Satellite Image Analysis for Disaster and Crisis-Management Support

The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar

Rabus, B., Eineder, M., Roth, A., & Bamler, R. (2003) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/s0924-2716(02)00124-7 · Cited by 1,825 · see citing works

An Enhanced Contextual Fire Detection Algorithm for MODIS

Giglio, L., Descloitres, J., Justice, C. O., & Kaufman, Y. J. (2003) · Remote Sensing of Environment · doi:10.1016/s0034-4257(03)00184-6 · Cited by 1,731 · see citing works

LandScan: a global population database for estimating populations at risk

Mesev, V. (2003) · CRC Press eBooks · doi:10.1201/9781482264678-24 · Cited by 899 · see citing works

NASA’s Global Orthorectified Landsat Data Set

Tucker, C. J., Grant, D. M., & Dykstra, J. D. (2004) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.70.3.313 · Cited by 506 · see citing works

Correction of satellite imagery over mountainous terrain

Richter, R. (1998) · Applied Optics · doi:10.1364/ao.37.004004 · Cited by 299 · see citing works

Satellite remote sensing for detailed landslide inventories using change detection and image fusion

Nichol, J. E., & Wong, M. S. (2005) · International Journal of Remote Sensing · doi:10.1080/01431160512331314047 · Cited by 280 · see citing works

Assessing the worldwide developments of national spatial data clearinghouses

Crompvoets, J., Bregt, A. K., Rajabifard, A., & WILLIAMSON, I. P. (2004) · International Journal of Geographical Information Systems · doi:10.1080/13658810410001702030 · Cited by 248 · see citing works

Geo-information for Disaster Management

Laurini, R., Servigne, S., & Noël, G. (2005) · Springer eBooks · doi:10.1007/b139115 · Cited by 247 · see citing works

Using SDI and web-based system to facilitate disaster management

Mansourian, A., Rajabifard, A., Zoej, M. J. V., & WILLIAMSON, I. P. (2005) · Computers & Geosciences · doi:10.1016/j.cageo.2005.06.017 · Cited by 213 · see citing works

The cloud analysis tool APOLLO: Improvements and validations

Kriebel, K. T., Gesell, G., ̈stner, M. K., & Mannstein, H. (2003) · International Journal of Remote Sensing · doi:10.1080/01431160210163065 · Cited by 164 · see citing works

Fire and smoke observed from the Earth Observing System MODIS instrument--products, validation, and operational use

Kaufman, Y. J., Ichoku, C. M., Giglio, L., Korontzi, S., Chu, D. A., Hao, W. M., Li, R. ‐., & Justice, C. (2003) · International Journal of Remote Sensing · doi:10.1080/01431160210144741 · Cited by 133 · see citing works

Comparison of SAR amplitude vs. coherence flood detection methods - a GIS application

Nico, G., Pappalepore, M., Pasquariello, G., Refice, A., & Samarelli, S. (2000) · International Journal of Remote Sensing · doi:10.1080/014311600209931 · Cited by 128 · see citing works

Rapid damage assessment of built‐up structures using VHR satellite data in tsunami‐affected areas

Pesaresi, M., Gerhardinger, A., & Haag, F. (2007) · International Journal of Remote Sensing · doi:10.1080/01431160601094492 · Cited by 81 · see citing works

Satellite-based forest fire detection for fire control in boreal forests

Rauste, Y., Herland, E., Frelander, H., Soini, K., Kuoremaki, T., & Ruokari, A. (1997) · International Journal of Remote Sensing · doi:10.1080/014311697217512 · Cited by 76 · see citing works

Accuracy analysis for DSM and orthoimages derived from SPOT HRS stereo data using direct georeferencing

Reinartz, P. H., Müller, R., Lehner, M., & Schroeder, M. (2006) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2005.12.003 · Cited by 56 · see citing works

Planimetric accuracy of Ikonos 1 m panchromatic orthoimage products and their utility for local government GIS basemap applications

Davis, C. H., & Wang, X. (2003) · International Journal of Remote Sensing · doi:10.1080/0143116031000070328 · Cited by 42 · see citing works

A comparison of visual observations of surface oil with Synthetic Aperture Radar imagery of the Sea Empress oil spill

Jones, B. (2001) · International Journal of Remote Sensing · doi:10.1080/01431160010008564 · Cited by 40 · see citing works

TOWARDS A GLOBAL ELEVATION PRODUCT: COMBINATION OF MULTI-SOURCE DIGITAL ELEVATION MODELS

Roth, A., Knöpfle, W., Strunz, G., Lehner, M., & Reinartz, P. H. (2002) · elib (German Aerospace Center) · Cited by 37 · see citing works

Block bundle adjustment of Ikonos in-track images

Toutin, T. (2003) · International Journal of Remote Sensing · doi:10.1080/0143116021000009877 · Cited by 33 · see citing works

Geocoding of TerraSAR-X Data

Roth, A., Huber, M., & Kosmann, D. (2004) · elib (German Aerospace Center) · Cited by 32 · see citing works

Geometric Processing of IKONOS Geo Images with DEM

Toutin, T. (2001) · doi:10.4095/219815 · Cited by 30 · see citing works

Comparing and combining the capability of detecting earthquake damages in urban areas using SAR and optical data

Bignami, C., Chini, M., Pierdicca, N., & Stramondo, S. (2004) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2004.1368943 · Cited by 22 · see citing works

Assessing flooding and vegetation structure in forested wetlands using Radarsat SAR imagery

Townsend, P. A., & Foster, J. R. (2003) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2002.1025811 · Cited by 9 · see citing works

Experiences in multi-sensoral SAR geocoding

Roth, A., Kosmann, D., Matschke, M., Müschen, B., & John, H. (2002) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.1996.516980 · Cited by 7 · see citing works

From Airborne Digital Raw Data to Image Maps

Müller, R., Palubinskas, G., Reinartz, P. H., Schroeder, M. R., Amann, V., & Stätter, R. (2003) · elib (German Aerospace Center) · Cited by 7 · see citing works

VALUE ADDED GEOCODED ENVISAT-ASAR PRODUCT SERVICE

Kosmann, D., Huber, M., Bollner, M., Raggam, H., & Small, D. (2004) · elib (German Aerospace Center) · Cited by 3 · see citing works

Evaluation of Different Machine Learning Methods and Deep-Learning Convolutional Neural Networks for Landslide Detection

Ghorbanzadeh, O., Blaschke, T., Gholamnia, K., Meena, S. R., Dirk Tiede, A., & Aryal, J. (2019) · Remote Sensing · doi:10.3390/rs11020196 · Cited by 891 · see citing works

Sentinel-1-based flood mapping: a fully automated processing chain

Twele, A., Cao, W., Plank, S., & Martinis, S. (2016) · International Journal of Remote Sensing · doi:10.1080/01431161.2016.1192304 · Cited by 641 · see citing works

Earthquake Damage Assessment of Buildings Using VHR Optical and SAR Imagery

Brunner, D., Lemoine, G., & Bruzzone, L. (2010) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2009.2038274 · Cited by 589 · see citing works

A comprehensive review of earthquake-induced building damage detection with remote sensing techniques

Dong, L., & Shan, J. (2013) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2013.06.011 · Cited by 528 · see citing works

A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters

Joyce, K. E., Belliss, S. E., Samsonov, S., McNeill, S. J. E., & Glassey, P. (2009) · Progress in Physical Geography Earth and Environment · doi:10.1177/0309133309339563 · Cited by 498 · see citing works

Convolutional Neural Networks for Multimodal Remote Sensing Data Classification

Wu, X., Hong, D., & Chanussot, J. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2021.3124913 · Cited by 422 · see citing works

A cloud detection algorithm for satellite imagery based on deep learning

Jeppesen, J. H., Jacobsen, R. H., Inceoglu, F., & Toftegaard, T. S. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.03.039 · Cited by 402 · see citing works

Understanding an urbanizing planet: Strategic directions for remote sensing

Zhu, Z., Zhou, Y., Seto, K. C., Stokes, E. C., Deng, C., Pickett, S. T. A., & Taubenböck, H. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.04.020 · Cited by 399 · see citing works

A neural network approach using multi-scale textural metrics from very high-resolution panchromatic imagery for urban land-use classification

Pacifici, F., Chini, M., & Emery, W. J. (2009) · Remote Sensing of Environment · doi:10.1016/j.rse.2009.02.014 · Cited by 379 · see citing works

A Novel Framework for the Design of Change-Detection Systems for Very-High-Resolution Remote Sensing Images

Bruzzone, L., & Bovolo, F. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2197169 · Cited by 332 · see citing works

Segment Optimization and Data-Driven Thresholding for Knowledge-Based Landslide Detection by Object-Based Image Analysis

Martha, T. R., Kerle, N., van Westen, C. J., Jetten, V. G., & Kumar, K. V. (2011) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2011.2151866 · Cited by 318 · see citing works

The benefits of very low earth orbit for earth observation missions

Crisp, N. H., Roberts, P. C. E., Livadiotti, S., Oiko, V. T. A., Edmondson, S., Haigh, S. J., Huyton, C., Sinpetru, L. A., Smith, K. L., Worrall, S. D., et al. (2020) · Progress in Aerospace Sciences · doi:10.1016/j.paerosci.2020.100619 · Cited by 255 · see citing works

Rapid Damage Assessment by Means of Multi-Temporal SAR — A Comprehensive Review and Outlook to Sentinel-1

Plank, S. (2014) · Remote Sensing · doi:10.3390/rs6064870 · Cited by 260 · see citing works

A Method for Automatic and Rapid Mapping of Water Surfaces from Sentinel-1 Imagery

Bioresita, F., Puissant, A., Stumpf, A., & Malet, J. (2018) · Remote Sensing · doi:10.3390/rs10020217 · Cited by 249 · see citing works

Global trends in satellite-based emergency mapping

Voigt, S., Tonolo, F. G., Lyons, J., Kučera, J., Jones, B. K., Schneiderhan, T., Platzeck, G., Kaku, K., Hazarika, M. K., Czaran, L., et al. (2016) · Science · doi:10.1126/science.aad8728 · Cited by 243 · see citing works

Volunteered geographic information for disaster management with application to rapid flood damage estimation

Poser, K., & Dransch, D. (2010) · Publication Database GFZ (GFZ German Research Centre for Geosciences) · Cited by 233 · see citing works

Landslides triggered by the June 2013 extreme rainfall event in parts of Uttarakhand state, India

Martha, T. R., Roy, P., Raj, K. B. G., Kumar, K. V., Diwakar, P. G., & Dadhwal, V. K. (2014) · Landslides · doi:10.1007/s10346-014-0540-7 · Cited by 230 · see citing works

Remote Sensing and Earthquake Damage Assessment: Experiences, Limits, and Perspectives

Dell’Acqua, F., & Gamba, P. E. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2196404 · Cited by 228 · see citing works

Tackling climate change with machine learning

Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works

Deep Learning and Earth Observation to Support the Sustainable Development Goals: Current approaches, open challenges, and future opportunities

Persello, C., Wegner, J. D., Hänsch, R., Tuia, D., Ghamisi, P., Koeva, M., & Camps‐Valls, G. (2022) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2021.3136100 · Cited by 197 · see citing works

Ship Classification in TerraSAR-X Images With Convolutional Neural Networks

Bentes, C., Velotto, D., & Tings, B. (2017) · IEEE Journal of Oceanic Engineering · doi:10.1109/joe.2017.2767106 · Cited by 166 · see citing works

Identification of damage in buildings based on gaps in 3D point clouds from very high resolution oblique airborne images

Vetrivel, A., Gerke, M., Kerle, N., & George Vosselman, A. (2015) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2015.03.016 · Cited by 164 · see citing works

Exploiting SAR and VHR Optical Images to Quantify Damage Caused by the 2003 Bam Earthquake

Chini, M., Pierdicca, N., & Emery, W. J. (2008) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2008.2002695 · Cited by 157 · see citing works

Unsupervised Extraction of Flood-Induced Backscatter Changes in SAR Data Using Markov Image Modeling on Irregular Graphs

Martinis, S., Twele, A., & Voigt, S. (2010) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2010.2052816 · Cited by 156 · see citing works

Environmental parameters associated with incidence and transmission of pathogenic Vibrio spp .

Brumfield, K. D., Usmani, M., Chen, K. M., Gangwar, M., Jutla, A., Huq, A., & Colwell, R. R. (2021) · Environmental Microbiology · doi:10.1111/1462-2920.15716 · Cited by 149 · see citing works

The state of the art of spaceborne remote sensing in flood management

Rahman, M. S., & Di, L. (2016) · Natural Hazards · doi:10.1007/s11069-016-2601-9 · Cited by 143 · see citing works

Semi-automated landslide inventory mapping from bitemporal aerial photographs using change detection and level set method

Li, Z. B., Shi, W., Myint, S. W., Lü, P., & Wang, Q. (2016) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.01.003 · Cited by 137 · see citing works

Fast Segmentation and Classification of Very High Resolution Remote Sensing Data Using SLIC Superpixels

Csillik, O. (2017) · Remote Sensing · doi:10.3390/rs9030243 · Cited by 136 · see citing works

A review on synthetic aperture radar-based building damage assessment in disasters

Ge, P., Gokon, H., & Meguro, K. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2020.111693 · Cited by 135 · see citing works

Detection of Temporary Flooded Vegetation Using Sentinel-1 Time Series Data

Tsyganskaya, V., Martinis, S., Marzahn, P., & Ludwig, R. (2018) · Remote Sensing · doi:10.3390/rs10081286 · Cited by 125 · see citing works

Flood Hazard and Flood Risk Assessment Using a Time Series of Satellite Images: A Case Study in Namibia

Skakun, S. V., Kussul, N., Шелестов, А. Ю., & Kussul, O. M. (2013) · Risk Analysis · doi:10.1111/risa.12156 · Cited by 130 · see citing works

Natural disasters detection in social media and satellite imagery: a survey

Said, N., Ahmad, K., Riegler, M., Pogorelov, K., Hassan, L., Ahmad, N., & Conci, N. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-07942-1 · Cited by 126 · see citing works

Automatic Structural Seismic Damage Assessment with Airborne Oblique Pictometry© Imagery

Gerke, M., & Kerle, N. (2011) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.77.9.885 · Cited by 123 · see citing works

Landslide Mapping in Vegetated Areas Using Change Detection Based on Optical and Polarimetric SAR Data

Plank, S., Twele, A., & Martinis, S. (2016) · Remote Sensing · doi:10.3390/rs8040307 · Cited by 121 · see citing works

Computational socioeconomics

Gao, J. G., Zhang, Y., & Zhou, T. (2019) · Physics Reports · doi:10.1016/j.physrep.2019.05.002 · Cited by 118 · see citing works

Risk, crisis and disaster management in hospitality and tourism: a comparative review

Ritchie, B. W., & Jiang, Y. (2021) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-12-2020-1480 · Cited by 120 · see citing works

Remote sensing contributing to assess earthquake risk: from a literature review towards a roadmap

Geiß, C., & Taubenböck, H. (2012) · Natural Hazards · doi:10.1007/s11069-012-0322-2 · Cited by 104 · see citing works

A Remote Sensing-Based Approach for Debris-Flow Susceptibility Assessment Using Artificial Neural Networks and Logistic Regression Modeling

Elkadiri, R., Sultan, M., Youssef, A. M., Elbayoumi, T. M., Chase, R. B., Bulkhi, A. B., & Al-Katheri, M. M. (2014) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2014.2337273 · Cited by 103 · see citing works

Rapid Mapping of Landslides on SAR Data by Attention U-Net

Nava, L., Bhuyan, K., Meena, S. R., Monserrat, O., & Catani, F. (2022) · Remote Sensing · doi:10.3390/rs14061449 · Cited by 103 · see citing works

Integrated assessment of the environmental impact of an IDP camp in Sudan based on very high resolution multi-temporal satellite imagery

Hagenlocher, M., Lang, S., & Dirk Tiede, A. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2012.08.010 · Cited by 102 · see citing works

Image4Act

Alam, F., Imran, M., & Ofli, F. (2017) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1145/3110025.3110164 · Cited by 102 · see citing works

Improving Landslide Detection on SAR Data Through Deep Learning

Nava, L., Monserrat, O., & Catani, F. (2021) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2021.3127073 · Cited by 101 · see citing works

Space-Based Earth Observations for Disaster Risk Management

Cozannet, G. L., Kervyn, M., Russo, S., Speranza, C. I., Ferrier, P., Foumelis, M., Lopez, T., & Modaressi, H. (2020) · Surveys in Geophysics · doi:10.1007/s10712-020-09586-5 · Cited by 97 · see citing works

Differential Evolution as a viable tool for satellite image registration

Falco, I. D., Cioppa, A. D., Maisto, D., & Tarantino, E. (2007) · Applied Soft Computing · doi:10.1016/j.asoc.2007.10.013 · Cited by 95 · see citing works

Mapping of flooded vegetation by means of polarimetric Sentinel-1 and ALOS-2/PALSAR-2 imagery

Plank, S., Jüssi, M., Martinis, S., & Twele, A. (2017) · International Journal of Remote Sensing · doi:10.1080/01431161.2017.1306143 · Cited by 94 · see citing works

Automatic Detection and Reconstruction of Building Radar Footprints From Single VHR SAR Images

Ferro, A., Brunner, D., & Bruzzone, L. (2012) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2012.2205156 · Cited by 91 · see citing works

Flood risks in urbanized areas – multi-sensoral approaches using remotely sensed data for risk assessment

Taubenböck, H., Wurm, M., Netzband, M., Zwenzner, H., Roth, A., Rahman, A., & Dech, S. W. (2011) · Natural hazards and earth system sciences · doi:10.5194/nhess-11-431-2011 · Cited by 91 · see citing works

Damage and geological assessment of the 18 September 2011 Mw 6.9 earthquake in Sikkim, India using very high resolution satellite data

Martha, T. R., Raj, K. B. G., & Kumar, K. V. (2014) · Geoscience Frontiers · doi:10.1016/j.gsf.2013.12.011 · Cited by 88 · see citing works

Cloud Computing in natural hazard modeling systems: Current research trends and future directions

Ujjwal, K. C., Garg, S., Hilton, J. E., Aryal, J., & Forbes-Smith, N. (2019) · International Journal of Disaster Risk Reduction · doi:10.1016/j.ijdrr.2019.101188 · Cited by 87 · see citing works

Remote Sensing, natural hazards and the contribution of ESA Sentinels missions

Poursanidis, D., & Chrysoulakis, N. (2017) · Remote Sensing Applications Society and Environment · doi:10.1016/j.rsase.2017.02.001 · Cited by 86 · see citing works

Big spatial data for urban and environmental sustainability

Huang, B., & Wang, J. (2020) · Geo-spatial Information Science · doi:10.1080/10095020.2020.1754138 · Cited by 86 · see citing works

Mapping and monitoring geological hazards using optical, LiDAR, and synthetic aperture RADAR image data

Joyce, K. E., Samsonov, S., Levick, S. R., Engelbrecht, J., & Belliss, S. E. (2014) · Natural Hazards · doi:10.1007/s11069-014-1122-7 · Cited by 85 · see citing works

Fusion of Sentinel-1 and Sentinel-2 image time series for permanent and temporary surface water mapping

Bioresita, F., Puissant, A., Stumpf, A., & Malet, J. (2019) · International Journal of Remote Sensing · doi:10.1080/01431161.2019.1624869 · Cited by 84 · see citing works

Object-Oriented Landslide Mapping Using ZY-3 Satellite Imagery, Random Forest and Mathematical Morphology, for the Three-Gorges Reservoir, China

Chen, T., Trinder, J. C., & Niu, R. (2017) · Remote Sensing · doi:10.3390/rs9040333 · Cited by 83 · see citing works

Landslides Mapped using Satellite Data in the Western Ghats of India After Excess Rainfall During August 2018

Martha, T. R., Roy, P., Khanna, K., Mrinalni, K., & Kumar, K. V. (2019) · Current Science · doi:10.18520/cs/v117/i5/804-812 · Cited by 82 · see citing works

Development of a comprehensive mangrove quality index (MQI) in Matang Mangrove: Assessing mangrove ecosystem health

Faridah-Hanum, I., Yusoff, F. M., Fitrianto, A., Ainuddin, N. A., Gandaseca, S., Samdin, Z., Kamarudin, N., Nurhidayu, S., Roslan, M. K. M., Hakeem, K. R., et al. (2019) · Ecological Indicators · doi:10.1016/j.ecolind.2019.02.030 · Cited by 81 · see citing works

Satellite-based damage mapping following the 2006 Indonesia earthquake—How accurate was it?

Kerle, N. (2010) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2010.07.004 · Cited by 81 · see citing works

Evidence and future potential of mobile phone data for disease disaster management

Cinnamon, J., Jones, S. K., & Adger, W. N. (2016) · Geoforum · doi:10.1016/j.geoforum.2016.07.019 · Cited by 80 · see citing works

Rapid Damage Assessment and Situation Mapping: Learning from the 2010 Haiti Earthquake

Voigt, S., Schneiderhan, T., Twele, A., Gähler, M., Stein, E., & Mehl, H. (2011) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.77.9.923 · Cited by 80 · see citing works

Improved Swin Transformer-Based Semantic Segmentation of Postearthquake Dense Buildings in Urban Areas Using Remote Sensing Images

Cui, L., Jing, X., Wang, Y., Huan, Y., Xu, Y., & Zhang, Q. (2022) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2022.3225150 · Cited by 76 · see citing works

Framework for Offline Flood Inundation Forecasts for Two-Dimensional Hydrodynamic Models

Bhola, P. K., Leandro, J., & Disse, M. (2018) · Geosciences · doi:10.3390/geosciences8090346 · Cited by 75 · see citing works

Machine Learning for Emergency Management: A Survey and Future Outlook

Kyrkou, C., Kolios, P., Theocharides, T., & Polycarpou, M. M. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3223186 · Cited by 78 · see citing works

Information Content of Very-High-Resolution SAR Images: Semantics, Geospatial Context, and Ontologies

Dumitru, C. O., Cui, S., Schwarz, G., & Datcu, M. P. (2014) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2014.2363595 · Cited by 66 · see citing works

Learning Change from Synthetic Aperture Radar Images: Performance Evaluation of a Support Vector Machine to Detect Earthquake and Tsunami-Induced Changes

Wieland, M., Liu, W., & Yamazaki, F. (2016) · Remote Sensing · doi:10.3390/rs8100792 · Cited by 66 · see citing works

Earthquake Damages Rapid Mapping by Satellite Remote Sensing Data: L'Aquila April 6th, 2009 Event

Dell’Acqua, F., Bignami, C., Chini, M., Lisini, G., Polli, D. A., & Stramondo, S. (2011) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2011.2162721 · Cited by 64 · see citing works

Applying Google earth engine for flood mapping and monitoring in the downstream provinces of Mekong river

Nghia, B. P. Q., Pal, I., Chollacoop, N., & Mukhopadhyay, A. (2022) · Progress in Disaster Science · doi:10.1016/j.pdisas.2022.100235 · Cited by 63 · see citing works

Remote Sensing Image Fusion Using Hierarchical Multimodal Probabilistic Latent Semantic Analysis

Fernández-Beltrán, R., Haut, J. M., Paoletti, M. E., Plaza, J., Plaza, A., & Pla, F. (2018) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2018.2881342 · Cited by 63 · see citing works

Development of flood inundation extent libraries over a range of potential flood levels: a practical framework for quick flood response

Bhatt, C. M., Rao, G. S., Diwakar, P. G., & Dadhwal, V. K. (2016) · Geomatics Natural Hazards and Risk · doi:10.1080/19475705.2016.1220025 · Cited by 62 · see citing works

Unsupervised Denoising for Satellite Imagery Using Wavelet Directional CycleGAN

Song, J., Jeong, J., Park, D.-S., Kim, H.-H., Seo, D., & Ye, J. C. (2021) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.3025601 · Cited by 57 · see citing works

Automatic Detection of Damaged Buildings after Earthquake Hazard by Using Remote Sensing and Information Technologies

Menderes, A., Erener, A., & Sarp, G. (2015) · Procedia Earth and Planetary Science · doi:10.1016/j.proeps.2015.08.063 · Cited by 60 · see citing works

Can the Future EnMAP Mission Contribute to Urban Applications? A Literature Survey

Heldens, W., Heiden, U., Esch, T., Stein, E., & Müller, A. (2011) · Remote Sensing · doi:10.3390/rs3091817 · Cited by 59 · see citing works

Multi-sensor feature fusion for very high spatial resolution built-up area extraction in temporary settlements

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European Gravity Service for Improved Emergency Management (EGSIEM)—from concept to implementation

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