offers several opportunities for the geoscience community to map and monitor geohazards from space. Topics of interest of this Special Issue include, but are not limited to: development, validation and implementation of satellite EO data processing methods and applications for geohazards mapping and monitoring; radar interferometry (InSAR), object-based image analysis (OBIA), multi-spectral data analysis, feature extraction, time series analysis, photo-interpretation, and digital fieldwork.

Description / Table of Contents: Over the last few decades, artificial neural networks, such as in data mining and machine learning technology, are being successfully applied across a wide range of science and engineering areas. In addition, according to the development of computer and space technologies, geoinformatics, as science and technology dealing with spatial information, are growing rapidly. Thus, recently, artificial neural networks have been widely applied in geoinformatics and have produced valuable results in geoscience, environment, natural hazards, and natural resources areas. This Special Issue of the journal Applied Sciences, “Application of Artificial Neural Networks in Geoinformatics”, aims to attract novel contributions covering a wide range of applications in artificial neural networks in geoinformatics.

Description / Table of Contents: Taravat, A.; Rajaei, M.; Emadodin, I.; Hasheminejad, H.; Mousavian, R.; Biniyaz, E. A Spaceborne Multisensory, Multitemporal Approach to Monitor Water Level and Storage Variations of Lakes. Water 2016, 8(11), 478; https://doi.org/10.3390/w8110478 --- Paillou, P. Mapping Palaeohydrography in Deserts: Contribution from Space-Borne Imaging Radar. Water 2017, 9(3), 194; https://doi.org/10.3390/w9030194 --- Jiang, L.; Schneider, R.; Andersen, O.; Bauer-Gottwein, P. CryoSat-2 Altimetry Applications over Rivers and Lakes. Water 2017, 9(3), 211; https://doi.org/10.3390/w9030211 --- Polishchuk, Y.; Bogdanov, A.; Polishchuk, V.; Manasypov, R.; Shirokova, L.; Kirpotin, S.; Pokrovsky, O. Size Distribution, Surface Coverage, Water, Carbon, and Metal Storage of Thermokarst Lakes in the Permafrost Zone of the Western Siberia Lowland. Water 2017, 9(3), 228; https://doi.org/10.3390/w9030228 --- Salameh, E.; Frappart, F.; Papa, F.; Güntner, A.; Venugopal, V.; Getirana, A.; Prigent, C.; Aires, F.; Labat, D.; Laignel, B. Fifteen Years (1993–2007) of Surface Freshwater Storage Variability in the Ganges-Brahmaputra River Basin Using Multi-Satellite Observations. Water 2017, 9(4), 245; https://doi.org/10.3390/w9040245 --- Springer, A.; Eicker, A.; Bettge, A.; Kusche, J.; Hense, A. Evaluation of the Water Cycle in the European COSMO-REA6 Reanalysis Using GRACE. Water 2017, 9(4), 289; https://doi.org/10.3390/w9040289 --- Parrens, M.; Al Bitar, A.; Frappart, F.; Papa, F.; Calmant, S.; Crétaux, J.; Wigneron, J.; Kerr, Y. Mapping Dynamic Water Fraction under the Tropical Rain Forests of the Amazonian Basin from SMOS Brightness Temperatures. Water 2017, 9(5), 350; https://doi.org/10.3390/w9050350 --- Pham-Duc, B.; Prigent, C.; Aires, F. Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations. Water 2017, 9(6), 366; https://doi.org/10.3390/w9060366 --- Nielsen, K.; Stenseng, L.; Andersen, O.; Knudsen, P. The Performance and Potentials of the CryoSat-2 SAR and SARIn Modes for Lake Level Estimation. Water 2017, 9(6), 374; https://doi.org/10.3390/w9060374 --- Nguyen, D.; Wagner, W. European Rice Cropland Mapping with Sentinel-1 Data: The Mediterranean Region Case Study. Water 2017, 9(6), 392; https://doi.org/10.3390/w9060392 --- Ferrara, C.; Lega, M.; Fusco, G.; Bishop, P.; Endreny, T. Characterization of Terrestrial Discharges into Coastal Waters with Thermal Imagery from a Hierarchical Monitoring Program. Water 2017, 9(7), 500; https://doi.org/10.3390/w9070500 --- Shen, H.; Leblanc, M.; Frappart, F.; Seoane, L.; O’Grady, D.; Olioso, A.; Tweed, S. A Comparative Study of GRACE with Continental Evapotranspiration Estimates in Australian Semi-Arid and Arid Basins: Sensitivity to Climate Variability and Extremes. Water 2017, 9(9), 614; https://doi.org/10.3390/w9090614 --- Erazo, B.; Bourrel, L.; Frappart, F.; Chimborazo, O.; Labat, D.; Dominguez-Granda, L.; Matamoros, D.; Mejia, R. Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM) for Rainfall Variability over the Pacific Slope and Coast of Ecuador. Water 2018, 10(2), 213; https://doi.org/10.3390/w10020213

Description / Table of Contents: Kuwahara, Y.; Liu, W.; Makio, M.; Otsuka, K. In Situ AFM Study of Crystal Growth on a Barite (001) Surface in BaSO4 Solutions at 30 °C. Minerals 2016, 6(4), 117; https://doi.org/10.3390/min6040117 --- Evans, J. Polymorphs, Proteins, and Nucleation Theory: A Critical Analysis. Minerals 2017, 7(4), 62; https://doi.org/10.3390/min7040062 --- Ochiai, A.; Utsunomiya, S. Crystal Chemistry and Stability of Hydrated Rare-Earth Phosphates Formed at Room Temperature. Minerals 2017, 7(5), 84; https://doi.org/10.3390/min7050084 --- Jones, F. Crystallization of Jarosite with Variable Al3+ Content: The Transition to Alunite. Minerals 2017, 7(6), 90; https://doi.org/10.3390/min7060090 --- Bacsik, Z.; Zhang, P.; Hedin, N. Ammonium-Carbamate-Rich Organogels for the Preparation of Amorphous Calcium Carbonates. Minerals 2017, 7(7), 110; https://doi.org/10.3390/min7070110 --- Harris, J.; Wolf, S. Desiccator Volume: A Vital Yet Ignored Parameter in CaCO3 Crystallization by the Ammonium Carbonate Diffusion Method. Minerals 2017, 7(7), 122; https://doi.org/10.3390/min7070122 --- Burgos-Cara, A.; Putnis, C.; Rodriguez-Navarro, C.; Ruiz-Agudo, E. Hydration Effects on the Stability of Calcium Carbonate Pre-Nucleation Species. Minerals 2017, 7(7), 126; https://doi.org/10.3390/min7070126 --- Ross, J.; Gao, L.; Meouch, O.; Anthony, E.; Sutarwala, D.; Mamo, H.; Omelon, S. Carbonate Apatite Precipitation from Synthetic Municipal Wastewater. Minerals 2017, 7(8), 129; https://doi.org/10.3390/min7080129 --- Kezuka, Y.; Kawai, K.; Eguchi, K.; Tajika, M. Fabrication of Single-Crystalline Calcite Needle-Like Particles Using the Aragonite–Calcite Phase Transition. Minerals 2017, 7(8), 133; https://doi.org/10.3390/min7080133 --- Pastero, L.; Bruno, M.; Aquilano, D. About the Genetic Mechanisms of Apatites: A Survey on the Methodological Approaches. Minerals 2017, 7(8), 139; https://doi.org/10.3390/min7080139 --- Ossorio, M.; Stawski, T.; Rodríguez-Blanco, J.; Sleutel, M.; García-Ruiz, J.; Benning, L.; Van Driessche, A. Physicochemical and Additive Controls on the Multistep Precipitation Pathway of Gypsum. Minerals 2017, 7(8), 140; https://doi.org/10.3390/min7080140 --- Zeng, C.; Vitale-Sullivan, C.; Ma, X. In Situ Atomic Force Microscopy Studies on Nucleation and Self-Assembly of Biogenic and Bio-Inspired Materials. Minerals 2017, 7(9), 158; https://doi.org/10.3390/min7090158 --- Gruber, D.; Wolf, S.; Hoyt, A.; Konsek, J.; Cölfen, H. A Micro-Comb Test System for In Situ Investigation of Infiltration and Crystallization Processes. Minerals 2017, 7(10), 187; https://doi.org/10.3390/min7100187 --- Kröger, R.; Verch, A. Liquid Cell Transmission Electron Microscopy and the Impact of Confinement on the Precipitation from Supersaturated Solutions. Minerals 2018, 8(1), 21; https://doi.org/10.3390/min8010021 --- Ibsen, C.; Birkedal, H. Pyrophosphate-Inhibition of Apatite Formation Studied by In Situ X-Ray Diffraction. Minerals 2018, 8(2), 65; https://doi.org/10.3390/min8020065 --- Opel, J.; Kellermeier, M.; Sickinger, A.; Morales, J.; Cölfen, H.; García-Ruiz, J. Structural Transition of Inorganic Silica–Carbonate Composites Towards Curved Lifelike Morphologies. Minerals 2018, 8(2), 75; https://doi.org/10.3390/min8020075 --- Gebauer, D.; Jansson, K.; Oliveberg, M.; Hedin, N. Indications that Amorphous Calcium Carbonates Occur in Pathological Mineralisation—A Urinary Stone from a Guinea Pig. Minerals 2018, 8(3), 84; https://doi.org/10.3390/min8030084 --- Gebauer, D. Editorial for Special Issue “Nucleation of Minerals: Precursors, Intermediates and Their Use in Materials Chemistry”. Minerals 2018, 8(6), 239; https://doi.org/10.3390/min8060239

Description / Table of Contents: Perea-Moreno, A.; Aguilera-Ureña, M.; Meroño-De Larriva, J.; Manzano-Agugliaro, F. Assessment of the Potential of UAV Video Image Analysis for Planning Irrigation Needs of Golf Courses. Water 2016, 8(12), 584; https://doi.org/10.3390/w8120584 --- Frappart, F.; Bourrel, L.; Brodu, N.; Riofrío Salazar, X.; Baup, F.; Darrozes, J.; Pombosa, R. Monitoring of the Spatio-Temporal Dynamics of the Floods in the Guayas Watershed (Ecuadorian Pacific Coast) Using Global Monitoring ENVISAT ASAR Images and Rainfall Data. Water 2017, 9(1), 12; https://doi.org/10.3390/w9010012 --- Li, Y.; Gong, H.; Zhu, L.; Li, X. Measuring Spatiotemporal Features of Land Subsidence, Groundwater Drawdown, and Compressible Layer Thickness in Beijing Plain, China. Water 2017, 9(1), 64; https://doi.org/10.3390/w9010064 --- Yang, F.; Guo, J.; Tan, H.; Wang, J. Automated Extraction of Urban Water Bodies from ZY‐3 Multi‐Spectral Imagery. Water 2017, 9(2), 144; https://doi.org/10.3390/w9020144 --- Lee, J.; Choi, H. Improvements to Runoff Predictions from a Land Surface Model with a Lateral Flow Scheme Using Remote Sensing and In Situ Observations. Water 2017, 9(2), 148; https://doi.org/10.3390/w9020148 --- Sharif, H.; Al-Zahrani, M.; Hassan, A. Physically, Fully-Distributed Hydrologic Simulations Driven by GPM Satellite Rainfall over an Urbanizing Arid Catchment in Saudi Arabia. Water 2017, 9(3), 163; https://doi.org/10.3390/w9030163 --- Wang, X.; Chen, H.; Chen, Y. Large Differences between Glaciers 3D Surface Extents and 2D Planar Areas in Central Tianshan. Water 2017, 9(4), 282; https://doi.org/10.3390/w9040282 --- Wang, R.; Chen, J.; Wang, X. Comparison of IMERG Level-3 and TMPA 3B42V7 in Estimating Typhoon-Related Heavy Rain. Water 2017, 9(4), 276; https://doi.org/10.3390/w9040276 --- Pan, C.; Wang, X.; Liu, L.; Huang, H.; Wang, D. Improvement to the Huff Curve for Design Storms and Urban Flooding Simulations in Guangzhou, China. Water 2017, 9(6), 411; https://doi.org/10.3390/w9060411 --- Ouyang, H.; Shih, S.; Wu, C. Optimal Combinations of Non-Sequential Regressors for ARX-Based Typhoon Inundation Forecast Models Considering Multiple Objectives. Water 2017, 9(7), 519; https://doi.org/10.3390/w9070519 --- Lu, Y.; Song, W.; Lu, J.; Wang, X.; Tan, Y. An Examination of Soil Moisture Estimation Using Ground Penetrating Radar in Desert Steppe. Water 2017, 9(7), 521; https://doi.org/10.3390/w9070521 --- Tekeli, A. Exploring Jeddah Floods by Tropical Rainfall Measuring Mission Analysis. Water 2017, 9(8), 612; https://doi.org/10.3390/w9080612 --- Wang, X.; Xie, H. A Review on Applications of Remote Sensing and Geographic Information Systems (GIS) in Water Resources and Flood Risk Management. Water 2018, 10(5), 608; https://doi.org/10.3390/w10050608

Description / Table of Contents: Dostal, J. Rare Earth Element Deposits of Alkaline Igneous Rocks. Resources 2017, 6(3), 34; https://doi.org/10.3390/resources6030034 --- Catlos, E.; Miller, N. Speculations Linking Monazite Compositions to Origin: Llallagua Tin Ore Deposit (Bolivia). Resources 2017, 6(3), 36; https://doi.org/10.3390/resources6030036 --- Smith, Y.; Kumar, P.; McLennan, J. On the Extraction of Rare Earth Elements from Geothermal Brines. Resources 2017, 6(3), 39; https://doi.org/10.3390/resources6030039 --- McLeod, C.; Krekeler, M. Sources of Extraterrestrial Rare Earth Elements: To the Moon and Beyond. Resources 2017, 6(3), 40; https://doi.org/10.3390/resources6030040 --- Chen, W.; Honghui, H.; Bai, T.; Jiang, S. Geochemistry of Monazite within Carbonatite Related REE Deposits. Resources 2017, 6(4), 51; https://doi.org/10.3390/resources6040051 --- Machacek, E.; Richter, J.; Lane, R. Governance and Risk–Value Constructions in Closing Loops of Rare Earth Elements in Global Value Chains. Resources 2017, 6(4), 59; https://doi.org/10.3390/resources6040059 --- McLemore, V. Rare Earth Elements (REE) Deposits Associated with Great Plain Margin Deposits (Alkaline-Related), Southwestern United States and Eastern Mexico. Resources 2018, 7(1), 8; https://doi.org/10.3390/resources7010008 --- Jowitt, S. Introduction to a Resources Special Issue on Criticality of the Rare Earth Elements: Current and Future Sources and Recycling. Resources 2018, 7(2), 35; https://doi.org/10.3390/resources7020035

Description / Table of Contents: Remote Sensing and Geosciences for Archaeology / Geosciences 2018, 8(2), 41; https://doi.org/10.3390/geosciences8020041 --- Landscape Pattern Detection in Archaeological Remote Sensing / Geosciences 2017, 7(4), 128; https://doi.org/10.3390/geosciences7040128 --- Semi-Automatic Detection of Indigenous Settlement Features on Hispaniola through Remote Sensing Data / Geosciences 2017, 7(4), 127; https://doi.org/10.3390/geosciences7040127 --- SARchaeology—Detecting Palaeochannels Based on High Resolution Radar Data and Their Impact of Changes in the Settlement Pattern in Cilicia (Turkey) / Geosciences 2017, 7(4), 109; https://doi.org/10.3390/geosciences7040109 --- Detecting Landscape Disturbance at the Nasca Lines Using SAR Data Collected from Airborne and Satellite Platforms / Geosciences 2017, 7(4), 106; https://doi.org/10.3390/geosciences7040106 --- SAR Imaging of Archaeological Sites on Intertidal Flats in the German Wadden Sea / Geosciences 2017, 7(4), 105; https://doi.org/10.3390/geosciences7040105 --- Geoarchaeological Core Prospection as a Tool to Validate Archaeological Interpretation Based on Geophysical Data at the Roman Settlement of Auritz/Burguete and Aurizberri/Espinal (Navarre) / Geosciences 2017, 7(4), 104; https://doi.org/10.3390/geosciences7040104 --- Geometric Analysis on Stone Façades with Terrestrial Laser Scanner Technology / Geosciences 2017, 7(4), 103; https://doi.org/10.3390/geosciences7040103 --- From Above and on the Ground: Geospatial Methods for Recording Endangered Archaeology in the Middle East and North Africa / Geosciences 2017, 7(4), 100; https://doi.org/10.3390/geosciences7040100 --- Optical Remote Sensing Potentials for Looting Detection / Geosciences 2017, 7(4), 98; https://doi.org/10.3390/geosciences7040098 --- How Can Remote Sensing Help in Detecting the Threats to Archaeological Sites in Upper Egypt? / Geosciences 2017, 7(4), 97; https://doi.org/10.3390/geosciences7040097 --- 3D Point Clouds in Archaeology: Advances in Acquisition, Processing and Knowledge Integration Applied to Quasi-Planar Objects / Geosciences 2017, 7(4), 96; https://doi.org/10.3390/geosciences7040096 --- The American Schools of Oriental Research Cultural Heritage Initiatives: Monitoring Cultural Heritage in Syria and Northern Iraq by Geospatial Imagery / Geosciences 2017, 7(4), 95; https://doi.org/10.3390/geosciences7040095 --- Using Ontology-Based Photogrammetry Survey for Medieval Archaeology: Toward a 3D Geographic Information System (GIS) / Geosciences 2017, 7(4), 93; https://doi.org/10.3390/geosciences7040093 --- Accurate Reconstruction of the Roman Circus in Milan by Georeferencing Heterogeneous Data Sources with GIS / Geosciences 2017, 7(3), 91; https://doi.org/10.3390/geosciences7030091 --- Are We There Yet? A Review and Assessment of Archaeological Passive Airborne Optical Imaging Approaches in the Light of Landscape Archaeology / Geosciences 2017, 7(3), 86; https://doi.org/10.3390/geosciences7030086 --- Comparison Study to the Use of Geophysical Methods at Archaeological Sites Observed by Various Remote Sensing Techniques in the Czech Republic / Geosciences 2017, 7(3), 81; https://doi.org/10.3390/geosciences7030081 --- Analysis and Processing of Nadir and Stereo VHR Pleiadés Images for 3D Mapping and Planning the Land of Nineveh, Iraqi Kurdistan / Geosciences 2017, 7(3), 80; https://doi.org/10.3390/geosciences7030080 --- A Manifold Approach for the Investigation of Early and Middle Neolithic Settlements in Thessaly, Greece / Geosciences 2017, 7(3), 79; https://doi.org/10.3390/geosciences7030079 --- Fusion of Satellite Multispectral Images Based on Ground-Penetrating Radar (GPR) Data for the Investigation of Buried Concealed Archaeological Remains / Geosciences 2017, 7(2), 40; https://doi.org/10.3390/geosciences7020040 --- Quantitative Examination of Piezoelectric/Seismoelectric Anomalies from Near-Surface Targets / Geosciences 2017, 7(3), 90; https://doi.org/10.3390/geosciences7030090

Description / Table of Contents: Experimental Tests on a Dowel-Type Timber Connection and Validation of Numerical Models. Buildings 2017, 7(4), 116; https://doi.org/10.3390/buildings7040116 --- Multi-Directional Seismic Assessment of Historical Masonry Buildings by Means of Macro-Element Modelling: Application to a Building Damaged during the L’Aquila Earthquake (Italy). Buildings 2017, 7(4), 106; https://doi.org/10.3390/buildings7040106 --- Nonlinear Modelling of Curved Masonry Structures after Seismic Retrofit through FRP Reinforcing. Buildings 2017, 7(3), 79; https://doi.org/10.3390/buildings7030079 --- Assessment Method for Combined Structural and Energy Retrofitting in Masonry Buildings. Buildings 2017, 7(3), 71; https://doi.org/10.3390/buildings7030071 --- Rocking and Kinematic Approaches for Rigid Block Analysis of Masonry Walls: State of the Art and Recent Developments. Buildings 2017, 7(3), 69; https://doi.org/10.3390/buildings7030069 --- Effect of Material Variability and Mechanical Eccentricity on the Seismic Vulnerability Assessment of Reinforced Concrete Buildings. Buildings 2017, 7(3), 66; https://doi.org/10.3390/buildings7030066 --- Analysis of Cylindrical Granular Material Silos under Seismic Excitation. Buildings 2017, 7(3), 61; https://doi.org/10.3390/buildings7030061 --- Seismic Reinforcement of a R.C. School Structure with Strength Irregularities throughout External Bracing Walls. Buildings 2017, 7(3), 58; https://doi.org/10.3390/buildings7030058 --- The TVT Glass Pavilion: Theoretical Study on a Highly Transparent Building Made with Long-Spanned TVT Portals Braced with Hybrid Glass-Steel Panels. Buildings 2017, 7(2), 50; https://doi.org/10.3390/buildings7020050 --- Strengthening Masonry Arches with Lime-Based Mortar Composite. Buildings 2017, 7(2), 49; https://doi.org/10.3390/buildings7020049

Description / Table of Contents: Mechanisms of SAR Imaging of Shallow Water Topography of the Subei Bank / Remote Sens. 2017, 9(11), 1203; doi:10.3390/rs9111203 --- Detection of Bivalve Beds on Exposed Intertidal Flats Using Polarimetric SAR Indicators / Remote Sens. 2017, 9(10), 1047; doi:10.3390/rs9101047 --- Exploring the Potential of Active Learning for Automatic Identification of Marine Oil Spills Using 10-Year (2004–2013) RADARSAT Data / Remote Sens. 2017, 9(10), 1041; doi:10.3390/rs9101041 --- Assimilation of Typhoon Wind Field Retrieved from Scatterometer and SAR Based on the Huber Norm Quality Control / Remote Sens. 2017, 9(10), 987; doi:10.3390/rs9100987 --- Performance Analysis of Ocean Surface Topography Altimetry by Ku-Band Near-Nadir Interferometric SAR / Remote Sens. 2017, 9(9), 933; doi:10.3390/rs9090933 --- Satellite Survey of Internal Waves in the Black and Caspian Seas / Remote Sens. 2017, 9(9), 892; doi:10.3390/rs9090892 --- Contextual Region-Based Convolutional Neural Network with Multilayer Fusion for SAR Ship Detection / Remote Sens. 2017, 9(8), 860; doi:10.3390/rs9080860 --- Refocusing of Moving Targets in SAR Images via Parametric Sparse Representation / Remote Sens. 2017, 9(8), 795; doi:10.3390/rs9080795 --- Modulation Model of High Frequency Band Radar Backscatter by the Internal Wave Based on the Third-Order Statistics / Remote Sens. 2017, 9(5), 501; doi:10.3390/rs9050501 --- Ku-Band Sea Surface Radar Backscatter at Low Incidence Angles under Extreme Wind Conditions / Remote Sens. 2017, 9(5), 474; doi:10.3390/rs9050474 --- Doppler Spectrum-Based NRCS Estimation Method for Low-Scattering Areas in Ocean SAR Images / Remote Sens. 2017, 9(3), 219; doi:10.3390/rs9030219 --- An Improved Shape Contexts Based Ship Classification in SAR Images / Remote Sens. 2017, 9(2), 145; doi:10.3390/rs9020145 --- GF-3 SAR Ocean Wind Retrieval: The First View and Preliminary Assessment / Remote Sens. 2017, 9(7), 694; doi:10.3390/rs9070694

Description / Table of Contents: Estimating River Depth from SWOT-Type Observables Obtained by Satellite Altimetry and Imagery / Water 2017, 9(10), 753; https://doi.org/10.3390/w9100753 --- Local- and Plot-Scale Measurements of Soil Moisture: Time and Spatially Resolved Field Techniques in Plain, Hill and Mountain Sites / Water 2017, 9(9), 706; https://doi.org/10.3390/w9090706 --- Snow Precipitation Measured by Gauges: Systematic Error Estimation and Data Series Correction in the Central Italian Alps / Water 2017, 9(7), 461; https://doi.org/10.3390/w9070461 --- Discharge Measurements of Snowmelt Flood by Space-Time Image Velocimetry during the Night Using Far-Infrared Camera / Water 2017, 9(4), 269; https://doi.org/10.3390/w9040269 --- Soil Moisture for Hydrological Applications: Open Questions and New Opportunities / Water 2017, 9(2), 140; https://doi.org/10.3390/w9020140 --- From Surface Flow Velocity Measurements to Discharge Assessment by the Entropy Theory / Water 2017, 9(2), 120; https://doi.org/10.3390/w9020120 --- Space–Time Characterization of Rainfall Field in Tuscany / Water 2017, 9(2), 86; https://doi.org/10.3390/w9020086 --- An Integrated Approach for Site Selection of Snow Measurement Stations / Water 2016, 8(11), 539; https://doi.org/10.3390/w8110539 --- Rainfall Characteristics and Regionalization in Peninsular Malaysia Based on a High Resolution Gridded Data Set / Water 2016, 8(11), 500; https://doi.org/10.3390/w8110500 --- Spatial Patterns and Influence Factors of Conversion Coefficients between Two Typical Pan Evaporimeters in China / Water 2016, 8(10), 422; https://doi.org/10.3390/w8100422 --- Daily Precipitation Changes over Large River Basins in China, 1960–2013 / Water 2016, 8(5), 185; https://doi.org/10.3390/w8050185

Description / Table of Contents: Editorial - Remote Sensing and Geospatial Technologies in Public Health / ISPRS Int. J. Geo-Inf. 2018, 7(8), 303; https://doi.org/10.3390/ijgi7080303 --- CALPUFF and CAFOs: Air Pollution Modeling and Environmental Justice Analysis in the North Carolina Hog Industry / ISPRS Int. J. Geo-Inf. 2015, 4(1), 150-171; https://doi.org/10.3390/ijgi4010150 --- Analyzing the Correlation between Deer Habitat and the Component of the Risk for Lyme Disease in Eastern Ontario, Canada: A GIS-Based Approach / ISPRS Int. J. Geo-Inf. 2015, 4(1), 105-123; https://doi.org/10.3390/ijgi4010105 --- Geospatial Technology: A Tool to Aid in the Elimination of Malaria in Bangladesh / ISPRS Int. J. Geo-Inf. 2015, 4(1), 47-58; https://doi.org/10.3390/ijgi4010047 --- Examining Personal Air Pollution Exposure, Intake, and Health Danger Zone Using Time Geography and 3D Geovisualization / ISPRS Int. J. Geo-Inf. 2015, 4(1), 32-46; https://doi.org/10.3390/ijgi4010032 --- Use of the NASA Giovanni Data System for Geospatial Public Health Research: Example of Weather-Influenza Connection / ISPRS Int. J. Geo-Inf. 2014, 3(4), 1372-1386; https://doi.org/10.3390/ijgi3041372 --- Mapping Entomological Dengue Risk Levels in Martinique Using High-Resolution Remote-Sensing Environmental Data / ISPRS Int. J. Geo-Inf. 2014, 3(4), 1352-1371; https://doi.org/10.3390/ijgi3041352 --- Improving Inland Water Quality Monitoring through Remote Sensing Techniques / ISPRS Int. J. Geo-Inf. 2014, 3(4), 1234-1255; https://doi.org/10.3390/ijgi3041234 --- Impacts of Scale on Geographic Analysis of Health Data: An Example of Obesity Prevalence / ISPRS Int. J. Geo-Inf. 2014, 3(4), 1198-1210; https://doi.org/10.3390/ijgi3041198 --- Geographical Variation of Incidence of Chronic Obstructive Pulmonary Disease in Manitoba, Canada / ISPRS Int. J. Geo-Inf. 2014, 3(3), 1039-1057; https://doi.org/10.3390/ijgi3031039 --- Holistics 3.0 for Health / ISPRS Int. J. Geo-Inf. 2014, 3(3), 1023-1038; https://doi.org/10.3390/ijgi3031023 --- Dasymetric Mapping and Spatial Modeling of Mosquito Vector Exposure, Chesapeake, Virginia, USA / ISPRS Int. J. Geo-Inf. 2014, 3(3), 891-913; https://doi.org/10.3390/ijgi3030891 --- Modeling Properties of Influenza-Like Illness Peak Events with Crossing Theory / ISPRS Int. J. Geo-Inf. 2014, 3(2), 764-780; https://doi.org/10.3390/ijgi3020764 --- Correlating Remote Sensing Data with the Abundance of Pupae of the Dengue Virus Mosquito Vector, Aedes aegypti, in Central Mexico / ISPRS Int. J. Geo-Inf. 2014, 3(2), 732-749; https://doi.org/10.3390/ijgi3020732 --- Canadian Forest Fires and the Effects of Long-Range Transboundary Air Pollution on Hospitalizations among the Elderly / ISPRS Int. J. Geo-Inf. 2014, 3(2), 713-731; https://doi.org/10.3390/ijgi3020713 --- Nexus of Health and Development: Modelling Crude Birth Rate and Maternal Mortality Ratio Using Nighttime Satellite Images / ISPRS Int. J. Geo-Inf. 2014, 3(2), 693-712; https://doi.org/10.3390/ijgi3020693

Description / Table of Contents: Belle, J.; Liu, Y. Evaluation of Aqua MODIS Collection 6 AOD Parameters for Air Quality Research over the Continental United States. Remote Sens. 2016, 8(10), 815; doi:10.3390/rs8100815. http://www.mdpi.com/2072-4292/8/10/815 --- Sun, K.; Chen, X.; Zhu, Z.; Zhang, T. High Resolution Aerosol Optical Depth Retrieval Using Gaofen-1 WFV Camera Data. Remote Sens. 2017, 9(1), 89; doi:10.3390/rs9010089. http://www.mdpi.com/2072-4292/9/1/89 --- Chen, X.; Yang, D.; Cai, Z.; Liu, Y.; Spurr, R. Aerosol Retrieval Sensitivity and Error Analysis for the Cloud and Aerosol Polarimetric Imager on Board TanSat: The Effect of Multi-Angle Measurement. Remote Sens. 2017, 9(2), 183; doi:10.3390/rs9020183. http://www.mdpi.com/2072-4292/9/2/183 --- Jiang, M.; Sun, W.; Yang, G.; Zhang, D. Modelling Seasonal GWR of Daily PM2.5 with Proper Auxiliary Variables for the Yangtze River Delta. Remote Sens. 2017, 9(4), 346; doi:10.3390/rs9040346. http://www.mdpi.com/2072-4292/9/4/346 --- Wang, Y.; Chen, L.; Li, S.; Wang, X.; Yu, C.; Si, Y.; Zhang, Z. Interference of Heavy Aerosol Loading on the VIIRS Aerosol Optical Depth (AOD) Retrieval Algorithm. Remote Sens. 2017, 9(4), 397; doi:10.3390/rs9040397. http://www.mdpi.com/2072-4292/9/4/397 --- Wang, W.; Mao, F.; Pan, Z.; Du, L.; Gong, W. Validation of VIIRS AOD through a Comparison with a Sun Photometer and MODIS AODs over Wuhan. Remote Sens. 2017, 9(5), 403; doi:10.3390/rs9050403. http://www.mdpi.com/2072-4292/9/5/403 --- Zhu, J.; Xia, X.; Wang, J.; Che, H.; Chen, H.; Zhang, J.; Xu, X.; Levy, R.; Oo, M.; Holz, R.; Ayoub, M. Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain. Remote Sens. 2017, 9(5), 432; doi:10.3390/rs9050432. http://www.mdpi.com/2072-4292/9/5/432 --- Dolgii, S.; Nevzorov, A.; Nevzorov, A.; Romanovskii, O.; Kharchenko, O. Intercomparison of Ozone Vertical Profile Measurements by Differential Absorption Lidar and IASI/MetOp Satellite in the Upper Troposphere–Lower Stratosphere. Remote Sens. 2017, 9(5), 447; doi:10.3390/rs9050447. http://www.mdpi.com/2072-4292/9/5/447 --- Liu, L.; Zhang, X.; Xu, W.; Liu, X.; Lu, X.; Wang, S.; Zhang, W.; Zhao, L. Ground Ammonia Concentrations over China Derived from Satellite and Atmospheric Transport Modeling. Remote Sens. 2017, 9(5), 467; doi:10.3390/rs9050467. http://www.mdpi.com/2072-4292/9/5/467 --- Chen, W.; Fan, A.; Yan, L. Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing. Remote Sens. 2017, 9(5), 496; doi:10.3390/rs9050496. http://www.mdpi.com/2072-4292/9/5/496 --- Osorio, M.; Casaballe, N.; Belsterli, G.; Barreto, M.; Gómez, Á.; Ferrari, J.; Frins, E. Plume Segmentation from UV Camera Images for SO2 Emission Rate Quantification on Cloud Days. Remote Sens. 2017, 9(6), 517; doi:10.3390/rs9060517. http://www.mdpi.com/2072-4292/9/6/517 --- Gu, J.; Chen, L.; Yu, C.; Li, S.; Tao, J.; Fan, M.; Xiong, X.; Wang, Z.; Shang, H.; Su, L. Ground-Level NO2 Concentrations over China Inferred from the Satellite OMI and CMAQ Model Simulations. Remote Sens. 2017, 9(6), 519; doi:10.3390/rs9060519. http://www.mdpi.com/2072-4292/9/6/519 --- Wang, Y.; Wang, J.; Levy, R.; Xu, X.; Reid, J. MODIS Retrieval of Aerosol Optical Depth over Turbid Coastal Water. Remote Sens. 2017, 9(6), 595; doi:10.3390/rs9060595. http://www.mdpi.com/2072-4292/9/6/595 --- Kim, D.; Lee, H.; Hong, H.; Choi, W.; Lee, Y.; Park, J. Estimation of Surface NO2 Volume Mixing Ratio in Four Metropolitan Cities in Korea Using Multiple Regression Models with OMI and AIRS Data. Remote Sens. 2017, 9(6), 627; doi:10.3390/rs9060627. http://www.mdpi.com/2072-4292/9/6/627 --- Qu, Y.; Han, Y.; Wu, Y.; Gao, P.; Wang, T. Study of PBLH and Its Correlation with Particulate Matter from One-Year Observation over Nanjing, Southeast China. Remote Sens. 2017, 9(7), 668; doi:10.3390/rs9070668. http://www.mdpi.com/2072-4292/9/7/668 --- Tosca, M.; Campbell, J.; Garay, M.; Lolli, S.; Seidel, F.; Marquis, J.; Kalashnikova, O. Attributing Accelerated Summertime Warming in the Southeast United States to Recent Reductions in Aerosol Burden: Indications from Vertically-Resolved Observations. Remote Sens. 2017, 9(7), 674; doi:10.3390/rs9070674. http://www.mdpi.com/2072-4292/9/7/674 --- Tao, M.; Wang, Z.; Tao, J.; Chen, L.; Wang, J.; Hou, C.; Wang, L.; Xu, X.; Zhu, H. How Do Aerosol Properties Affect the Temporal Variation of MODIS AOD Bias in Eastern China?. Remote Sens. 2017, 9(8), 800; doi:10.3390/rs9080800. http://www.mdpi.com/2072-4292/9/8/800 --- Wang, W.; Mao, F.; Du, L.; Pan, Z.; Gong, W.; Fang, S. Deriving Hourly PM2.5 Concentrations from Himawari-8 AODs over Beijing–Tianjin–Hebei in China. Remote Sens. 2017, 9(8), 858; doi:10.3390/rs9080858. http://www.mdpi.com/2072-4292/9/8/858 --- Yuchechen, A.; Lakkis, S.; Canziani, P. Linear and Non-Linear Trends for Seasonal NO2 and SO2 Concentrations in the Southern Hemisphere (2004−2016). Remote Sens. 2017, 9(9), 891; doi:10.3390/rs9090891. http://www.mdpi.com/2072-4292/9/9/891 --- Qin, K.; Rao, L.; Xu, J.; Bai, Y.; Zou, J.; Hao, N.; Li, S.; Yu, C. Estimating Ground Level NO2 Concentrations over Central-Eastern China Using a Satellite-Based Geographically and Temporally Weighted Regression Model. Remote Sens. 2017, 9(9), 950; doi:10.3390/rs9090950. http://www.mdpi.com/2072-4292/9/9/950

Description / Table of Contents: Chen, K.; Zamora, N.; Babeyko, A.; Li, X.; Ge, M. Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea. Remote Sensing 2015, 7(12), 15955-15968; doi:10.3390/rs71215814 --- Cianflone, G.; Tolomei, C.; Brunori, C.; Dominici, R. InSAR Time Series Analysis of Natural and Anthropogenic Coastal Plain Subsidence: The Case of Sibari (Southern Italy). Remote Sensing 2015, 7(12), 16004-16023; doi:10.3390/rs71215812 --- Kropáček, J.; Vařilová, Z.; Baroň, I.; Bhattacharya, A.; Eberle, J.; Hochschild, V. Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment. Remote Sensing 2015, 7(12), 16183-16203; doi:10.3390/rs71215821 --- Pacheco-Martínez, J.; Cabral-Cano, E.; Wdowinski, S.; Hernández-Marín, M.; Ortiz-Lozano, J.; Zermeño-de-León, M. Application of InSAR and Gravimetry for Land Subsidence Hazard Zoning in Aguascalientes, Mexico. Remote Sensing 2015, 7(12), 17035-17050; doi:10.3390/rs71215868 --- Al-Rawabdeh, A.; He, F.; Moussa, A.; El-Sheimy, N.; Habib, A. Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition. Remote Sensing 2016, 8(2), 95; doi:10.3390/rs8020095 --- Zhai, W.; Shen, H.; Huang, C.; Pei, W. Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image. Remote Sensing 2016, 8(3), 171; doi:10.3390/rs8030171 --- Jiang, Y.; Liao, M.; Zhou, Z.; Shi, X.; Zhang, L.; Balz, T. Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation. Remote Sensing 2016, 8(3), 179; doi:10.3390/rs8030179 --- He, M.; Zhu, Q.; Du, Z.; Hu, H.; Ding, Y.; Chen, M. A 3D Shape Descriptor Based on Contour Clusters for Damaged Roof Detection Using Airborne LiDAR Point Clouds. Remote Sensing 2016, 8(3), 189; doi:10.3390/rs8030189 --- Hu, J.; Wang, Q.; Li, Z.; Zhao, R.; Sun, Q. Investigating the Ground Deformation and Source Model of the Yangbajing Geothermal Field in Tibet, China with the WLS InSAR Technique. Remote Sensing 2016, 8(3), 191; doi:10.3390/rs8030191 --- Hsieh, Y.; Chan, Y.; Hu, J. Digital Elevation Model Differencing and Error Estimation from Multiple Sources: A Case Study from the Meiyuan Shan Landslide in Taiwan. Remote Sensing 2016, 8(3), 199; doi:10.3390/rs8030199 --- Zhu, S.; Xu, C.; Wen, Y.; Liu, Y. Interseismic Deformation of the Altyn Tagh Fault Determined by Interferometric Synthetic Aperture Radar (InSAR) Measurements. Remote Sensing 2016, 8(3), 233; doi:10.3390/rs8030233 --- Vetrivel, A.; Gerke, M.; Kerle, N.; Vosselman, G. Identification of Structurally Damaged Areas in Airborne Oblique Images Using a Visual-Bag-of-Words Approach. Remote Sensing 2016, 8(3), 231; doi:10.3390/rs8030231 --- Bardi, F.; Raspini, F.; Ciampalini, A.; Kristensen, L.; Rouyet, L.; Lauknes, T.; Frauenfelder, R.; Casagli, N. Space-Borne and Ground-Based InSAR Data Integration: The Åknes Test Site. Remote Sensing 2016, 8(3), 237; doi:10.3390/rs8030237 --- Liu, P.; Li, Q.; Li, Z.; Hoey, T.; Liu, G.; Wang, C.; Hu, Z.; Zhou, Z.; Singleton, A. Anatomy of Subsidence in Tianjin from Time Series InSAR. Remote Sensing 2016, 8(3), 266; doi:10.3390/rs8030266 --- Ma, Y.; Chen, F.; Liu, J.; He, Y.; Duan, J.; Li, X. An Automatic Procedure for Early Disaster Change Mapping Based on Optical Remote Sensing. Remote Sensing 2016, 8(4), 272; doi:10.3390/rs8040272 --- Yang, C.; Zhang, Q.; Xu, Q.; Zhao, C.; Peng, J.; Ji, L. Complex Deformation Monitoring over the Linfen–Yuncheng Basin (China) with Time Series InSAR Technology. Remote Sensing 2016, 8(4), 284; doi:10.3390/rs8040284 --- Watanabe, M.; Thapa, R.; Shimada, M. Pi-SAR-L2 Observation of the Landslide Caused by Typhoon Wipha on Izu Oshima Island. Remote Sensing 2016, 8(4), 282; doi:10.3390/rs8040282 --- Plank, S.; Twele, A.; Martinis, S. Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data. Remote Sensing 2016, 8(4), 307; doi:10.3390/rs8040307 --- Solaro, G.; De Novellis, V.; Castaldo, R.; De Luca, C.; Lanari, R.; Manunta, M.; Casu, F. Coseismic Fault Model of Mw 8.3 2015 Illapel Earthquake (Chile) Retrieved from Multi-Orbit Sentinel1-A DInSAR Measurements. Remote Sensing 2016, 8(4), 323; doi:10.3390/rs8040323 --- Bai, L.; Jiang, L.; Wang, H.; Sun, Q. Spatiotemporal Characterization of Land Subsidence and Uplift (2009–2010) over Wuhan in Central China Revealed by TerraSAR-X InSAR Analysis. Remote Sensing 2016, 8(4), 350; doi:10.3390/rs8040350 --- Xu, B.; Li, Z.; Feng, G.; Zhang, Z.; Wang, Q.; Hu, J.; Chen, X. Continent-Wide 2-D Co-Seismic Deformation of the 2015 Mw 8.3 Illapel, Chile Earthquake Derived from Sentinel-1A Data: Correction of Azimuth Co-Registration Error. Remote Sensing 2016, 8(5), 376; doi:10.3390/rs8050376 --- Chen, M.; Tomás, R.; Li, Z.; Motagh, M.; Li, T.; Hu, L.; Gong, H.; Li, X.; Yu, J.; Gong, X. Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry. Remote Sensing 2016, 8(6), 468; doi:10.3390/rs8060468 --- Ji, L.; Xu, J.; Zhao, Q.; Yang, C. Source Parameters of the 2003–2004 Bange Earthquake Sequence, Central Tibet, China, Estimated from InSAR Data. Remote Sensing 2016, 8(6), 516; doi:10.3390/rs8060516 --- Li, Y.; Jiang, W.; Zhang, J.; Luo, Y. Space Geodetic Observations and Modeling of 2016 Mw 5.9 Menyuan Earthquake: Implications on Seismogenic Tectonic Motion. Remote Sensing 2016, 8(6), 519; doi:10.3390/rs8060519 --- Trasatti, E.; Tolomei, C.; Pezzo, G.; Atzori, S.; Salvi, S. Deformation and Related Slip Due to the 2011 Van Earthquake (Turkey) Sequence Imaged by SAR Data and Numerical Modeling. Remote Sensing 2016, 8(6), 532; doi:10.3390/rs8060532 --- Wang, C.; Mao, X.; Wang, Q. Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method. Remote Sensing 2016, 8(8), 624; doi:10.3390/rs8080624 --- Liu, Y.; Xu, C.; Li, Z.; Wen, Y.; Chen, J.; Li, Z. Time-Dependent Afterslip of the 2009 Mw 6.3 Dachaidan Earthquake (China) and Viscosity beneath the Qaidam Basin Inferred from Postseismic Deformation Observations. Remote Sensing 2016, 8(8), 649; doi:10.3390/rs8080649 --- Xu, B.; Feng, G.; Li, Z.; Wang, Q.; Wang, C.; Xie, R. Coastal Subsidence Monitoring Associated with Land Reclamation Using the Point Target Based SBAS-InSAR Method: A Case Study of Shenzhen, China. Remote Sensing 2016, 8(8), 652; doi:10.3390/rs8080652 --- Sun, L.; Muller, J. Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas. Remote Sensing 2016, 8(8), 659; doi:10.3390/rs8080659 --- De Novellis, V.; Castaldo, R.; Lollino, P.; Manunta, M.; Tizzani, P. Advanced Three-Dimensional Finite Element Modeling of a Slow Landslide through the Exploitation of DInSAR Measurements and in Situ Surveys. Remote Sensing 2016, 8(8), 670; doi:10.3390/rs8080670 --- Zhang, Y.; Wu, H.; Kang, Y.; Zhu, C. Ground Subsidence in the Beijing-Tianjin-Hebei Region from 1992 to 2014 Revealed by Multiple SAR Stacks. Remote Sensing 2016, 8(8), 675; doi:10.3390/rs8080675 --- Zhou, G.; Yue, T.; Shi, Y.; Zhang, R.; Huang, J. Second-Order Polynomial Equation-Based Block Adjustment for Orthorectification of DISP Imagery. Remote Sensing 2016, 8(8), 680; doi:10.3390/rs8080680 --- Bonì, R.; Pilla, G.; Meisina, C. Methodology for Detection and Interpretation of Ground Motion Areas with the A-DInSAR Time Series Analysis. Remote Sensing 2016, 8(8), 686; doi:10.3390/rs8080686 --- Xie, S.; Duan, J.; Liu, S.; Dai, Q.; Liu, W.; Ma, Y.; Guo, R.; Ma, C. Crowdsourcing Rapid Assessment of Collapsed Buildings Early after the Earthquake Based on Aerial Remote Sensing Image: A Case Study of Yushu Earthquake. Remote Sensing 2016, 8(9), 759; doi:10.3390/rs8090759 --- Fernández, T.; Pérez, J.; Cardenal, J.; Gómez, J.; Colomo, C.; Delgado, J. Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques. Remote Sensing 2016, 8(10), 837; doi:10.3390/rs8100837 --- Cignetti, M.; Manconi, A.; Manunta, M.; Giordan, D.; De Luca, C.; Allasia, P.; Ardizzone, F. Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy. Remote Sensing 2016, 8(10), 852; doi:10.3390/rs8100852 --- Cooner, A.; Shao, Y.; Campbell, J. Detection of Urban Damage Using Remote Sensing and Machine Learning Algorithms: Revisiting the 2010 Haiti Earthquake. Remote Sensing 2016, 8(10), 868; doi:10.3390/rs8100868 --- Zhou, W.; Li, S.; Zhou, Z.; Chang, X. InSAR Observation and Numerical Modeling of the Earth-Dam Displacement of Shuibuya Dam (China). Remote Sensing 2016, 8(10), 877; doi:10.3390/rs8100877 --- Qu, T.; Lu, P.; Liu, C.; Wu, H.; Shao, X.; Wan, H.; Li, N.; Li, R. Hybrid-SAR Technique: Joint Analysis Using Phase-Based and Amplitude-Based Methods for the Xishancun Giant Landslide Monitoring. Remote Sensing 2016, 8(10), 874; doi:10.3390/rs8100874 --- Gong, L.; Wang, C.; Wu, F.; Zhang, J.; Zhang, H.; Li, Q. Earthquake-Induced Building Damage Detection with Post-Event Sub-Meter VHR TerraSAR-X Staring Spotlight Imagery. Remote Sensing 2016, 8(11), 887; doi:10.3390/rs8110887 --- Ding, C.; Feng, G.; Li, Z.; Shan, X.; Du, Y.; Wang, H. Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements. Remote Sensing 2016, 8(11), 937; doi:10.3390/rs8110937 --- Ma, C.; Cheng, X.; Yang, Y.; Zhang, X.; Guo, Z.; Zou, Y. Investigation on Mining Subsidence Based on Multi-Temporal InSAR and Time-Series Analysis of the Small Baseline Subset—Case Study of Working Faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield, China. Remote Sensing 2016, 8(11), 951; doi:10.3390/rs8110951 --- Caló, F.; Notti, D.; Galve, J.; Abdikan, S.; Görüm, T.; Pepe, A.; Balik Şanli, F. DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey. Remote Sensing 2017, 9(1), 83; doi:10.3390/rs9010083 --- Tomás, R.; Li, Z. Earth Observations for Geohazards: Present and Future Challenges. Remote Sensing 2017, 9(3), 194; doi:10.3390/rs9030194

Description / Table of Contents: Chen, K.; Zamora, N.; Babeyko, A.; Li, X.; Ge, M. Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea. Remote Sensing 2015, 7(12), 15955-15968; doi:10.3390/rs71215814 --- Cianflone, G.; Tolomei, C.; Brunori, C.; Dominici, R. InSAR Time Series Analysis of Natural and Anthropogenic Coastal Plain Subsidence: The Case of Sibari (Southern Italy). Remote Sensing 2015, 7(12), 16004-16023; doi:10.3390/rs71215812 --- Kropáček, J.; Vařilová, Z.; Baroň, I.; Bhattacharya, A.; Eberle, J.; Hochschild, V. Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment. Remote Sensing 2015, 7(12), 16183-16203; doi:10.3390/rs71215821 --- Pacheco-Martínez, J.; Cabral-Cano, E.; Wdowinski, S.; Hernández-Marín, M.; Ortiz-Lozano, J.; Zermeño-de-León, M. Application of InSAR and Gravimetry for Land Subsidence Hazard Zoning in Aguascalientes, Mexico. Remote Sensing 2015, 7(12), 17035-17050; doi:10.3390/rs71215868 --- Al-Rawabdeh, A.; He, F.; Moussa, A.; El-Sheimy, N.; Habib, A. Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition. Remote Sensing 2016, 8(2), 95; doi:10.3390/rs8020095 --- Zhai, W.; Shen, H.; Huang, C.; Pei, W. Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image. Remote Sensing 2016, 8(3), 171; doi:10.3390/rs8030171 --- Jiang, Y.; Liao, M.; Zhou, Z.; Shi, X.; Zhang, L.; Balz, T. Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation. Remote Sensing 2016, 8(3), 179; doi:10.3390/rs8030179 --- He, M.; Zhu, Q.; Du, Z.; Hu, H.; Ding, Y.; Chen, M. A 3D Shape Descriptor Based on Contour Clusters for Damaged Roof Detection Using Airborne LiDAR Point Clouds. Remote Sensing 2016, 8(3), 189; doi:10.3390/rs8030189 --- Hu, J.; Wang, Q.; Li, Z.; Zhao, R.; Sun, Q. Investigating the Ground Deformation and Source Model of the Yangbajing Geothermal Field in Tibet, China with the WLS InSAR Technique. Remote Sensing 2016, 8(3), 191; doi:10.3390/rs8030191 --- Hsieh, Y.; Chan, Y.; Hu, J. Digital Elevation Model Differencing and Error Estimation from Multiple Sources: A Case Study from the Meiyuan Shan Landslide in Taiwan. Remote Sensing 2016, 8(3), 199; doi:10.3390/rs8030199 --- Zhu, S.; Xu, C.; Wen, Y.; Liu, Y. Interseismic Deformation of the Altyn Tagh Fault Determined by Interferometric Synthetic Aperture Radar (InSAR) Measurements. Remote Sensing 2016, 8(3), 233; doi:10.3390/rs8030233 --- Vetrivel, A.; Gerke, M.; Kerle, N.; Vosselman, G. Identification of Structurally Damaged Areas in Airborne Oblique Images Using a Visual-Bag-of-Words Approach. Remote Sensing 2016, 8(3), 231; doi:10.3390/rs8030231 --- Bardi, F.; Raspini, F.; Ciampalini, A.; Kristensen, L.; Rouyet, L.; Lauknes, T.; Frauenfelder, R.; Casagli, N. Space-Borne and Ground-Based InSAR Data Integration: The Åknes Test Site. Remote Sensing 2016, 8(3), 237; doi:10.3390/rs8030237 --- Liu, P.; Li, Q.; Li, Z.; Hoey, T.; Liu, G.; Wang, C.; Hu, Z.; Zhou, Z.; Singleton, A. Anatomy of Subsidence in Tianjin from Time Series InSAR. Remote Sensing 2016, 8(3), 266; doi:10.3390/rs8030266 --- Ma, Y.; Chen, F.; Liu, J.; He, Y.; Duan, J.; Li, X. An Automatic Procedure for Early Disaster Change Mapping Based on Optical Remote Sensing. Remote Sensing 2016, 8(4), 272; doi:10.3390/rs8040272 --- Yang, C.; Zhang, Q.; Xu, Q.; Zhao, C.; Peng, J.; Ji, L. Complex Deformation Monitoring over the Linfen–Yuncheng Basin (China) with Time Series InSAR Technology. Remote Sensing 2016, 8(4), 284; doi:10.3390/rs8040284 --- Watanabe, M.; Thapa, R.; Shimada, M. Pi-SAR-L2 Observation of the Landslide Caused by Typhoon Wipha on Izu Oshima Island. Remote Sensing 2016, 8(4), 282; doi:10.3390/rs8040282 --- Plank, S.; Twele, A.; Martinis, S. Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data. Remote Sensing 2016, 8(4), 307; doi:10.3390/rs8040307 --- Solaro, G.; De Novellis, V.; Castaldo, R.; De Luca, C.; Lanari, R.; Manunta, M.; Casu, F. Coseismic Fault Model of Mw 8.3 2015 Illapel Earthquake (Chile) Retrieved from Multi-Orbit Sentinel1-A DInSAR Measurements. Remote Sensing 2016, 8(4), 323; doi:10.3390/rs8040323 --- Bai, L.; Jiang, L.; Wang, H.; Sun, Q. Spatiotemporal Characterization of Land Subsidence and Uplift (2009–2010) over Wuhan in Central China Revealed by TerraSAR-X InSAR Analysis. Remote Sensing 2016, 8(4), 350; doi:10.3390/rs8040350 --- Xu, B.; Li, Z.; Feng, G.; Zhang, Z.; Wang, Q.; Hu, J.; Chen, X. Continent-Wide 2-D Co-Seismic Deformation of the 2015 Mw 8.3 Illapel, Chile Earthquake Derived from Sentinel-1A Data: Correction of Azimuth Co-Registration Error. Remote Sensing 2016, 8(5), 376; doi:10.3390/rs8050376 --- Chen, M.; Tomás, R.; Li, Z.; Motagh, M.; Li, T.; Hu, L.; Gong, H.; Li, X.; Yu, J.; Gong, X. Imaging Land Subsidence Induced by Groundwater Extraction in Beijing (China) Using Satellite Radar Interferometry. Remote Sensing 2016, 8(6), 468; doi:10.3390/rs8060468 --- Ji, L.; Xu, J.; Zhao, Q.; Yang, C. Source Parameters of the 2003–2004 Bange Earthquake Sequence, Central Tibet, China, Estimated from InSAR Data. Remote Sensing 2016, 8(6), 516; doi:10.3390/rs8060516 --- Li, Y.; Jiang, W.; Zhang, J.; Luo, Y. Space Geodetic Observations and Modeling of 2016 Mw 5.9 Menyuan Earthquake: Implications on Seismogenic Tectonic Motion. Remote Sensing 2016, 8(6), 519; doi:10.3390/rs8060519 --- Trasatti, E.; Tolomei, C.; Pezzo, G.; Atzori, S.; Salvi, S. Deformation and Related Slip Due to the 2011 Van Earthquake (Turkey) Sequence Imaged by SAR Data and Numerical Modeling. Remote Sensing 2016, 8(6), 532; doi:10.3390/rs8060532 --- Wang, C.; Mao, X.; Wang, Q. Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method. Remote Sensing 2016, 8(8), 624; doi:10.3390/rs8080624 --- Liu, Y.; Xu, C.; Li, Z.; Wen, Y.; Chen, J.; Li, Z. Time-Dependent Afterslip of the 2009 Mw 6.3 Dachaidan Earthquake (China) and Viscosity beneath the Qaidam Basin Inferred from Postseismic Deformation Observations. Remote Sensing 2016, 8(8), 649; doi:10.3390/rs8080649 --- Xu, B.; Feng, G.; Li, Z.; Wang, Q.; Wang, C.; Xie, R. Coastal Subsidence Monitoring Associated with Land Reclamation Using the Point Target Based SBAS-InSAR Method: A Case Study of Shenzhen, China. Remote Sensing 2016, 8(8), 652; doi:10.3390/rs8080652 --- Sun, L.; Muller, J. Evaluation of the Use of Sub-Pixel Offset Tracking Techniques to Monitor Landslides in Densely Vegetated Steeply Sloped Areas. Remote Sensing 2016, 8(8), 659; doi:10.3390/rs8080659 --- De Novellis, V.; Castaldo, R.; Lollino, P.; Manunta, M.; Tizzani, P. Advanced Three-Dimensional Finite Element Modeling of a Slow Landslide through the Exploitation of DInSAR Measurements and in Situ Surveys. Remote Sensing 2016, 8(8), 670; doi:10.3390/rs8080670 --- Zhang, Y.; Wu, H.; Kang, Y.; Zhu, C. Ground Subsidence in the Beijing-Tianjin-Hebei Region from 1992 to 2014 Revealed by Multiple SAR Stacks. Remote Sensing 2016, 8(8), 675; doi:10.3390/rs8080675 --- Zhou, G.; Yue, T.; Shi, Y.; Zhang, R.; Huang, J. Second-Order Polynomial Equation-Based Block Adjustment for Orthorectification of DISP Imagery. Remote Sensing 2016, 8(8), 680; doi:10.3390/rs8080680 --- Bonì, R.; Pilla, G.; Meisina, C. Methodology for Detection and Interpretation of Ground Motion Areas with the A-DInSAR Time Series Analysis. Remote Sensing 2016, 8(8), 686; doi:10.3390/rs8080686 --- Xie, S.; Duan, J.; Liu, S.; Dai, Q.; Liu, W.; Ma, Y.; Guo, R.; Ma, C. Crowdsourcing Rapid Assessment of Collapsed Buildings Early after the Earthquake Based on Aerial Remote Sensing Image: A Case Study of Yushu Earthquake. Remote Sensing 2016, 8(9), 759; doi:10.3390/rs8090759 --- Fernández, T.; Pérez, J.; Cardenal, J.; Gómez, J.; Colomo, C.; Delgado, J. Analysis of Landslide Evolution Affecting Olive Groves Using UAV and Photogrammetric Techniques. Remote Sensing 2016, 8(10), 837; doi:10.3390/rs8100837 --- Cignetti, M.; Manconi, A.; Manunta, M.; Giordan, D.; De Luca, C.; Allasia, P.; Ardizzone, F. Taking Advantage of the ESA G-POD Service to Study Ground Deformation Processes in High Mountain Areas: A Valle d’Aosta Case Study, Northern Italy. Remote Sensing 2016, 8(10), 852; doi:10.3390/rs8100852 --- Cooner, A.; Shao, Y.; Campbell, J. Detection of Urban Damage Using Remote Sensing and Machine Learning Algorithms: Revisiting the 2010 Haiti Earthquake. Remote Sensing 2016, 8(10), 868; doi:10.3390/rs8100868 --- Zhou, W.; Li, S.; Zhou, Z.; Chang, X. InSAR Observation and Numerical Modeling of the Earth-Dam Displacement of Shuibuya Dam (China). Remote Sensing 2016, 8(10), 877; doi:10.3390/rs8100877 --- Qu, T.; Lu, P.; Liu, C.; Wu, H.; Shao, X.; Wan, H.; Li, N.; Li, R. Hybrid-SAR Technique: Joint Analysis Using Phase-Based and Amplitude-Based Methods for the Xishancun Giant Landslide Monitoring. Remote Sensing 2016, 8(10), 874; doi:10.3390/rs8100874 --- Gong, L.; Wang, C.; Wu, F.; Zhang, J.; Zhang, H.; Li, Q. Earthquake-Induced Building Damage Detection with Post-Event Sub-Meter VHR TerraSAR-X Staring Spotlight Imagery. Remote Sensing 2016, 8(11), 887; doi:10.3390/rs8110887 --- Ding, C.; Feng, G.; Li, Z.; Shan, X.; Du, Y.; Wang, H. Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements. Remote Sensing 2016, 8(11), 937; doi:10.3390/rs8110937 --- Ma, C.; Cheng, X.; Yang, Y.; Zhang, X.; Guo, Z.; Zou, Y. Investigation on Mining Subsidence Based on Multi-Temporal InSAR and Time-Series Analysis of the Small Baseline Subset—Case Study of Working Faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield, China. Remote Sensing 2016, 8(11), 951; doi:10.3390/rs8110951 --- Caló, F.; Notti, D.; Galve, J.; Abdikan, S.; Görüm, T.; Pepe, A.; Balik Şanli, F. DInSAR-Based Detection of Land Subsidence and Correlation with Groundwater Depletion in Konya Plain, Turkey. Remote Sensing 2017, 9(1), 83; doi:10.3390/rs9010083 --- Tomás, R.; Li, Z. Earth Observations for Geohazards: Present and Future Challenges. Remote Sensing 2017, 9(3), 194; doi:10.3390/rs9030194

Description / Table of Contents: Wang, X.; Wang, R.; Wei, Q.; Wang, P.; Wei, J. Mineralogical and Geochemical Characteristics of Late Permian Coals from the Mahe Mine, Zhaotong Coalfield, Northeastern Yunnan, China. Minerals 2015, 5(3), 380-396; doi:10.3390/min5030380. http://www.mdpi.com/2075-163X/5/3/380 --- Hower, J.; Eble, C.; O'Keefe, J.; Dai, S.; Wang, P.; Xie, P.; Liu, J.; Ward, C.; French, D. Petrology, Palynology, and Geochemistry of Gray Hawk Coal (Early Pennsylvanian, Langsettian) in Eastern Kentucky, USA. Minerals 2015, 5(3), 592-622; doi:10.3390/min5030511. http://www.mdpi.com/2075-163X/5/3/0511 --- Devasahayam, S.; Ameen, M.; Verheyen, T.; Bandyopadhyay, S. Brown Coal Dewatering Using Poly (Acrylamide-Co-Potassium Acrylic) Based Super Absorbent Polymers. Minerals 2015, 5(4), 623-636; doi:10.3390/min5040512. http://www.mdpi.com/2075-163X/5/4/0512 --- Wang, X.; Feng, Q.; Sun, R.; Liu, G. Radioactivity of Natural Nuclides (40K, 238U, 232Th, 226Ra) in Coals from Eastern Yunnan, China. Minerals 2015, 5(4), 637-646; doi:10.3390/min5040513. http://www.mdpi.com/2075-163X/5/4/0513 --- Yang, N.; Tang, S.; Zhang, S.; Chen, Y. Mineralogical and Geochemical Compositions of the No. 5 Coal in Chuancaogedan Mine, Junger Coalfield, China. Minerals 2015, 5(4), 788-800; doi:10.3390/min5040525. http://www.mdpi.com/2075-163X/5/4/0525 --- Jia, J.; Li, X.; Wu, P.; Liu, Y.; Han, C.; Zhou, L.; Yang, L. Human Health Risk Assessment and Safety Threshold of Harmful Trace Elements in the Soil Environment of the Wulantuga Open-Cast Coal Mine. Minerals 2015, 5(4), 837-848; doi:10.3390/min5040528. http://www.mdpi.com/2075-163X/5/4/0528 --- Wang, G.; Luo, Z.; Zhang, J.; Zhao, Y. Modes of Occurrence of Fluorine by Extraction and SEM Method in a Coal-Fired Power Plant from Inner Mongolia, China. Minerals 2015, 5(4), 863-869; doi:10.3390/min5040530. http://www.mdpi.com/2075-163X/5/4/0530 --- Zhao, L.; Ward, C.; French, D.; Graham, I. Major and Trace Element Geochemistry of Coals and Intra-Seam Claystones from the Songzao Coalfield, SW China. Minerals 2015, 5(4), 870-893; doi:10.3390/min5040531. http://www.mdpi.com/2075-163X/5/4/0531 --- Johnston, M.; Hower, J.; Dai, S.; Wang, P.; Xie, P.; Liu, J. Petrology and Geochemistry of the Harlan, Kellioka, and Darby Coals from the Louellen 7.5-Minute Quadrangle, Harlan County, Kentucky. Minerals 2015, 5(4), 894-918; doi:10.3390/min5040532. http://www.mdpi.com/2075-163X/5/4/0532 --- Liu, S.; Qi, C.; Zhang, S.; Deng, Y. Minerals in the Ash and Slag from Oxygen-Enriched Underground Coal Gasification. Minerals 2016, 6(2), 27; doi:10.3390/min6020027. http://www.mdpi.com/2075-163X/6/2/27 --- Xiao, L.; Zhao, B.; Duan, P.; Shi, Z.; Ma, J.; Lin, M. Geochemical Characteristics of Trace Elements in the No. 6 Coal Seam from the Chuancaogedan Mine, Jungar Coalfield, Inner Mongolia, China. Minerals 2016, 6(2), 28; doi:10.3390/min6020028. http://www.mdpi.com/2075-163X/6/2/28 --- Xie, P.; Song, H.; Wei, J.; Li, Q. Mineralogical Characteristics of Late Permian Coals from the Yueliangtian Coal Mine, Guizhou, Southwestern China. Minerals 2016, 6(2), 29; doi:10.3390/min6020029. http://www.mdpi.com/2075-163X/6/2/29 --- Hower, J.; Granite, E.; Mayfield, D.; Lewis, A.; Finkelman, R. Notes on Contributions to the Science of Rare Earth Element Enrichment in Coal and Coal Combustion Byproducts. Minerals 2016, 6(2), 32; doi:10.3390/min6020032. http://www.mdpi.com/2075-163X/6/2/32 --- Liu, H.; Sun, Q.; Wang, B.; Wang, P.; Zou, J. Morphology and Composition of Microspheres in Fly Ash from the Luohuang Power Plant, Chongqing, Southwestern China. Minerals 2016, 6(2), 30; doi:10.3390/min6020030. http://www.mdpi.com/2075-163X/6/2/30 --- Dang, J.; Xie, Q.; Liang, D.; Wang, X.; Dong, H.; Cao, J. The Fate of Trace Elements in Yanshan Coal during Fast Pyrolysis. Minerals 2016, 6(2), 35; doi:10.3390/min6020035. http://www.mdpi.com/2075-163X/6/2/35 --- Yang, N.; Tang, S.; Zhang, S.; Chen, Y. Modes of Occurrence and Abundance of Trace Elements in Pennsylvanian Coals from the Pingshuo Mine, Ningwu Coalfield, Shanxi Province, China. Minerals 2016, 6(2), 40; doi:10.3390/min6020040. http://www.mdpi.com/2075-163X/6/2/40 --- Zhao, L.; Dai, S.; Graham, I.; Wang, P. Clay Mineralogy of Coal-Hosted Nb-Zr-REE-Ga Mineralized Beds from Late Permian Strata, Eastern Yunnan, SW China: Implications for Paleotemperature and Origin of the Micro-Quartz. Minerals 2016, 6(2), 45; doi:10.3390/min6020045. http://www.mdpi.com/2075-163X/6/2/45 --- Zou, J.; Tian, H.; Li, T. Geochemistry and Mineralogy of Tuff in Zhongliangshan Mine, Chongqing, Southwestern China. Minerals 2016, 6(2), 47; doi:10.3390/min6020047. http://www.mdpi.com/2075-163X/6/2/47 --- Yang, L.; Song, J.; Bai, X.; Song, B.; Wang, R.; Zhou, T.; Jia, J.; Pu, H. Leaching Behavior and Potential Environmental Effects of Trace Elements in Coal Gangue of an Open-Cast Coal Mine Area, Inner Mongolia, China. Minerals 2016, 6(2), 50; doi:10.3390/min6020050. http://www.mdpi.com/2075-163X/6/2/50 --- Wang, X.; Zhang, L.; Jiang, Y.; Wei, J.; Chen, Z. Mineralogical and Geochemical Characteristics of the Early Permian Upper No. 3 Coal from Southwestern Shandong, China. Minerals 2016, 6(3), 58; doi:10.3390/min6030058. http://www.mdpi.com/2075-163X/6/3/58 --- Giménez-García, R.; Vigil de la Villa Mencía, R.; Rubio, V.; Frías, M. The Transformation of Coal-Mining Waste Minerals in the Pozzolanic Reactions of Cements. Minerals 2016, 6(3), 64; doi:10.3390/min6030064. http://www.mdpi.com/2075-163X/6/3/64 --- Wang, R. Geological Controls on Mineralogy and Geochemistry of an Early Permian Coal from the Songshao Mine, Yunnan Province, Southwestern China. Minerals 2016, 6(3), 66; doi:10.3390/min6030066. http://www.mdpi.com/2075-163X/6/3/66 --- Luo, Y.; Zheng, M. Origin of Minerals and Elements in the Late Permian Coal Seams of the Shiping Mine, Sichuan, Southwestern China. Minerals 2016, 6(3), 74; doi:10.3390/min6030074. http://www.mdpi.com/2075-163X/6/3/74

Description / Table of Contents: All living organisms are composed of major, minor, and trace elements, given by nature and supplied by geology. Medical geology is a rapidly growing discipline dealing with the influence of natural geological and environmental risk factors on the distribution of health problems in humans and animals. As a multi-disciplinary scientific field, medical geology has the potential of helping medical and public health communities all over the world in the pursuit of solutions to a wide range of environmental and naturally induced health issues. The natural environment can impact health in a variety of ways. The composition of rocks and minerals are imprinted on the air that we breathe, the water that we drink, and the food that we eat. For many people this transference of minerals and the trace elements they contain is beneficial as it is the primary source of nutrients (such as calcium, iron, magnesium, potassium, and about a dozen other elements) that are essential for a healthy life. However, sometimes the local geology can cause significant health problems because there is an insufficient amount of an essential element or an excess of a potentially toxic element (such as arsenic, mercury, lead, fluorine, etc.), or a harmful substance such as methane gas, dust-sized particles of asbestos, quartz or pyrite, or certain naturally occurring organic compounds. Current and future medical geology concerns include: dangerous levels of arsenic in drinking water in dozens of countries including the USA; mercury emissions from coal combustion and its bioaccumulation in the environment; the impacts of mercury and lead mobilizations in regions were artisanal gold mining is conducted; the residual health impacts of geologic processes such as volcanic emissions, earthquakes, tsunamis, hurricanes, and geogenic dust; exposure to fibrous minerals such as asbestos and erionite; and the health impacts of global climate change. Billions of people, most in developing countries, are afflicted by these and other environmental health issues that can be avoided, prevented, mitigated or minimized through research and educational outreach. This Special Issue of Geosciences discusses recent advances in medical geology, providing examples from research conducted all over the world. Among the topics to be discussed are: - Health effects from trace elements, metals and metalloids - Regional and global impacts of natural dust (including the study of nanoparticles) - Chemical and environmental pathology of diseases associated with natural environment - Novel analytical approaches to the study of natural geochemical and environmental agents - Research on beneficial health aspects of natural geological materials - Risk management, risk communication and risk mitigation on medical geology - Remote sensing and GIS applications on medical geology - Epidemiology and public health studies on medical geology - Climate change and medical geology - Clinical and toxicological research on biomarkers of exposure - Veterinary medical geology - Biosurveillance and biomonitoring studies on medical geology

Description / Table of Contents: Falcinelli, S.; Pirani, F.; Vecchiocattivi, F. The Possible Role of Penning Ionization Processes in Planetary Atmospheres. Atmosphere 2015, 6(3), 299-317; doi:10.3390/atmos6030299 --- Park, S.; Seo, B.; Lee, G.; Kahng, S.; Jang, Y. Chemical Composition of Water Soluble Inorganic Species in Precipitation at Shihwa Basin, Korea. Atmosphere 2015, 6(6), 732-750; doi:10.3390/atmos6060732 --- Kassianov, E.; Berg, L.; Pekour, M.; Barnard, J.; Chand, D.; Flynn, C.; Ovchinnikov, M.; Sedlacek, A.; Schmid, B.; Shilling, J.; Tomlinson, J.; Fast, J. Airborne Aerosol in Situ Measurements during TCAP: A Closure Study of Total Scattering. Atmosphere 2015, 6(8), 1069-1101; doi:10.3390/atmos6081069 --- Majewski, G.; Rogula-Kozłowska, W.; Czechowski, P.; Badyda, A.; Brandyk, A. The Impact of Selected Parameters on Visibility: First Results from a Long-Term Campaign in Warsaw, Poland. Atmosphere 2015, 6(8), 1154-1174; doi:10.3390/atmos6081154 --- Khwaja, H.; Aburizaiza, O.; Hershey, D.; Siddique, A.; E., D.; Zeb, J.; Abbass, M.; Blake, D.; Hussain, M.; Aburiziza, A.; Kramer, M.; Simpson, I. Study of Black Sand Particles from Sand Dunes in Badr, Saudi Arabia Using Electron Microscopy. Atmosphere 2015, 6(8), 1175-1194; doi:10.3390/atmos6081175 --- Wu, Z.; Liu, F.; Fan, W. Characteristics of PM10 and PM2.5 at Mount Wutai Buddhism Scenic Spot, Shanxi, China. Atmosphere 2015, 6(8), 1195-1210; doi:10.3390/atmos6081195 --- Saldarriaga-Noreña, H.; López-Márquez, R.; Murillo-Tovar, M.; Hernández-Mena, L.; Ospina-Noreña, E.; Sánchez-Salinas, E.; Waliszewski, S.; Montiel-Palma, S. Analysis of PAHs Associated with Particulate Matter PM2.5 in Two Places at the City of Cuernavaca, Morelos, México. Atmosphere 2015, 6(9), 1259-1270; doi:10.3390/atmos6091259 --- Faxon, C.; Bean, J.; Ruiz, L. Inland Concentrations of Cl2 and ClNO2 in Southeast Texas Suggest Chlorine Chemistry Significantly Contributes to Atmospheric Reactivity. Atmosphere 2015, 6(10), 1487-1506; doi:10.3390/atmos6101487 --- Asa-Awuku, A.; Sorooshian, A.; Flagan, R.; Seinfeld, J.; Nenes, A. CCN Properties of Organic Aerosol Collected Below and within Marine Stratocumulus Clouds near Monterey, California. Atmosphere 2015, 6(11), 1590-1607; doi:10.3390/atmos6111590 --- Yang, M.; Wang, Y.; Liu, Q.; Ding, A.; Li, Y. The Influence of Sandstorms and Long-Range Transport on Polycyclic Aromatic Hydrocarbons (PAHs) in PM2.5 in the High-Altitude Atmosphere of Southern China. Atmosphere 2015, 6(11), 1633-1651; doi:10.3390/atmos6111633 --- Rubio, M.; Lissi, E.; Gramsch, E.; Garreaud, R. Effect of Nearby Forest Fires on Ground Level Ozone Concentrations in Santiago, Chile. Atmosphere 2015, 6(12), 1926-1938; doi:10.3390/atmos6121838 --- Lopez, D.; Rabbani, M.; Crosbie, E.; Raman, A.; Arellano, A.; Sorooshian, A. Frequency and Character of Extreme Aerosol Events in the Southwestern United States: A Case Study Analysis in Arizona. Atmosphere 2016, 7(1), 1; doi:10.3390/atmos7010001 --- Stovern, M.; Guzmán, H.; Rine, K.; Felix, O.; King, M.; Ela, W.; Betterton, E.; Sáez, A. Windblown Dust Deposition Forecasting and Spread of Contamination around Mine Tailings. Atmosphere 2016, 7(2), 16; doi:10.3390/atmos7020016 --- Raman, A.; Arellano, A.; Sorooshian, A. Decreasing Aerosol Loading in the North American Monsoon Region. Atmosphere 2016, 7(2), 24; doi:10.3390/atmos7020024 --- Hetem, I.; Andrade, M. Characterization of Fine Particulate Matter Emitted from the Resuspension of Road and Pavement Dust in the Metropolitan Area of São Paulo, Brazil. Atmosphere 2016, 7(3), 31; doi:10.3390/atmos7030031

Description / Table of Contents: Mercury is a serious environmental toxin that is distributed globally by large-scale atmospheric circulations. Atmospheric chemists have only been studying mercury in earnest for approximately the past 10 years. In the troposphere elemental mercury (Hgo) is observed ubiquitously with contemporary mixing ratios at the parts per quadrillion by volume (ppqv; 1 ng m−3 = 112 ppqv) level. The distributions of gaseous oxidized mercury (GOM) and particulate mercury (HgP) are not well documented at this time. In fact, the chemical composition of GOM is presently highly uncertain. At most mid-latitude locations, Hgo exhibits seasonality with the lowest mixing ratios in the fall and the greatest in late winter/early spring. It is highly desirable to conduct measurements of a variety of trace gases along with atmospheric mercury to facilitate source identification, but few studies have done so to date. A serious drawback in modeling atmospheric mercury is a lack of reliable rigorous emission inventories. Consequently, much work is needed to identify mercury sources and to quantify emission strengths. There are few published papers on measurements of atmospheric mercury from aircraft. Initial work has shown that there is little to no Hgo above the tropopause and that HgP is elevated there. The chemical cycling and transformations in the tropopause region are essentially unstudied. Both measurements and modeling are required to ascertain the important processes affecting atmospheric mercury in the tropopause region.