{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T00:08:12Z","timestamp":1767917292708,"version":"3.49.0"},"reference-count":61,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NASA Science Mission Directorate","award":["80NSSC20K0164"],"award-info":[{"award-number":["80NSSC20K0164"]}]},{"name":"NASA Science Mission Directorate","award":["80NSSC19K1109"],"award-info":[{"award-number":["80NSSC19K1109"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Hindu Kush Himalaya (HKH) is one of the most flood-prone regions in the world, yet heavy cloud cover and limited in situ observations have hampered efforts to monitor the impact of heavy rainfall, flooding, and inundation during severe weather events. This paper introduces HydroSAR, a Sentinel-1 SAR-based hazard monitoring service which was co-developed with in-region partners to provide year-round, low-latency weather hazard information across the HKH. This paper describes the end user-focused concept and overall design of the HydroSAR service. It introduces the main processing algorithms behind HydroSAR\u2019s broad product portfolio, which includes qualitative visual layers as well as quantitative products measuring the surface water extent and water depth. We summarize the cloud-based implementation of the developed service, which provides the capability to scale automatically with the event size. A performance assessment of our quantitative algorithms is described, demonstrating the capabilities to map the flood extent and water depth with an accuracy of &gt;90% and &lt;1 m, respectively. An application of the HydroSAR service to the 2023 South Asia monsoon seasons showed that monsoon floods peaked near 6 August 2023 and covered 11.6% of Bangladesh in water. At the peak of the flood season, nearly 13.5% of Bangladesh\u2019s agriculture areas were affected.<\/jats:p>","DOI":"10.3390\/rs16173244","type":"journal-article","created":{"date-parts":[[2024,9,2]],"date-time":"2024-09-02T07:59:40Z","timestamp":1725263980000},"page":"3244","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["HydroSAR: A Cloud-Based Service for the Monitoring of Inundation Events in the Hindu Kush Himalaya"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2491-526X","authenticated-orcid":false,"given":"Franz J.","family":"Meyer","sequence":"first","affiliation":[{"name":"Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK 99775, USA"},{"name":"Alaska Satellite Facility, University of Alaska Fairbanks, Fairbanks, AK 99775, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1212-2665","authenticated-orcid":false,"given":"Lori A.","family":"Schultz","sequence":"additional","affiliation":[{"name":"NASA Marshall Space Flight Center, Huntsville, AL 35812, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5857-2883","authenticated-orcid":false,"given":"Batuhan","family":"Osmanoglu","sequence":"additional","affiliation":[{"name":"NASA Goddard Space Flight Center, 8800 Greenbelt Rd, Greenbelt, MD 20771, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9348-693X","authenticated-orcid":false,"given":"Joseph H.","family":"Kennedy","sequence":"additional","affiliation":[{"name":"Alaska Satellite Facility, University of Alaska Fairbanks, Fairbanks, AK 99775, USA"}]},{"given":"MinJeong","family":"Jo","sequence":"additional","affiliation":[{"name":"NASA Goddard Space Flight Center, 8800 Greenbelt Rd, Greenbelt, MD 20771, USA"},{"name":"University of Maryland, Baltimore County, Baltimore, MD 21250, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4467-0148","authenticated-orcid":false,"given":"Rajesh B.","family":"Thapa","sequence":"additional","affiliation":[{"name":"International Centre for Integrated Mountain Development, G.P.O. Box 3226, Lalitpur 44700, Nepal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7463-2973","authenticated-orcid":false,"given":"Jordan R.","family":"Bell","sequence":"additional","affiliation":[{"name":"NASA Marshall Space Flight Center, Huntsville, AL 35812, USA"}]},{"given":"Sudip","family":"Pradhan","sequence":"additional","affiliation":[{"name":"International Centre for Integrated Mountain Development, G.P.O. Box 3226, Lalitpur 44700, Nepal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0653-7736","authenticated-orcid":false,"given":"Manish","family":"Shrestha","sequence":"additional","affiliation":[{"name":"International Centre for Integrated Mountain Development, G.P.O. Box 3226, Lalitpur 44700, Nepal"}]},{"given":"Jacquelyn","family":"Smale","sequence":"additional","affiliation":[{"name":"Alaska Satellite Facility, University of Alaska Fairbanks, Fairbanks, AK 99775, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2130-4527","authenticated-orcid":false,"given":"Heidi","family":"Kristenson","sequence":"additional","affiliation":[{"name":"Alaska Satellite Facility, University of Alaska Fairbanks, Fairbanks, AK 99775, USA"}]},{"given":"Brooke","family":"Kubby","sequence":"additional","affiliation":[{"name":"Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK 99775, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-5647-5557","authenticated-orcid":false,"given":"Thomas J.","family":"Meyer","sequence":"additional","affiliation":[{"name":"Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK 99775, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Vaidya, R.A., Shrestha, M.S., Nasab, N., Gurung, D.R., Kozo, N., Pradhan, N.S., and Wasson, R.J. (2019). Disaster risk reduction and building resilience in the Hindu Kush Himalaya. The Hindu Kush Himalaya Assessment: Mountains, Climate Change, Sustainability and People, Springer.","DOI":"10.1007\/978-3-319-92288-1_11"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Bajracharya, B., Thapa, R.B., and Matin, M.A. (2021). Earth Observation Science and Applications for Risk Reduction and Enhanced Resilience in Hindu Kush Himalaya Region: A Decade of Experience from SERVIR, Springer Nature.","DOI":"10.1007\/978-3-030-73569-2"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1080\/07900627.2015.1023891","article-title":"Establishment of a regional flood information system in the Hindu Kush Himalayas: Challenges and opportunities","volume":"31","author":"Shrestha","year":"2015","journal-title":"Int. J. Water Resour. Dev."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Uddin, K., Matin, M.A., and Meyer, F.J. (2019). Operational flood mapping using multi-temporal Sentinel-1 SAR images: A case study from Bangladesh. Remote Sens., 11.","DOI":"10.3390\/rs11131581"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Potin, P., Bargellini, P., Laur, H., Rosich, B., and Schmuck, S. (2012, January 22\u201327). Sentinel-1 mission operations concept. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6351183"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kellogg, K., Hoffman, P., Standley, S., Shaffer, S., Rosen, P., Edelstein, W., Dunn, C., Baker, C., Barela, P., and Shen, Y. (2020, January 7\u201314). NASA-ISRO synthetic aperture radar (NISAR) mission. Proceedings of the 2020 IEEE Aerospace Conference, Big Sky, MT, USA.","DOI":"10.1109\/AERO47225.2020.9172638"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"303","DOI":"10.5194\/nhess-9-303-2009","article-title":"Towards operational near real-time flood detection using a split-based automatic thresholding procedure on high resolution TerraSAR-X data","volume":"9","author":"Martinis","year":"2009","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"035002","DOI":"10.1088\/1748-9326\/9\/3\/035002","article-title":"Flood extent mapping for Namibia using change detection and thresholding with SAR","volume":"9","author":"Long","year":"2014","journal-title":"Environ. Res. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Seitz, F., Hedman, K., Meyer, F.J., and Lee, H. (2014). Multi-sensor space observation of heavy flood and drought conditions in the Amazon region. Earth on the Edge: Science for a Sustainable Planet: Proceedings of the IAG General Assembly, Melbourne, Australia, 28 June\u20132 July 2011, Springer.","DOI":"10.1007\/978-3-642-37222-3_41"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.isprsjprs.2014.05.009","article-title":"Integrating SAR and derived products into operational volcano monitoring and decision support systems","volume":"100","author":"Meyer","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ajadi, O.A., Meyer, F.J., and Webley, P.W. (2016). Change detection in synthetic aperture radar images using a multiscale-driven approach. Remote Sens., 8.","DOI":"10.3390\/rs8060482"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2990","DOI":"10.1080\/01431161.2016.1192304","article-title":"Sentinel-1-based flood mapping: A fully automated processing chain","volume":"37","author":"Twele","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Tran, K.H., Menenti, M., and Jia, L. (2022). Surface water mapping and flood monitoring in the Mekong Delta using sentinel-1 SAR time series and Otsu threshold. Remote Sens., 14.","DOI":"10.3390\/rs14225721"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Qiu, J., Cao, B., Park, E., Yang, X., Zhang, W., and Tarolli, P. (2021). Flood monitoring in rural areas of the Pearl River Basin (China) using Sentinel-1 SAR. Remote Sens., 13.","DOI":"10.3390\/rs13071384"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Martinis, S., Wieland, M., and R\u00e4ttich, M. (2021). An Automatic System for Near-Real Time Flood Extent and Duration Mapping Based on Multi-Sensor Satellite Data. Earth Observation for Flood Applications, Elsevier.","DOI":"10.1016\/B978-0-12-819412-6.00002-X"},{"key":"ref_16","first-page":"23","article-title":"A threshold selection method from gray-level histograms","volume":"11","author":"Otsu","year":"1975","journal-title":"Automatica"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Uddin, K., Matin, M.A., and Thapa, R.B. (2021). Rapid flood mapping using multi-temporal sar images: An example from Bangladesh. A Decade of Experience from SERVIR, Springer.","DOI":"10.1007\/978-3-030-73569-2_10"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1007\/s41748-022-00295-0","article-title":"Delineating flood zones upon employing synthetic aperture data for the 2020 flood in Bangladesh","volume":"6","author":"Aziz","year":"2022","journal-title":"Earth Syst. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1016\/j.isprsjprs.2020.06.011","article-title":"Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine","volume":"166","author":"Singha","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Pandey, A.C., Kaushik, K., and Parida, B.R. (2022). Google Earth Engine for large-scale flood mapping using SAR data and impact assessment on agriculture and population of Ganga-Brahmaputra basin. Sustainability, 14.","DOI":"10.3390\/su14074210"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Soria-Ruiz, J., Fernandez-Ordo\u00f1ez, Y.M., Ambrosio-Ambrosio, J.P., Escalona-Maurice, M.J., Medina-Garc\u00eda, G., Sotelo-Ruiz, E.D., and Ramirez-Guzman, M.E. (2022). Flooded extent and depth analysis using optical and SAR remote sensing with machine learning algorithms. Atmosphere, 13.","DOI":"10.3390\/atmos13111852"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"113367","DOI":"10.1016\/j.jenvman.2021.113367","article-title":"Basin-wide flood depth and exposure mapping from SAR images and machine learning models","volume":"297","author":"Hao","year":"2021","journal-title":"J. Environ. Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.enggeo.2017.01.003","article-title":"The evolution (2010\u20132015) and engineering mitigation of a rockslide-dammed lake (Hunza River, Pakistan); characterisation by analytical remote sensing","volume":"220","author":"Delaney","year":"2017","journal-title":"Eng. Geol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3241","DOI":"10.1109\/ACCESS.2023.3234742","article-title":"Flood depth estimation in agricultural lands from L and C-band synthetic aperture radar images and digital elevation model","volume":"11","author":"Surampudi","year":"2023","journal-title":"IEEE Access"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ozaki, M. (2016). Disaster Risk Financing in Bangladesh, Asian Development Bank.","DOI":"10.2139\/ssrn.2941319"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1007\/s12571-016-0607-5","article-title":"Household food security in the face of climate change in the Hindu-Kush Himalayan region","volume":"8","author":"Hussain","year":"2016","journal-title":"Food Secur."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/s13753-012-0011-5","article-title":"Optimization of threshold ranges for rapid flood inundation mapping by evaluating backscatter profiles of high incidence angle SAR images","volume":"3","author":"Manjusree","year":"2012","journal-title":"Int. J. Disaster Risk Sci."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Thapa, R.B., Bajracharya, B., Matin, M.A., Anderson, E., and Epanchin, P. (2021). Service planning approach and its application. A Decade of Experience from SERVIR, Springer.","DOI":"10.1007\/978-3-030-73569-2_2"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1659\/MRD-JOURNAL-D-13-00018.1","article-title":"ICIMOD\u2019s strategy for delivering high-quality research and achieving impact for sustainable mountain development","volume":"33","author":"Molden","year":"2013","journal-title":"Mt. Res. Dev."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Cigna, F., and Xie, H. (2020). Imaging floods and glacier geohazards with remote sensing. Remote Sens., 12.","DOI":"10.3390\/rs12233874"},{"key":"ref_31","unstructured":"Bell, J., Kubby, B., Meyer, F., and Yadav, S. (2021, January 13\u201317). Identifying and Mapping Agricultural Areas Using Synthetic Aperture Radar Time Series. Proceedings of the AGU Fall Meeting, New Orleans, LA, USA."},{"key":"ref_32","unstructured":"(2024, March 03). Copernicus DEM. Available online: https:\/\/dataspace.copernicus.eu\/explore-data\/data-collections\/copernicus-contributing-missions\/collections-description\/COP-DEM."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3546","DOI":"10.1109\/JSTARS.2021.3062286","article-title":"TanDEM-X: 10 years of formation flying bistatic SAR interferometry","volume":"14","author":"Zink","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.isprsjprs.2018.02.017","article-title":"Accuracy assessment of the global TanDEM-X Digital Elevation Model with GPS data","volume":"139","author":"Wessel","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1029\/2008EO100001","article-title":"New global hydrography derived from spaceborne elevation data","volume":"89","author":"Lehner","year":"2008","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Buchhorn, M., Lesiv, M., Tsendbazar, N.E., Herold, M., Bertels, L., and Smets, B. (2020). Copernicus global land cover layers\u2014Collection 2. Remote Sens., 12.","DOI":"10.3390\/rs12061044"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.jhydrol.2011.03.051","article-title":"Height Above the Nearest Drainage\u2014A hydrologically relevant new terrain model","volume":"404","author":"Nobre","year":"2011","journal-title":"J. Hydrol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3275","DOI":"10.5194\/hess-15-3275-2011","article-title":"Hydrological landscape classification: Investigating the performance of HAND based landscape classifications in a central European meso-scale catchment","volume":"15","author":"Gharari","year":"2011","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_39","unstructured":"Hogenson, K., Kristenson, H., Kennedy, J., Johnston, A., Rine, J., Logan, T., Zhu, J., Williams, F., Herrmann, J., and Smale, J. (2024). Hybrid Pluggable Processing Pipeline (HyP3): A Cloud-Native Infrastructure for Generic Processing of SAR Data, Zenodo."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"493","DOI":"10.5589\/m11-059","article-title":"Terrain-flattened gamma nought Radarsat-2 backscatter","volume":"37","author":"Small","year":"2011","journal-title":"Can. J. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3147472","article-title":"An area-based projection algorithm for SAR radiometric terrain correction and geocoding","volume":"60","author":"Shiroma","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3081","DOI":"10.1109\/TGRS.2011.2120616","article-title":"Flattening gamma: Radiometric terrain correction for SAR imagery","volume":"49","author":"Small","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Flores-Anderson, A.I., Parache, H.B., Martin-Arias, V., Jim\u00e9nez, S.A., Herndon, K., Mehlich, S., Meyer, F.J., Agarwal, S., Ilyushchenko, S., and Agarwal, M. (2023). Evaluating SAR Radiometric Terrain Correction Products: Analysis-Ready Data for Users. Remote Sens., 15.","DOI":"10.3390\/rs15215110"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Truckenbrodt, J., Freemantle, T., Williams, C., Jones, T., Small, D., Dubois, C., Thiel, C., Rossi, C., Syriou, A., and Giuliani, G. (2019). Towards Sentinel-1 SAR analysis-ready data: A best practices assessment on preparing backscatter data for the cube. Data, 4.","DOI":"10.3390\/data4030093"},{"key":"ref_45","first-page":"102214","article-title":"Assessing SAR C-band data to effectively distinguish modified land uses in a heavily disturbed Amazon forest","volume":"94","author":"Nicolau","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1109\/LGRS.2012.2192093","article-title":"DEM-based SAR pixel-area estimation for enhanced geocoding refinement and radiometric normalization","volume":"10","author":"Frey","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.isprsjprs.2014.07.014","article-title":"A fully automated TerraSAR-X based flood service","volume":"104","author":"Martinis","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s11069-017-3036-7","article-title":"Decadal flood trends in Bangladesh from extensive hydrographic data","volume":"90","author":"Sciance","year":"2018","journal-title":"Nat. Hazards"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Meyer, F.J., Schultz, L., Bell, J., Molthan, A.L., Osmanoglu, B., Jo, M., Lundell, E., Chapman, B.D., Kubby, B., and Meyer, T. (2021, January 11\u201316). Monitoring Weather-Related Hazards Using the HydroSAR Service: Application to the 2020 South Asia Monsoon Season. Proceedings of the 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, Brussels, Belgium.","DOI":"10.1109\/IGARSS47720.2021.9553203"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Olson, B., and Shehu, A. (2012, January 4\u20137). Efficient basin hopping in the protein energy surface. Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine, Philadelphia, PA, USA.","DOI":"10.1109\/BIBM.2012.6392655"},{"key":"ref_52","unstructured":"Hogenson, K., Arko, S.A., Buechler, B., Hogenson, R., Herrmann, J., and Geiger, A. (2016, January 12\u201316). Hybrid Pluggable Processing Pipeline (HyP3): A cloud-based infrastructure for generic processing of SAR data. Proceedings of the AGU Fall Meeting, San Francisco, CA, USA."},{"key":"ref_53","first-page":"228","article-title":"An introduction to docker and analysis of its performance","volume":"17","author":"Rad","year":"2017","journal-title":"Int. J. Comput. Sci. Netw. Secur. (IJCSNS)"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"4013","DOI":"10.5194\/hess-26-4013-2022","article-title":"Flood forecasting with machine learning models in an operational framework","volume":"26","author":"Nevo","year":"2022","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"e2019GL086933","DOI":"10.1029\/2019GL086933","article-title":"The 2019 Mississippi and Missouri River flooding and its impact on atmospheric boundary layer dynamics","volume":"47","author":"Pal","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalised 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_57","unstructured":"Fahrland, E., Jacob, P., Schrader, H., and Kahabka, H. (2020). Copernicus Digital Elevation Model\u2014Product Handbook, Airbus Defence and Space\u2014Intelligence."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1007\/s41748-021-00221-w","article-title":"Geo-spatial analysis for flash flood susceptibility mapping in the North-East Haor (Wetland) Region in Bangladesh","volume":"5","author":"Haque","year":"2021","journal-title":"Earth Syst. Environ."},{"key":"ref_59","first-page":"53","article-title":"Floods in Bangladesh: A comparative hydrological investigation on two catastrophic events","volume":"8","author":"AM","year":"2003","journal-title":"J. Fac. Environ. Sci. Technol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2548","DOI":"10.1080\/01431161.2014.883098","article-title":"The PROBA-V mission: The space segment","volume":"35","author":"Francois","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"12","DOI":"10.3126\/pjri.v3i1.37432","article-title":"Assessment of Natural Hazard in the Himalayas: A Case Study of the Seti River Flash Flood 2012","volume":"3","author":"Poudel","year":"2021","journal-title":"Prithvi J. Res. Innov."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/17\/3244\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:46:47Z","timestamp":1760111207000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/17\/3244"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,1]]},"references-count":61,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2024,9]]}},"alternative-id":["rs16173244"],"URL":"https:\/\/doi.org\/10.3390\/rs16173244","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,1]]}}}