ALBERT

Description / Table of Contents: The present Special Issue intends to explore new directions in the field of acoustics and ultrasonics. The interest includes, but is not limited to, the use of acoustic technology for condition monitoring of materials and structures. (The basis of this issue comes from selected papers of the 6th International Conference on Emerging Technologies in Non-destructive Testing, ETNDT6 held in Brussels May 27-29th, 2015).

Description / Table of Contents: The success of the Suomi National Polar-orbiting Partnership (NPP) brings us into a new era of global daily Earth observations, ranging from the faintest light of human settlements and air glows to the dramatic events of hurricanes and forest fires, as well as the subtle changes in the planet Earth which we call home. At the heart of all satellite applications, calibration/validation of the measurements and derived products is the key. Satellite product calibration and validation have become increasingly more important and challenging in order to meet the stringent requirements for accurate quantitative data for climate change detection, numerical weather prediction, and environmental intelligence. Validation is required not only for the satellite measurements, but also for all geophysical retrievals, including aerosols, cloud properties, radiation budget, sea surface temperature, ocean color, active fire, albedo, snow and ice, vegetation, as well as nightlights from human settlements. Active validation research includes but not limited to, comparisons with similar products from other satellites, with in situ, aircraft measurements, or observations from other platforms. Validation results not only help users and decision makers but also serve as feedback to calibration, which in turn improves the products. This Special Issue of Remote Sensing aims at exploring recent results in the calibration and validation of the Suomi National Polar-orbiting Partnership satellite (Suomi NPP)/JPSS radiometers.

Description / Table of Contents: The pulse width of an electromagnetic wave is determined by the frequency band width of the wave used. Therefore, one femtosecond is the ultimate in pulse width for an “optical” wave. For this reason, several methods have been proposed for the generation of an ultrashort optical pulse. For example, resonance/non-resonance four-wave mixing would be one of the candidates for generating multi-color laser emission in an extremely wide spectral region, thus breaking the 1-fs barrier. To date, numerous emission lines have been generated from the deep-ultraviolet to the near-infrared region (〈45,000 cm−1). Such generations use a variety of techniques, such as four-wave Raman mixing in molecular hydrogen. This type of technique is promising for the generation of 1-fs optical pulses via phase locking and the Fourier synthesis of the emission lines. For verification, it would be necessary to develop a new method for measuring the pulse width, since the spectral band width approaches or is beyond one octave. Ultrashort optical pulses can be utilized in a variety of applications in science and technology. For example, an ultrashort optical pulse can be used in the studies of ultrafast phenomena. More practically, a laser pulse shorter than 100 fs is reported to be useful in mass spectrometry for observing a molecular ion of triacetone triperoxide, an explosive used in terrorist attacks. A train of ultrashort optical pulses in the terahertz region, which has been generated in the optical cavity to enhance the nonlinear optical effect, would be employed as a clock pulse in optical computation/communication in future advanced industries.

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: 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: As the fields of organometallic and coordination chemistry of the transition metals has grown more mature, the under-explored chemistry of the rare-earths and actinides has drawn the attention of research groups from across the globe looking for new fundamental discoveries and access to compounds with unique properties. The rare earths – the group 3 metals and the 4f lanthanide series – have long shown many interesting properties in the solid state which exploit their unique electronic configurations. However, it is the molecular chemistry of these metals that has expanded dramatically in recent years as researchers identify the differences between – and unique features of – their molecular compounds. Recent highlights include the identification of new oxidation states and patterns of reactivity as well as applications in medical imaging and health care which represent new and exciting areas of research. The actinides show a wide range of different properties as a consequence of their radioactivity and radiochemistry, but this has not stopped recent rapid progress into the exploration of their unique chemistry. Uranium, in particular, shows huge potential with its transition metal like range of oxidation states (+2 to +6), and in specialised laboratories, the heavier actinides are also beginning to show their unique chemistry as well. This Special Issue aims to bring together these strands of research in an openly-accessible way to allow better communication of these advances to a wider audience. This is necessary as despite these exciting advances, the rare earths and actinides are still much neglected topics in both school and undergraduate curriculums.

Description / Table of Contents: According to the 2014 revision of the World Urbanization Prospects by UN DESA, urbanization could add another 2.5 billion people to the urban population by 2050, with close to 90 percent of the increase concentrated in Asia and Africa. The largest urban growth will take place in India, China and Nigeria. This unprecedented increase in urban population not only poses challenges to providing urban jobs, housing, and infrastructure, but also exerts an increased pressure on urban land and sustainability. As land is a vital yet limited resource, sustainable management of urban land to cater to the needs of this growing urban population is seen as one of the key challenges for achieving an economically efficient, socially equitable, and environmentally safe society. A key tenet for sustainable economic development and smart growth is promoting sustainable urban land development and mitigating land use conflicts. While a large body of literature has dealt with both land use and sustainable development, the study of the interactive effects of these two remains limited. We also need more sophisticated empirical studies examining processes, mechanisms, institutions, equity, and sustainability of urban land use. We also encourage efforts to develop new theories, new concepts and new methods to understand the myriad ways in which urban land and sustainable development correlate each other. This special issue examines patterns, structure, and dynamics of urban land development and sustainability from multiple perspectives, in various contexts and at multiple dimensions (economic, social, political, developmental, environmental, etc.).

Description / Table of Contents: In the face of climate change and resource scarcity, energy supply systems are on the verge of a major transformation, which mainly includes the introduction of new components and their integration into the existing infrastructures, new network configurations and reliable topologies, optimal design and novel operation schemes, and new incentives and business models. This revolution is affecting the current paradigm and demanding that energy systems be integrated into multi-carrier energy hubs. It is greatly increasing the interactions between today’s energy systems at various scales (ranging from the multinational, national, community scales down to the building level) and future intelligent energy systems, which are able to incorporate an increasing amount of often fluctuating, renewable energy sources (RESs). It is also increases the need for the integration of energy storage options into the energy mix, not only to reduce the need for increased peak generation capacity, but also to enhance grid reliability and support higher penetration of RESs. Moreover, this transformation is accommodating active participation of end-users as responsive prosumers at different scales, which in turn help to reduce energy costs to all consumers, increase reliability of service and mitigate carbon footprints. However, this plan of action necessitates regulatory frameworks, strategic incentives and business models for efficient deployment. This Special Issue will cover these promising and dynamic areas of research and development, and will allow gathering of contributions in design, control and optimization of integrated energy systems. This Special Issue also seeks papers to report advances in any aspect of these developments. The manuscripts should be unpublished and report significant advancement.

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: Fu, R.; Wu, Y.; Wang, H.; Xie, J. A Distributed Control Strategy for Frequency Regulation in Smart Grids Based on the Consensus Protocol. Energies 2015, 8(8), 7930-7944; doi:10.3390/en8087930. http://www.mdpi.com/1996-1073/8/8/7930 --- Chae, W.; Lee, H.; Won, J.; Park, J.; Kim, J. Design and Field Tests of an Inverted Based Remote MicroGrid on a Korean Island. Energies 2015, 8(8), 8193-8210; doi:10.3390/en8088193. http://www.mdpi.com/1996-1073/8/8/8193 --- Nguyen, T.; Yoo, H.; Kim, H. Application of Model Predictive Control to BESS for Microgrid Control. Energies 2015, 8(8), 8798-8813; doi:10.3390/en8088798. http://www.mdpi.com/1996-1073/8/8/8798 --- Jung, S.; Jang, G. Development of an Optimal Power Control Scheme for Wave-Offshore Hybrid Generation Systems. Energies 2015, 8(9), 9009-9028; doi:10.3390/en8099009. http://www.mdpi.com/1996-1073/8/9/9009 --- Yang, Y.; Zhang, W.; Jiang, J.; Huang, M.; Niu, L. Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration. Energies 2015, 8(10), 10718-10735; doi:10.3390/en81010718. http://www.mdpi.com/1996-1073/8/10/10718 --- Xia, H.; Chen, H.; Yang, Z.; Lin, F.; Wang, B. Optimal Energy Management, Location and Size for Stationary Energy Storage System in a Metro Line Based on Genetic Algorithm. Energies 2015, 8(10), 11618-11640; doi:10.3390/en81011618. http://www.mdpi.com/1996-1073/8/10/11618 --- Telaretti, E.; Ippolito, M.; Dusonchet, L. A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs. Energies 2016, 9(1), 12; doi:10.3390/en9010012. http://www.mdpi.com/1996-1073/9/1/12 --- Gelažanskas, L.; Gamage, K. Distributed Energy Storage Using Residential Hot Water Heaters. Energies 2016, 9(3), 127; doi:10.3390/en9030127. http://www.mdpi.com/1996-1073/9/3/127 --- Pietrosanti, S.; Holderbaum, W.; Becerra, V. Optimal Power Management Strategy for Energy Storage with Stochastic Loads. Energies 2016, 9(3), 175; doi:10.3390/en9030175. http://www.mdpi.com/1996-1073/9/3/175 --- Lin, F.; Li, X.; Zhao, Y.; Yang, Z. Control Strategies with Dynamic Threshold Adjustment for Supercapacitor Energy Storage System Considering the Train and Substation Characteristics in Urban Rail Transit. Energies 2016, 9(4), 257; doi:10.3390/en9040257. http://www.mdpi.com/1996-1073/9/4/257 --- Bruen, T.; Hooper, J.; Marco, J.; Gama, M.; Chouchelamane, G. Analysis of a Battery Management System (BMS) Control Strategy for Vibration Aged Nickel Manganese Cobalt Oxide (NMC) Lithium-Ion 18650 Battery Cells. Energies 2016, 9(4), 255; doi:10.3390/en9040255. http://www.mdpi.com/1996-1073/9/4/255 --- Chung, Y. A Novel Power-Saving Transmission Scheme for Multiple-Component-Carrier Cellular Systems. Energies 2016, 9(4), 265; doi:10.3390/en9040265. http://www.mdpi.com/1996-1073/9/4/265 --- Zangs, M.; Adams, P.; Yunusov, T.; Holderbaum, W.; Potter, B. Distributed Energy Storage Control for Dynamic Load Impact Mitigation. Energies 2016, 9(8), 647; doi:10.3390/en9080647. http://www.mdpi.com/1996-1073/9/8/647 --- Zhao, Z.; Sun, Y.; Hu, A.; Dai, X.; Tang, C. Energy Link Optimization in a Wireless Power Transfer Grid under Energy Autonomy Based on the Improved Genetic Algorithm. Energies 2016, 9(9), 682; doi:10.3390/en9090682. http://www.mdpi.com/1996-1073/9/9/682 --- Gatta, F.; Geri, A.; Lamedica, R.; Lauria, S.; Maccioni, M.; Palone, F.; Rebolini, M.; Ruvio, A. Application of a LiFePO4 Battery Energy Storage System to Primary Frequency Control: Simulations and Experimental Results. Energies 2016, 9(11), 887; doi:10.3390/en9110887. http://www.mdpi.com/1996-1073/9/11/887 --- Kies, A.; Schyska, B.; von Bremen, L. The Demand Side Management Potential to Balance a Highly Renewable European Power System. Energies 2016, 9(11), 955; doi:10.3390/en9110955. http://www.mdpi.com/1996-1073/9/11/955 --- Yang, J.; Choi, J.; An, G.; Choi, Y.; Kim, M.; Won, D. Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation. Energies 2016, 9(12), 1010; doi:10.3390/en9121010. http://www.mdpi.com/1996-1073/9/12/1010 --- Gao, Z.; Chin, C.; Woo, W.; Jia, J. Integrated Equivalent Circuit and Thermal Model for Simulation of Temperature-Dependent LiFePO4 Battery in Actual Embedded Application. Energies 2017, 10(1), 85; doi:10.3390/en10010085. http://www.mdpi.com/1996-1073/10/1/85 --- Yunusov, T.; Zangs, M.; Holderbaum, W. Control of Energy Storage. Energies 2017, 10(7), 1010; doi:10.3390/en10071010. http://www.mdpi.com/1996-1073/10/7/1010

Description / Table of Contents: The “landscape Approach” is widely promoted as a way to reconcile biodiversity conservation with both commercial agriculture and local peoples’ demands for land. Landscape approaches imply a strong role for local communities in decision making and, therefore, local citizen science plays a role in determining landscape outcomes (Sayer et al., under review). Many claims and counter claims are made about the success and failure of local management in achieving good forest outcomes. There is significant uncertainty about the incentives for local people to manage forests for their global carbon storage and biodiversity values. Local people may be more concerned about immediate economic returns and less about the long term global environmental values of their forests. This Special Issue seeks to assemble papers that provide empirical evidence for the success of landscape and community managed initiatives to conserve biodiversity. We are seeking papers that report upon successful biodiversity conservation projects that have operated at a landscape scale and those that have been led by local communities. We are also interested in cases where these approaches were attempted but were less successful. Our ultimate goals is to identify the conditions under which these approaches have succeeded and those where they have been less successful.

Description / Table of Contents: Nishimura, T. Rust Formation Mechanism on Low Alloy Steels after Exposure Test in High Cl− and High SOx Environmen. Materials 2017, 10(2), 199; doi:10.3390/ma10020199. http://www.mdpi.com/1996-1944/10/2/199 --- Chang, T.; Odnevall Wallinder, I.; de la Fuente, D.; Chico, B.; Morcillo, M.; Welter, J.; Leygraf, C. Analysis of Historic Copper Patinas. Influence of Inclusions on Patina Uniformity. Materials 2017, 10(3), 298; doi:10.3390/ma10030298. http://www.mdpi.com/1996-1944/10/3/298 --- Na, O.; Cai, X.; Xi, Y. Corrosion Prediction with Parallel Finite Element Modeling for Coupled Hygro-Chemo Transport into Concrete under Chloride-Rich Environment. Materials 2017, 10(4), 350; doi:10.3390/ma10040350. http://www.mdpi.com/1996-1944/10/4/350 --- Kreislova, K.; Knotkova, D. The Results of 45 Years of Atmospheric Corrosion Study in the Czech Republic. Materials 2017, 10(4), 394; doi:10.3390/ma10040394. http://www.mdpi.com/1996-1944/10/4/394 --- Alcántara, J.; Fuente, D.; Chico, B.; Simancas, J.; Díaz, I.; Morcillo, M. Marine Atmospheric Corrosion of Carbon Steel: A Review. Materials 2017, 10(4), 406; doi:10.3390/ma10040406. http://www.mdpi.com/1996-1944/10/4/406 --- Hosseinpour, S.; Johnson, M. Vibrational Spectroscopy in Studies of Atmospheric Corrosion. Materials 2017, 10(4), 413; doi:10.3390/ma10040413. http://www.mdpi.com/1996-1944/10/4/413 --- Panchenko, Y.; Marshakov, A. Prediction of First-Year Corrosion Losses of Carbon Steel and Zinc in Continental Regions. Materials 2017, 10(4), 422; doi:10.3390/ma10040422. http://www.mdpi.com/1996-1944/10/4/422 --- Chico, B.; de la Fuente, D.; Díaz, I.; Simancas, J.; Morcillo, M. Annual Atmospheric Corrosion of Carbon Steel Worldwide. An Integration of ISOCORRAG, ICP/UNECE and MICAT Databases. Materials 2017, 10(6), 601; doi:10.3390/ma10060601. http://www.mdpi.com/1996-1944/10/6/601 --- Bouchar, M.; Dillmann, P.; Neff, D. New Insights in the Long-Term Atmospheric Corrosion Mechanisms of Low Alloy Steel Reinforcements of Cultural Heritage Buildings. Materials 2017, 10(6), 670; doi:10.3390/ma10060670. http://www.mdpi.com/1996-1944/10/6/670 --- Tidblad, J.; Kreislová, K.; Faller, M.; de la Fuente, D.; Yates, T.; Verney-Carron, A.; Grøntoft, T.; Gordon, A.; Hans, U. ICP Materials Trends in Corrosion, Soiling and Air Pollution (1987–2014). Materials 2017, 10(8), 969; doi:10.3390/ma10080969. http://www.mdpi.com/1996-1944/10/8/969 --- Cole, I. Recent Progress and Required Developments in Atmospheric Corrosion of Galvanised Steel and Zinc. Materials 2017, 10(11), 1288; doi:10.3390/ma10111288. http://www.mdpi.com/1996-1944/10/11/1288

Description / Table of Contents: The reversible elimination of hydrogen from metal hydrides serves as the basis for unique methods of energy transformation. This technology has found widespread practical utilization in applications such as hydrogen compressors, storage, and sensors, as well as batteries. Moreover, it is plausible that metal hydride technology could be utilized to provide practically viable solutions to the challenges of energy storage. For nearly two decades, an extensive, worldwide research effort has been devoted to complex metal hydrides possessing high volumetric and/or gravimetric hydrogen densities with the goal of their practical utilization as onboard hydrogen storage materials. Additionally, a significant and growing number of efforts have been devoted to developing metal hydrides as advanced sensors and ionic conductors, and for electrochemical and stationary energy storage. This Special Issue will provide a sampling of on-going, state-of-art research on metal hydrides, ranging from fundamental investigations to practical applications with a concentration on topics which are currently of high interest.

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: In 1692, Newton wrote: "That gravity should be innate inherent and essential to matter so that one body may act upon another at a distance through a vacuum without the mediation of anything else by and through which their action or force may be conveyed from one to another is to me so great an absurdity that I believe no man who has in philosophical matters any competent faculty of thinking can ever fall into it. Gravity must be caused by an agent acting constantly according to certain laws, but whether this agent be material or immaterial is a question I have left to the consideration of my readers". One of them who, just over 200 years later, picked up the baton of Newton was Albert Einstein. His General Theory of Relativity, which marks the centenary this year, opened up new windows on our comprehension of Nature, disclosed new, previously unpredictable, phenomena occurring when relative velocities dramatically change in intense gravitational fields reaching values close to the speed of light and, for the first time after millennia of speculations, put Cosmology on the firm grounds of empirically testable science. This Special Issue is dedicated to such a grandest achievement of the human thought.