{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T01:15:33Z","timestamp":1773105333186,"version":"3.50.1"},"reference-count":87,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study aims to present a technique that combines multi-sensor spatial data to monitor wetland areas after a flash-flood event in a Saharan arid region. To extract the most efficient information, seven satellite images (radar and optical) taken before and after the event were used. To achieve the objectives, this study used Sentinel-1 data to discriminate water body and soil roughness, and optical data to monitor the soil moisture after the event. The proposed method combines two approaches: one based on spectral processing, and the other based on categorical processing. The first step was to extract four spectral indices and utilize change vector analysis on multispectral diachronic images from three MSI Sentinel-2 images and two Landsat-8 OLI images acquired before and after the event. The second step was performed using pattern classification techniques, namely, linear classifiers based on support vector machines (SVM) with Gaussian kernels. The results of these two approaches were fused to generate a collaborative wetland change map. The application of co-registration and supervised classification based on textural and intensity information from Radar Sentinel-1 images taken before and after the event completes this work. The results obtained demonstrate the importance of the complementarity of multi-sensor images and a multi-approach methodology to better monitor changes to a wetland area after a flash-flood disaster.<\/jats:p>","DOI":"10.3390\/rs11091042","type":"journal-article","created":{"date-parts":[[2019,5,2]],"date-time":"2019-05-02T03:15:22Z","timestamp":1556766922000},"page":"1042","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["A Collaborative Change Detection Approach on Multi-Sensor Spatial Imagery for Desert Wetland Monitoring after a Flash Flood in Southern Morocco"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8781-8141","authenticated-orcid":false,"given":"Sofia","family":"Hakdaoui","sequence":"first","affiliation":[{"name":"Geo-Biodiversity and Natural Patrimony Laboratory, Geophysics, Natural Patrimony and Green Chemistry Research Center, Scientific Institute, Mohamed V University in Rabat. Av. Ibn Batouta B.P 703, Rabat 10106, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anas","family":"Emran","sequence":"additional","affiliation":[{"name":"Geo-Biodiversity and Natural Patrimony Laboratory, Geophysics, Natural Patrimony and Green Chemistry Research Center, Scientific Institute, Mohamed V University in Rabat. Av. Ibn Batouta B.P 703, Rabat 10106, Morocco"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9863-2054","authenticated-orcid":false,"given":"Biswajeet","family":"Pradhan","sequence":"additional","affiliation":[{"name":"The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia"},{"name":"Department of Energy and Mineral Resources Engineering, Choongmu-gwan, Sejong University, 209, Neungdong-roGwangin-gu, Seoul 05006, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7235-3225","authenticated-orcid":false,"given":"Chang-Wook","family":"Lee","sequence":"additional","affiliation":[{"name":"Division of Science Education, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon-si 24341, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3987-6643","authenticated-orcid":false,"given":"Salomon Cesar","family":"Nguemhe Fils","sequence":"additional","affiliation":[{"name":"Image Processing Laboratory (LTI), IRGM, P.O. Box 4110, Yaounde, Cameroon"},{"name":"Department of Earth Sciences, University of Yaounde I, P.O. Box 812, Yaounde, Cameroon"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1390","DOI":"10.1080\/02626667.2014.923970","article-title":"Evaluating flash flood warnings at ungauged locations using post-event surveys: A case study with the AIGA warning system","volume":"59","author":"Javelle","year":"2014","journal-title":"Hydrol. Sci. J."},{"key":"ref_2","first-page":"100051G","article-title":"Flash Flood Area mapping utilising Sentinel-1 Radar Data, Earth Resources and Environmental Remote Sensing\/GIS Applications VII","volume":"10005","author":"Psomiadis","year":"2017","journal-title":"Proc. SPIE"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"315","DOI":"10.4236\/ars.2016.54024","article-title":"Assessment of Land Erosion and Sediment Accumulation Caused by Runoff after a Flash-Flooding Storm Using Topographic Profiles and Spectral Indices","volume":"5","author":"Bannari","year":"2016","journal-title":"Adv. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Bannari, A., Ghadeer, A., El-Battay, A., Hameed, N.A., and Rouai, M. (2016). Detection of Areas Associated with Flash Floods and Erosion Caused by Rainfall Storm Using Topographic Attributes, Hydrologic Indices, and GIS. Global Changes and Natural Disaster Management: Geo-information Technologies, Springer International Publishing AG. Chapter: 13.","DOI":"10.1007\/978-3-319-51844-2_13"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3390","DOI":"10.3390\/rs4113390","article-title":"Unmanned aerial vehicle (UAV) for monitoring soil erosion in Morocco","volume":"4","author":"Marzolff","year":"2012","journal-title":"Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1080\/19475705.2017.1407368","article-title":"Assessment of the effects of training data selection on the landslide susceptibility mapping: A comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)","volume":"9","author":"Kalantar","year":"2018","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1016\/j.cageo.2011.12.014","article-title":"Support vector machine for multi-classification of mineral prospectivity areas","volume":"46","author":"Abedi","year":"2012","journal-title":"Comput. Geosci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"452","DOI":"10.1029\/94EO01076","article-title":"Flash floods in desert rivers: Studying the unexpected","volume":"75","author":"Reid","year":"2004","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Warner, T.T. (2004). Desert Meteorology, Cambridge University Press.","DOI":"10.1017\/CBO9780511535789"},{"key":"ref_11","unstructured":"Thomas, D.S.G. (1997). Channel form, flows and sediments in deserts. Arid Zone Geomorphology: Process, form and Change in Drylands, John Wiley."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1016\/S0022-1694(96)03183-6","article-title":"The role of the land surface in Sahelian climate: HAPEX-Sahel results and future research needs","volume":"188\u2013189","author":"Dolman","year":"1997","journal-title":"J. Hydrol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.still.2015.08.008","article-title":"Short-term soil loss by eolian erosion in response to different rainfed agricultural practices","volume":"155","author":"Tanner","year":"2016","journal-title":"Soil Tillage Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1002\/esp.1425","article-title":"Loss of soil and PM10 from agricultural fields associated with high winds on the Columbia Plateau","volume":"32","author":"Sharratt","year":"2007","journal-title":"Earth Surf. Proc. Land"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1038\/nature04058","article-title":"Field evidence for surface-wave-induced instability of sand dunes","volume":"437","author":"Elbelrhiti","year":"2005","journal-title":"Nature"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1038\/202759a0","article-title":"Origin of the coastal flats, the sabkha, off the Trucial coast, Persian Gulf","volume":"202","author":"Evans","year":"1964","journal-title":"Nature"},{"key":"ref_17","first-page":"141","article-title":"Spectral Analysis of a Core from the Sebkha of Sidi Mansour, Southern Tunisia: The Holocene Cyclostratigraphy","volume":"4","author":"Essefi","year":"2015","journal-title":"J. Remote Sens. GIS"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/j.yqres.2008.06.002","article-title":"Late Holocene high resolution palaeoclimatic reconstruction inferred from Sabkha Mhabeul, southeast Tunisia","volume":"70","author":"Marquer","year":"2008","journal-title":"Quat. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"7952","DOI":"10.3390\/rs6097952","article-title":"Continuity of reflectance data between Landsat-7 ETM+ and Landsat-8 OLI, for both Top-of-Atmosphere and surface reflectance: A study in the Australian landscape","volume":"6","author":"Flood","year":"2014","journal-title":"Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Richards, J.A. (1993). Remote Sensing Digital Image Analysis: An. Introduction, Springer.","DOI":"10.1007\/978-3-642-88087-2"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/0034-4257(92)90077-W","article-title":"An Algorithm for the Radiometric and Atmospheric Correction of AVHRR Data in the Solar Reflective Channels","volume":"41","author":"Teillet","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1007\/s12524-017-0677-7","article-title":"TM\/ETM+\/LDCM Images for studying land surface temperature (LST) interplay with impervious surfaces changes over time within the Douala Metropolis, Cameroon","volume":"46","author":"Mimba","year":"2018","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0034-4257(88)90116-2","article-title":"Radiometric scene normalization using pseudo invariant features","volume":"26","author":"Schott","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1080\/0143116031000150022","article-title":"Using Landsat 7 TM data acquired days after a flood event to delineate the maximum flood extent on a coastal floodplain","volume":"25","author":"Wang","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1109\/TGRS.2005.859952","article-title":"Post-flood damage evaluation using Landsat TM and ETM+ data integrated with DEM. IEEE Trans. Geosci","volume":"44","author":"Gianinetto","year":"2006","journal-title":"Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2516","DOI":"10.1109\/TGRS.2005.852082","article-title":"Multisensor approach to determine changes of wetland characteristics in semi-arid environments (Central Spain)","volume":"43","author":"Schmid","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Martinis, S. (2017, January 23\u201328). Improving flood mapping in arid areas using Sentinel-1 time series data. Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA.","DOI":"10.1109\/IGARSS.2017.8126927"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Martinis, S., Plank, S., and C\u2019wik, K. (2018). The Use of Sentinel-1 Time-Series Data to Improve Flood Monitoring in Arid Areas. Remote Sens., 10.","DOI":"10.3390\/rs10040583"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"9822","DOI":"10.3390\/rs70809822","article-title":"Multi-temporal independent component analysis and Landsat 8 for delineating maximum extent of the 2013 Colorado front range flood","volume":"7","author":"Chignell","year":"2015","journal-title":"Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2043","DOI":"10.1080\/01431160902942902","article-title":"Improving flood monitoring by the Robust AVHRR Technique (RAT) approach: The case of the April 2000 Hungary flood","volume":"31","author":"Lacava","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1890\/1051-0761(2003)013[0206:ESWMMR]2.0.CO;2","article-title":"Ecologically sustainable water management: Managing River flows for ecological integrity","volume":"13","author":"Richter","year":"2003","journal-title":"Ecol. Appl."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/S0169-555X(99)00023-9","article-title":"Quantifying geomorphic and riparian land cover changes either side of a large flood event using airborne remote sensing: River Tay, Scotland","volume":"29","author":"Bryant","year":"1999","journal-title":"Geomorphology"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Bannari, A., Ozbakir, B.A., and Langlois, A. (2007). Spatial Distribution Mapping of Vegetation Cover in Urban Environment Using TDVI for Quality of Life Monitoring. Int. Geosci. Remote Sens., 679\u2013682.","DOI":"10.1109\/IGARSS.2007.4422887"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.3390\/w7041437","article-title":"Urban Flood Mapping Based on Unmanned Aerial Vehicle Remote Sensing and Random Forest Classifier\u2014A Case of Yuyao, China","volume":"7","author":"Feng","year":"2015","journal-title":"Water"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"407","DOI":"10.14358\/PERS.82.6.407","article-title":"An assessment of algorithmic parameters affecting image classification accuracy by random forests","volume":"82","author":"Shi","year":"2016","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_36","first-page":"391","article-title":"Classification of remotely sensed data by an artificial neural network: issues related to training data characteristics","volume":"61","author":"Foody","year":"1995","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_37","first-page":"493","article-title":"Detecting subpixel woody vegetation in digital imagery using two artificial intelligence approaches","volume":"63","author":"Foschi","year":"1997","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1623\/hysj.48.3.381.45286","article-title":"Artificial neural network approach to flood forecasting in the river Arno","volume":"48","author":"Campolo","year":"2003","journal-title":"Hydrol. Sci. J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3091","DOI":"10.1080\/01431160310001648019","article-title":"Supervised image classification by MLP and RBF neural networks with and without an exhaustively defined set of classes","volume":"25","author":"Foody","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/S0022-1694(01)00353-5","article-title":"Quantitative flood forecasting using multisensory data and neural networks","volume":"246","author":"Kim","year":"2001","journal-title":"J. Hydrol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4907","DOI":"10.1080\/0143116031000114851","article-title":"The use of backpropagating artificial neural networks in land cover classification","volume":"24","author":"Kavzoglu","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1175\/1520-0450(1997)036<1176:PEFRSI>2.0.CO;2","article-title":"Precipitation estimation from remotely sensed information using artificial neural networks","volume":"36","author":"Hsu","year":"1997","journal-title":"J. Appl. Meteorol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2517","DOI":"10.1029\/95WR01955","article-title":"Artificial neural network modelling of the rainfall-runoff process","volume":"31","author":"Hsu","year":"1995","journal-title":"Water Resour. Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/S0022-1694(00)00228-6","article-title":"River flow prediction using artificial neural networks: Generalizations beyond the calibration range","volume":"233","author":"Imrie","year":"2000","journal-title":"J. Hydrol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"27","DOI":"10.14358\/PERS.77.1.27","article-title":"Parameterizing support vector machines for land cover classification","volume":"77","author":"Yang","year":"2011","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Sachdeva, S., Bhatia, T., and Verma, A.K. (2017, January 3\u20135). Flood susceptibility mapping using GIS-based support vector machine and particle swarm optimization: A case study in Uttarakhand (India). Proceedings of the 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Delhi, India.","DOI":"10.1109\/ICCCNT.2017.8204182"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jenvman.2018.03.089","article-title":"Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping","volume":"217","author":"Valavi","year":"2018","journal-title":"J. Environ. Manag."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.jhydrol.2014.03.008","article-title":"Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS","volume":"512","author":"Tehrany","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_49","first-page":"75","article-title":"Albedo-NDVI space and remote sensing synthesis index models for desertification monitoring","volume":"26","author":"Zeng","year":"2006","journal-title":"Sci. Geogr. Sin."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2029","DOI":"10.1016\/j.proenv.2011.09.318","article-title":"The Construction and Application of an Albedo-NDVI Based Desertification Monitoring Model","volume":"10","author":"Zongyi","year":"2011","journal-title":"Procedia Environ. Sci."},{"key":"ref_51","unstructured":"Dobos, E. (2007). Albedo Encyclopedia of Soil Science, Springer. [2nd ed.]. ISBN: 978-0-8493-3830-4 eBook ISBN 978-1-4398-7062-4."},{"key":"ref_52","unstructured":"Asrar, G. (1989). Soil Reflectance. Theory and Applications of Optical Remote Sensing, John Wiley & Sons, Inc."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalized difference water index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.rse.2013.08.029","article-title":"Automated Water Extraction Index: A new technique for surface water mapping using Landsat imagery","volume":"140","author":"Feyisa","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Notti, D., Giordan, D., Cal\u00f3, F., Pepe, A., Zucca, F., and Galve, J.P. (2018). Potential and Limitations of Open Satellite Data for Flood Mapping. Remote Sens., 10.","DOI":"10.20944\/preprints201807.0624.v1"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"722","DOI":"10.2136\/sssaj2002.7220","article-title":"Moisture Effects on Soil Reflectance","volume":"66","author":"Lobell","year":"2002","journal-title":"Soil Sci. Am. J."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2007GL031021","article-title":"NMDI: A Normalized Multi-Band Drought Index for Monitoring Soil and Vegetation Moisture with Satellite Remote Sensing","volume":"34","author":"Wang","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"4340","DOI":"10.1109\/JSTARS.2014.2347313","article-title":"Monitoring Spatiotemporal Surface Soil Moisture Variations during Dry Seasons in Central America With Multisensor Cascade Data Fusion","volume":"7","author":"Chen","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.jaridenv.2015.04.006","article-title":"Assessing desertification risk in the semi-arid highlands of central Mexico","volume":"120","author":"Khalidou","year":"2015","journal-title":"J. Arid Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1254","DOI":"10.1109\/36.536541","article-title":"Designing optimal spectral indexes for remote sensing applications","volume":"3434","author":"Verstraete","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_61","unstructured":"Jensen, J.R. (2000). Remote Sensing of the Environment: An. Earth Resource Perspective, Prentice-Hall."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1007\/s12665-015-4830-8","article-title":"Flash flood susceptibility assessment in Jeddah city (Kingdom of 773 Saudi Arabia) using bivariate and multivariate statistical models","volume":"75","author":"Youssef","year":"2016","journal-title":"Environ. Earth Sci."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"369","DOI":"10.14358\/PERS.69.4.369","article-title":"Land-use\/land-cover change detection using improved change-vector analysis","volume":"69","author":"Chen","year":"2003","journal-title":"Photogram. Eng. Remote Sens."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.rse.2006.06.003","article-title":"A comparative study of NOAA\u2013AVHRR derived drought indices using change vector analysis","volume":"105","author":"Bayarjargal","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1111\/jfr3.12303","article-title":"Multi-temporal synthetic aperture radar flood mapping using change detection","volume":"11","author":"Clement","year":"2017","journal-title":"J. Flood Risk Manag."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.pce.2010.12.009","article-title":"Towards an automated SAR-based flood monitoring system: Lessons learned from two case studies","volume":"36","author":"Matgen","year":"2011","journal-title":"Phys. Chem. Earth"},{"key":"ref_67","unstructured":"Martinis, S. (2010). Automatic Near Real-Time Flood Detection in High Resolution X-Band Synthetic Aperture Radar Satellite Data Using Context-Based Classification on Irregular Graphs. [Ph.D. Thesis, LMU M\u00fcnchen: Faculty of Geosciences]."},{"key":"ref_68","first-page":"69","article-title":"Flood mapping of Danube River at Romania using single and multi-date ERS2-SAR images","volume":"18","author":"Gan","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_69","unstructured":"Ardiana, S., Ahmad, A., and Kadir, O. (2000). Capability of Radarsat Data in Monsoon Flood Monitoring. Proc. GIS Dev., 1\u20136."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/j.rse.2006.11.012","article-title":"Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data","volume":"108","author":"Martinez","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_71","first-page":"317","article-title":"Detection of lowland flooding using active microwave systems","volume":"51","author":"Ormsby","year":"1985","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"64100Z","DOI":"10.1117\/12.693947","article-title":"Advantage of multi-polarized SAR data for flood extent delineation","volume":"6410","author":"Rao","year":"2006","journal-title":"Proc. SPIE"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.jhydrol.2007.06.024","article-title":"Deriving distributed roughness values from satellite radar data for flood inundation modellin","volume":"344","author":"Schumann","year":"2007","journal-title":"J. Hydrol."},{"key":"ref_74","unstructured":"Vilches, J.P. (2013). Detection of Areas Affected by Flooding River using SAR images. Seminar: Master in Space Applications for Emergency Early Warning and Response, National University of Cordoba."},{"key":"ref_75","unstructured":"Voigt, S., Martinis, S., Zwenzner, H., Hahmann, T., Twele, A., and Schneiderhan, T. (2008, January 6\u20138). Extraction of flood masks using satellite based very high-resolution SAR data for flood management and modeling. Proceedings of the 4th International Symposium on Flood Defense Managing Flood Risk Reliability and Vulnerability, Toronto, ON, Canada."},{"key":"ref_76","unstructured":"Touzi, R., H\u00e9lie, R., and Filfil, R. (2005, January 25\u201329). On the use of polarimetric SAR information for extraction of wetland indicators. Proceedings of the IGARSS\u201905, Seoul, Korea."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1080\/07038992.1996.10874644","article-title":"The role of Earth observation technologies in flood mapping: A Manitoba case study","volume":"22","author":"Barber","year":"1996","journal-title":"Can. J. Remote Sens."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.rse.2005.03.012","article-title":"Towards operational monitoring of a northern wetland using geomatics-based techniques","volume":"97","author":"Toyra","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/S0034-4257(96)00157-5","article-title":"Monitoring of local environmental conditions with SIR-C\/XSAR","volume":"59","author":"Pultz","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1111\/jawr.12082","article-title":"Coastal flood inundation monitoring with satellite C-band and L-band Synthetic Aperture Radar data","volume":"49","author":"Ramsey","year":"2013","journal-title":"J. Am. Water Resour. Assoc."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/0034-4257(95)00191-3","article-title":"Anomalies on geologic maps from multispectral and textural classification: The bleida mining district (Morocco)","volume":"57","author":"Emran","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1080\/01431169608949052","article-title":"Spectral signatures and textures in geological mapping by direct HRV-XS classification of SPOT images of deserts-The mining sector of Zgounder (Anti-Atlas, Morocco)","volume":"17","author":"Emran","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"4407","DOI":"10.1080\/01431161.2011.552923","article-title":"Death to Kappa: Birth of quantity disagreement and allocation disagreement for accuracy assessment","volume":"32","author":"Pontius","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Ayala-Izurieta, J.E., M\u00e1rquez, C.O., Garc\u00eda, V.J., Recalde-Moreno, C.G., Rodr\u00edguez-Llerena, M.V., and Dami\u00e1n-Carri\u00f3n, D.A. (2017). Land Cover Classification in an Ecuadorian Mountain Geosystem Using a Random Forest Classifier, Spectral Vegetation Indices, and Ancillary Geographic Data. Geosciences, 7.","DOI":"10.3390\/geosciences7020034"},{"key":"ref_85","first-page":"205","article-title":"Change detection approaches for flood extent mapping: How to select the most adequate reference image from online archives?","volume":"19","author":"Hostache","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.ecolind.2019.01.025","article-title":"Changes in wetlands and surrounding land cover in a desert area under the influences of human and climatic factors: A case study of the Hongjian Nur region","volume":"101","author":"Xiua","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Guo, M., Li, J., Sheng, C., Xu, J., and Wu, L. (2017). A Review of Wetland Remote Sensing. Sensors, 17.","DOI":"10.3390\/s17040777"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/9\/1042\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:48:42Z","timestamp":1760186922000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/9\/1042"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,1]]},"references-count":87,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2019,5]]}},"alternative-id":["rs11091042"],"URL":"https:\/\/doi.org\/10.3390\/rs11091042","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,1]]}}}