{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T20:38:02Z","timestamp":1774039082374,"version":"3.50.1"},"reference-count":160,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T00:00:00Z","timestamp":1770681600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100020362","name":"INTERREG IVB NWE","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100020362","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100013276","name":"Interreg","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100013276","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Environmental Modelling &amp; Software"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.envsoft.2026.106910","type":"journal-article","created":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T16:45:59Z","timestamp":1770741959000},"page":"106910","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Computer vision in flash flood forecasting: A narrative review of applications, integration pathways, and future directions"],"prefix":"10.1016","volume":"198","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4444-4125","authenticated-orcid":false,"given":"Hasitha","family":"Adikari","sequence":"first","affiliation":[]},{"given":"Christian","family":"O\u2019Leary","sequence":"additional","affiliation":[]},{"given":"Joe","family":"Harrington","sequence":"additional","affiliation":[]},{"given":"Conor","family":"Lynch","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b1","doi-asserted-by":"crossref","first-page":"167","DOI":"10.5194\/esurf-13-167-2025","article-title":"Automatic detection of floating instream large wood in videos using deep learning","volume":"13","author":"Aarnink","year":"2025","journal-title":"Earth Surf. Dyn."},{"key":"10.1016\/j.envsoft.2026.106910_b2","first-page":"62","article-title":"Image compression based on deep learning: A review","author":"Abdulazeez","year":"2021","journal-title":"Asian J. Res. Comput. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b3","article-title":"Deep learning for rapid identification and assessment of disaster areas based on satellite images","volume":"17","author":"Aboosh","year":"2024","journal-title":"Int. J. Comput. Digit. Syst."},{"key":"10.1016\/j.envsoft.2026.106910_b4","series-title":"2020 5th International Conference on Information Technology Research (ICITR)","first-page":"1","article-title":"An automated decision-making framework for precipitation-related workflows","author":"Adikari","year":"2020"},{"issue":"19","key":"10.1016\/j.envsoft.2026.106910_b5","doi-asserted-by":"crossref","first-page":"2984","DOI":"10.3390\/w14192984","article-title":"Flood inundation modeling by integrating HEC\u2013RAS and satellite imagery: a case study of the indus river basin","volume":"14","author":"Afzal","year":"2022","journal-title":"Water"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b6","first-page":"1","article-title":"Toward brague river flood modelling 1: Validity of a simplified 1D-2D hydraulic model to flash flood understanding","volume":"3","author":"Ah-Woane","year":"2025","journal-title":"Digit. Water"},{"key":"10.1016\/j.envsoft.2026.106910_b7","series-title":"Transformer-based flood scene segmentation for developing countries","author":"AhanM.","year":"2022"},{"issue":"9","key":"10.1016\/j.envsoft.2026.106910_b8","doi-asserted-by":"crossref","first-page":"1283","DOI":"10.3390\/w17091283","article-title":"A deep learning framework for flash-flood-runoff prediction: integrating CNN-RNN with neural ordinary differential equations (ODEs)","volume":"17","author":"Alkaabi","year":"2025","journal-title":"Water"},{"key":"10.1016\/j.envsoft.2026.106910_b9","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2025.133688","article-title":"A hybrid framework for real-time flash flood forecasting in small ungauged catchments: Integrating hydrodynamic simulations with LSTM networks","volume":"661","author":"An","year":"2025","journal-title":"J. Hydrol."},{"key":"10.1016\/j.envsoft.2026.106910_b10","series-title":"2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS)","first-page":"1","article-title":"Deep learning-based adaptive image compression system for a real-world scenario","author":"Anelli","year":"2020"},{"issue":"22","key":"10.1016\/j.envsoft.2026.106910_b11","doi-asserted-by":"crossref","first-page":"5012","DOI":"10.3390\/s19225012","article-title":"Computer vision and IoT-based sensors in flood monitoring and mapping: a systematic review","volume":"19","author":"Arshad","year":"2019","journal-title":"Sensors"},{"key":"10.1016\/j.envsoft.2026.106910_b12","series-title":"2023 12th International Conference on System Modeling & Advancement in Research Trends (SMART)","first-page":"315","article-title":"IP and IoT-based waterside surveillance for early floods alarming system","author":"Bachani","year":"2023"},{"issue":"12","key":"10.1016\/j.envsoft.2026.106910_b13","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1109\/TPAMI.2016.2644615","article-title":"SegNet: A deep convolutional encoder-decoder architecture for image segmentation","volume":"39","author":"Badrinarayanan","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106910_b14","doi-asserted-by":"crossref","first-page":"191","DOI":"10.3390\/drones9030191","article-title":"Aerial-drone-based tool for assessing Flood Risk Areas due to woody debris along river basins","volume":"9","author":"Barbero-Garcia","year":"2025","journal-title":"Drones"},{"key":"10.1016\/j.envsoft.2026.106910_b15","series-title":"Mdbartos\/pysheds: 0.4","author":"Bartos","year":"2024"},{"issue":"8","key":"10.1016\/j.envsoft.2026.106910_b16","doi-asserted-by":"crossref","first-page":"1598","DOI":"10.3390\/rs13081598","article-title":"Development of novel classification algorithms for detection of floating plastic debris in coastal waterbodies using multispectral sentinel-2 remote sensing imagery","volume":"13","author":"Basu","year":"2021","journal-title":"Remote. Sens."},{"issue":"1\u20132","key":"10.1016\/j.envsoft.2026.106910_b17","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.jhydrol.2010.03.027","article-title":"A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling","volume":"387","author":"Bates","year":"2010","journal-title":"J. Hydrol."},{"issue":"14","key":"10.1016\/j.envsoft.2026.106910_b18","doi-asserted-by":"crossref","first-page":"2283","DOI":"10.3390\/rs12142283","article-title":"A practical methodology for generating high-resolution 3D models of open-pit slopes using UAVs: flight path planning and optimization","volume":"12","author":"Battulwar","year":"2020","journal-title":"Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b19","first-page":"613","article-title":"Cloud optimized image format and compression","volume":"XL-7\/W3","author":"Becker","year":"2015","journal-title":"ISPRS - Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b20","series-title":"2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS)","first-page":"145","article-title":"Urban flood modelling simulation with 3D building models from airborne LiDAR point cloud","author":"Behera","year":"2022"},{"issue":"16","key":"10.1016\/j.envsoft.2026.106910_b21","doi-asserted-by":"crossref","first-page":"4345","DOI":"10.5194\/hess-26-4345-2022","article-title":"Deep learning methods for flood mapping: A review of existing applications and future research directions","volume":"26","author":"Bentivoglio","year":"2022","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b22","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2022.128975","article-title":"Developing reliable urban flood hazard mapping from LiDAR data","volume":"617","author":"Bodoque","year":"2023","journal-title":"J. Hydrol."},{"key":"10.1016\/j.envsoft.2026.106910_b23","series-title":"2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","first-page":"835","article-title":"Sen1Floods11: A georeferenced dataset to train and test deep learning flood algorithms for sentinel-1","author":"Bonafilia","year":"2020"},{"issue":"7","key":"10.1016\/j.envsoft.2026.106910_b24","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1016\/j.envsci.2011.05.017","article-title":"Flash flood forecasting, warning and risk management: The HYDRATE project","volume":"14","author":"Borga","year":"2011","journal-title":"Environ. Sci. Policy"},{"key":"10.1016\/j.envsoft.2026.106910_b25","doi-asserted-by":"crossref","first-page":"10.1","DOI":"10.1175\/AMSMONOGRAPHS-D-16-0015.1","article-title":"Remote sensing","volume":"58","author":"B\u00fchl","year":"2017","journal-title":"Meteorol. Monogr."},{"key":"10.1016\/j.envsoft.2026.106910_b26","doi-asserted-by":"crossref","first-page":"10608","DOI":"10.1109\/JSTARS.2025.3552783","article-title":"A lightweight network with embedded soft constraints on approximate spectral features for real-time water body segmentation in remote sensing images","volume":"18","author":"Cao","year":"2025","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b27","doi-asserted-by":"crossref","first-page":"2361","DOI":"10.3390\/rs15092361","article-title":"Mapping pluvial flood-induced damages with multi-sensor optical remote sensing: A transferable approach","volume":"15","author":"Cerbelaud","year":"2023","journal-title":"Remote. Sens."},{"issue":"12","key":"10.1016\/j.envsoft.2026.106910_b28","doi-asserted-by":"crossref","first-page":"1670","DOI":"10.3390\/w16121670","article-title":"Vision transformer for flood detection using satellite images from sentinel-1 and sentinel-2","volume":"16","author":"Chamatidis","year":"2024","journal-title":"Water"},{"issue":"4","key":"10.1016\/j.envsoft.2026.106910_b29","doi-asserted-by":"crossref","first-page":"405","DOI":"10.3390\/w13040405","article-title":"An operational high-performance forecasting system for city-scale pluvial flash floods in the Southwestern Plain Areas of Taiwan","volume":"13","author":"Chang","year":"2021","journal-title":"Water"},{"issue":"10","key":"10.1016\/j.envsoft.2026.106910_b30","doi-asserted-by":"crossref","first-page":"2100","DOI":"10.3390\/w11102100","article-title":"An operational forecasting system for flash floods in mountainous areas in Taiwan","volume":"11","author":"Chen","year":"2019","journal-title":"Water"},{"issue":"10","key":"10.1016\/j.envsoft.2026.106910_b31","doi-asserted-by":"crossref","first-page":"1662","DOI":"10.3390\/rs12101662","article-title":"A spatial-temporal attention-based method and a new dataset for remote sensing image change detection","volume":"12","author":"Chen","year":"2020","journal-title":"Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b32","series-title":"Computer Vision \u2013 ECCV 2018","first-page":"833","article-title":"Encoder-decoder with atrous separable convolution for semantic image segmentation","author":"Chen","year":"2018"},{"issue":"11","key":"10.1016\/j.envsoft.2026.106910_b33","doi-asserted-by":"crossref","first-page":"3387","DOI":"10.5194\/gmd-18-3387-2025","article-title":"A reach-integrated hydraulic modelling approach for large-scale and real-time inundation mapping","volume":"18","author":"Chlumsky","year":"2025","journal-title":"Geosci. Model. Dev."},{"issue":"21","key":"10.1016\/j.envsoft.2026.106910_b34","doi-asserted-by":"crossref","first-page":"3813","DOI":"10.3390\/w15213813","article-title":"Remote sensing with UAVs for flood modeling: A validation with actual flood records","volume":"15","author":"Clasing","year":"2023","journal-title":"Water"},{"key":"10.1016\/j.envsoft.2026.106910_b35","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2014.02.013","article-title":"Unmanned aerial systems for photogrammetry and remote sensing: A review","volume":"92","author":"Colomina","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b36","series-title":"European State of the Climate 2024","author":"Copernicus Climate Change Service","year":"2024"},{"issue":"16","key":"10.1016\/j.envsoft.2026.106910_b37","doi-asserted-by":"crossref","first-page":"4020","DOI":"10.3390\/rs15164020","article-title":"Improving the accuracy of land use and land cover classification of landsat data in an agricultural watershed","volume":"15","author":"Dash","year":"2023","journal-title":"Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b38","series-title":"Qgis\/QGIS: 3.44.5","author":"Dawson","year":"2025"},{"issue":"7","key":"10.1016\/j.envsoft.2026.106910_b39","doi-asserted-by":"crossref","first-page":"4081","DOI":"10.5194\/hess-25-4081-2021","article-title":"Assimilation of probabilistic flood maps from SAR data into a coupled hydrologic\u2013hydraulic forecasting model: A proof of concept","volume":"25","author":"Di Mauro","year":"2021","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b40","series-title":"Docker","author":"Docker Inc","year":"2025"},{"issue":"22","key":"10.1016\/j.envsoft.2026.106910_b41","doi-asserted-by":"crossref","first-page":"8015","DOI":"10.1080\/01431161.2024.2394238","article-title":"Comparing sentinel-2 and landsat 9 for land use and land cover mapping assessment in the north of congo Republic: a case study in sangha region","volume":"45","author":"Donatien","year":"2024","journal-title":"Int. J. Remote Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b42","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2011.11.026","article-title":"Sentinel-2: ESA\u2019s optical high-resolution mission for GMES operational services","volume":"120","author":"Drusch","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.envsoft.2026.106910_b43","doi-asserted-by":"crossref","DOI":"10.1016\/j.image.2021.116255","article-title":"Convolution neural network based lossy compression of hyperspectral images","volume":"95","author":"Dua","year":"2021","journal-title":"Signal Process., Image Commun."},{"issue":"10","key":"10.1016\/j.envsoft.2026.106910_b44","doi-asserted-by":"crossref","first-page":"1382","DOI":"10.3390\/w10101382","article-title":"Application of python scripting techniques for control and automation of HEC-RAS simulations","volume":"10","author":"Dysarz","year":"2018","journal-title":"Water"},{"issue":"4\u20135","key":"10.1016\/j.envsoft.2026.106910_b45","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1007\/s10236-007-0124-3","article-title":"Application of data assimilation in portable operational forecasting systems\u2014the DATools assimilation environment","volume":"57","author":"El Serafy","year":"2007","journal-title":"Ocean. Dyn."},{"issue":"19","key":"10.1016\/j.envsoft.2026.106910_b46","doi-asserted-by":"crossref","first-page":"7384","DOI":"10.3390\/s22197384","article-title":"A review on multiscale-deep-learning applications","volume":"22","author":"Elizar","year":"2022","journal-title":"Sensors (Basel, Switzerland)"},{"issue":"2","key":"10.1016\/j.envsoft.2026.106910_b47","doi-asserted-by":"crossref","DOI":"10.1029\/2022WR033168","article-title":"Physics-informed neural networks of the saint-venant equations for downscaling a large-scale river model","volume":"59","author":"Feng","year":"2023","journal-title":"Water Resour. Res."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106910_b48","doi-asserted-by":"crossref","first-page":"1104","DOI":"10.3390\/s22031104","article-title":"First gradually, then suddenly: understanding the impact of image compression on object detection using deep learning","volume":"22","author":"Gandor","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.envsoft.2026.106910_b49","series-title":"2024 IEEE International Conference on Multimedia and Expo (ICME)","first-page":"1","article-title":"Relating CNN-transformer fusion network for remote sensing change detection","author":"Gao","year":"2024"},{"issue":"3","key":"10.1016\/j.envsoft.2026.106910_b50","doi-asserted-by":"crossref","first-page":"144","DOI":"10.3390\/ijgi10030144","article-title":"Three-dimensional inundation mapping using UAV image segmentation and digital surface model","volume":"10","author":"Gebrehiwot","year":"2021","journal-title":"ISPRS Int. J. Geo-Inform."},{"issue":"11","key":"10.1016\/j.envsoft.2026.106910_b51","doi-asserted-by":"crossref","first-page":"E2328","DOI":"10.1175\/BAMS-D-24-0214.1","article-title":"The data assimilation research testbed: A robust, scalable software facility with groundbreaking capabilities for model-data integration","volume":"106","author":"Gharamti","year":"2025","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"10.1016\/j.envsoft.2026.106910_b52","series-title":"Rasterio","author":"Gillies","year":"2024"},{"key":"10.1016\/j.envsoft.2026.106910_b53","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1016\/j.jhydrol.2016.03.007","article-title":"Initial soil moisture effects on flash flood generation \u2013 A comparison between basins of contrasting hydro-climatic conditions","volume":"541","author":"Grillakis","year":"2016","journal-title":"J. Hydrol."},{"issue":"11","key":"10.1016\/j.envsoft.2026.106910_b54","doi-asserted-by":"crossref","DOI":"10.1029\/2022MS003542","article-title":"Direct sampling for spatially variable extreme event generation in resampling-based stochastic weather generators","volume":"15","author":"Guevara","year":"2023","journal-title":"J. Adv. Model. Earth Syst."},{"key":"10.1016\/j.envsoft.2026.106910_b55","unstructured":"Gupta, R., Goodman, B., Patel, N., Hosfelt, R., Sajeev, S., Heim, E., Doshi, J., Lucas, K., Choset, H., Gaston, M., 2019. Creating xBD: A Dataset for Assessing Building Damage from Satellite Imagery. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106910_b56","doi-asserted-by":"crossref","first-page":"150","DOI":"10.3390\/buildings11040150","article-title":"Change detection in unmanned aerial vehicle images for progress monitoring of road construction","volume":"11","author":"Han","year":"2021","journal-title":"Buildings"},{"issue":"20","key":"10.1016\/j.envsoft.2026.106910_b57","doi-asserted-by":"crossref","first-page":"6503","DOI":"10.3390\/s24206503","article-title":"High-quality image compression algorithm design based on unsupervised learning","volume":"24","author":"Han","year":"2024","journal-title":"Sensors"},{"key":"10.1016\/j.envsoft.2026.106910_b58","series-title":"2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","first-page":"1471","article-title":"SpaceNet 8 - the detection of flooded roads and buildings","author":"Hansch","year":"2022"},{"issue":"15","key":"10.1016\/j.envsoft.2026.106910_b59","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2024.e35274","article-title":"Prediction of dynamics of riverbank erosion: A tale of the riverine town chandpur sadar","volume":"10","author":"Hasan","year":"2024","journal-title":"Heliyon"},{"key":"10.1016\/j.envsoft.2026.106910_b60","series-title":"2017 IEEE International Conference on Computer Vision (ICCV)","first-page":"2980","article-title":"Mask R-CNN","author":"He","year":"2017"},{"key":"10.1016\/j.envsoft.2026.106910_b61","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.envsoft.2026.106910_b62","series-title":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","first-page":"204","article-title":"Introducing eurosat: a novel dataset and deep learning benchmark for land use and land cover classification","author":"Helber","year":"2018"},{"key":"10.1016\/j.envsoft.2026.106910_b63","doi-asserted-by":"crossref","first-page":"2023","DOI":"10.1109\/JSTARS.2022.3152127","article-title":"Sentinel-1-based water and flood mapping: benchmarking convolutional neural networks against an operational rule-based processing chain","volume":"15","author":"Helleis","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b64","doi-asserted-by":"crossref","first-page":"223","DOI":"10.3390\/rs14010223","article-title":"Flood detection using real-time image segmentation from unmanned aerial vehicles on edge-computing platform","volume":"14","author":"Hernandez","year":"2022","journal-title":"Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b65","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2025.3609573","article-title":"Deep-learning-based object detection and tracking of debris flows in 3-D through LiDAR-camera fusion","volume":"63","author":"Hirschberg","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"8","key":"10.1016\/j.envsoft.2026.106910_b66","doi-asserted-by":"crossref","first-page":"5516","DOI":"10.1029\/2017WR022205","article-title":"Near-real-time assimilation of SAR-derived flood maps for improving flood forecasts","volume":"54","author":"Hostache","year":"2018","journal-title":"Water Resour. Res."},{"key":"10.1016\/j.envsoft.2026.106910_b67","doi-asserted-by":"crossref","first-page":"91980","DOI":"10.1109\/ACCESS.2019.2927809","article-title":"UAV image high fidelity compression algorithm based on generative adversarial networks under complex disaster conditions","volume":"7","author":"Hu","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.envsoft.2026.106910_b68","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.isprsjprs.2020.09.012","article-title":"A deep learning framework for matching of SAR and optical imagery","volume":"169","author":"Hughes","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b69","series-title":"2009 IEEE International Geoscience and Remote Sensing Symposium","first-page":"IV","article-title":"The orfeo toolbox remote sensing image processing software","volume":"4","author":"Inglada","year":"2009"},{"issue":"17","key":"10.1016\/j.envsoft.2026.106910_b70","doi-asserted-by":"crossref","first-page":"2605","DOI":"10.3390\/w14172605","article-title":"Floodborne objects type recognition using computer vision to mitigate blockage originated floods","volume":"14","author":"Iqbal","year":"2022","journal-title":"Water"},{"key":"10.1016\/j.envsoft.2026.106910_b71","series-title":"2024 28th International Symposium on VLSI Design and Test (VDAT)","first-page":"1","article-title":"Enhanced edge detection for image segmentation and its real-time implementation","author":"J. R","year":"2024"},{"issue":"6","key":"10.1016\/j.envsoft.2026.106910_b72","doi-asserted-by":"crossref","first-page":"1438","DOI":"10.1016\/j.jenvman.2011.01.018","article-title":"Identification and quantification of the hydrological impacts of imperviousness in urban catchments: A review","volume":"92","author":"Jacobson","year":"2011","journal-title":"J. Environ. Manag."},{"key":"10.1016\/j.envsoft.2026.106910_b73","doi-asserted-by":"crossref","DOI":"10.1016\/j.compag.2022.106844","article-title":"A comprehensive review of remote sensing platforms, sensors, and applications in nut crops","volume":"197","author":"Jafarbiglu","year":"2022","journal-title":"Comput. Electron. Agric."},{"issue":"11","key":"10.1016\/j.envsoft.2026.106910_b74","doi-asserted-by":"crossref","first-page":"308","DOI":"10.3390\/fi14110308","article-title":"Real-time flood monitoring with computer vision through edge computing-based internet of things","volume":"14","author":"Jan","year":"2022","journal-title":"Futur. Internet"},{"issue":"9","key":"10.1016\/j.envsoft.2026.106910_b75","doi-asserted-by":"crossref","first-page":"1849","DOI":"10.1080\/13658816.2025.2543038","article-title":"GeoFM: How will geo-foundation models reshape spatial data science and GeoAI?","volume":"39","author":"Janowicz","year":"2025","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b76","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.inffus.2020.03.005","article-title":"Radar networks: A review of features and challenges","volume":"61","author":"Javadi","year":"2020","journal-title":"Inf. Fusion"},{"issue":"5","key":"10.1016\/j.envsoft.2026.106910_b77","doi-asserted-by":"crossref","first-page":"285","DOI":"10.3390\/ijgi10050285","article-title":"Digital terrain models generated with Low-Cost UAV Photogrammetry: methodology and accuracy","volume":"10","author":"Jimenez-Jimenez","year":"2021","journal-title":"ISPRS Int. J. Geo-Inform."},{"key":"10.1016\/j.envsoft.2026.106910_b78","article-title":"A review of ground camera-based computer vision techniques for flood management","volume":"33","author":"Jun","year":"2024","journal-title":"Comput. Concr."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106910_b79","doi-asserted-by":"crossref","first-page":"1228","DOI":"10.1109\/36.701075","article-title":"The moderate resolution imaging spectroradiometer (MODIS): land remote sensing for global change research","volume":"36","author":"Justice","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b80","first-page":"80","article-title":"Mapping of large-scale flooding in thessaly region using sentinel data","volume":"vol. 13197","author":"Kalafatis","year":"2024"},{"issue":"21","key":"10.1016\/j.envsoft.2026.106910_b81","doi-asserted-by":"crossref","first-page":"2943","DOI":"10.3390\/w13212943","article-title":"FLOMPY: an open-source toolbox for floodwater mapping using sentinel-1 intensity time series","volume":"13","author":"Karamvasis","year":"2021","journal-title":"Water"},{"issue":"12","key":"10.1016\/j.envsoft.2026.106910_b82","doi-asserted-by":"crossref","first-page":"2334","DOI":"10.3390\/rs13122334","article-title":"Near-real-time flood mapping using off-the-shelf models with SAR imagery and deep learning","volume":"13","author":"Katiyar","year":"2021","journal-title":"Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b83","series-title":"Filterpy","author":"Labbe","year":"2025"},{"issue":"16","key":"10.1016\/j.envsoft.2026.106910_b84","doi-asserted-by":"crossref","first-page":"2513","DOI":"10.3390\/w14162513","article-title":"Flood risk assessment using TELEMAC-2D models integrated with multi-index analysis in shenzhen river basin, China","volume":"14","author":"Li","year":"2022","journal-title":"Water"},{"key":"10.1016\/j.envsoft.2026.106910_b85","series-title":"Hard region aware network for remote sensing change detection","author":"Li","year":"2023"},{"key":"10.1016\/j.envsoft.2026.106910_b86","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2022.105586","article-title":"V-FloodNet: A video segmentation system for urban flood detection and quantification","volume":"160","author":"Liang","year":"2023","journal-title":"Environ. Model. Softw."},{"key":"10.1016\/j.envsoft.2026.106910_b87","first-page":"n\/a","article-title":"An adaptive image compression algorithm based on joint clustering algorithm and deep learning","volume":"18","author":"Liang","year":"2023","journal-title":"IET Image Process."},{"key":"10.1016\/j.envsoft.2026.106910_b88","doi-asserted-by":"crossref","first-page":"488","DOI":"10.3390\/drones7080488","article-title":"Image splicing compression algorithm based on the extended Kalman filter for unmanned aerial vehicles communication","volume":"7","author":"Liang","year":"2023","journal-title":"Drones"},{"key":"10.1016\/j.envsoft.2026.106910_b89","series-title":"Remote Sensing and Image Interpretation","author":"Lillesand","year":"2015"},{"issue":"9","key":"10.1016\/j.envsoft.2026.106910_b90","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.3390\/e23091111","article-title":"Improved YOLO based detection algorithm for floating debris in waterway","volume":"23","author":"Lin","year":"2021","journal-title":"Entropy"},{"issue":"3","key":"10.1016\/j.envsoft.2026.106910_b91","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s13753-025-00639-0","article-title":"A comprehensive review of machine learning approaches for flood depth estimation","volume":"16","author":"Liu","year":"2025","journal-title":"Int. J. Disaster Risk Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b92","doi-asserted-by":"crossref","first-page":"12910","DOI":"10.1109\/JSTARS.2024.3424831","article-title":"A review of optical and SAR image deep feature fusion in semantic segmentation","volume":"17","author":"Liu","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b93","first-page":"1","article-title":"PointSAM: pointly-supervised segment anything model for remote sensing images","volume":"63","author":"Liu","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"11","key":"10.1016\/j.envsoft.2026.106910_b94","doi-asserted-by":"crossref","first-page":"1956","DOI":"10.1080\/02626667.2020.1787417","article-title":"Impacts of land-use and climate changes on surface runoff in a tropical forest watershed (Brazil)","volume":"65","author":"Lucas-Borja","year":"2020","journal-title":"Hydrol. Sci. J."},{"issue":"1\u20132","key":"10.1016\/j.envsoft.2026.106910_b95","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.jhydrol.2010.07.017","article-title":"Characterisation of selected extreme flash floods in Europe and implications for flood risk management","volume":"394","author":"Marchi","year":"2010","journal-title":"J. Hydrol."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b96","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1186\/s42269-020-00442-5","article-title":"Hydrological problems of flash floods and the encroachment of wastewater affecting the urban areas in greater cairo, Egypt, using remote sensing and GIS techniques","volume":"44","author":"Megahed","year":"2020","journal-title":"Bull. Natl. Res. Cent."},{"key":"10.1016\/j.envsoft.2026.106910_b97","first-page":"1","article-title":"SCD-SAM: adapting segment anything model for semantic change detection in remote sensing imagery","volume":"62","author":"Mei","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b98","doi-asserted-by":"crossref","first-page":"889","DOI":"10.5721\/EuJRS20164946","article-title":"River morphology monitoring using multitemporal SAR data: Preliminary results","volume":"49","author":"Mitidieri","year":"2016","journal-title":"Eur. J. Remote. Sens."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106910_b99","doi-asserted-by":"crossref","first-page":"525","DOI":"10.5194\/nhess-23-525-2023","article-title":"A multi-disciplinary analysis of the exceptional flood event of july 2021 in central Europe \u2013 part 1: event description and analysis","volume":"23","author":"Mohr","year":"2023","journal-title":"Nat. Hazards Earth Syst. Sci."},{"issue":"11","key":"10.1016\/j.envsoft.2026.106910_b100","doi-asserted-by":"crossref","first-page":"4621","DOI":"10.5194\/hess-23-4621-2019","article-title":"Scalable flood level trend monitoring with surveillance cameras using a deep convolutional neural network","volume":"23","author":"Moy de Vitry","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"issue":"11","key":"10.1016\/j.envsoft.2026.106910_b101","doi-asserted-by":"crossref","first-page":"4621","DOI":"10.5194\/hess-23-4621-2019","article-title":"Scalable flood level trend monitoring with surveillance cameras using a deep convolutional neural network","volume":"23","author":"Moy de Vitry","year":"2019","journal-title":"Hydrol. Earth Syst. Sci."},{"issue":"14","key":"10.1016\/j.envsoft.2026.106910_b102","doi-asserted-by":"crossref","first-page":"2308","DOI":"10.3390\/rs12142308","article-title":"The use of LiDAR-derived DEM in flood applications: A review","volume":"12","author":"Muhadi","year":"2020","journal-title":"Remote. Sens."},{"issue":"20","key":"10.1016\/j.envsoft.2026.106910_b103","doi-asserted-by":"crossref","first-page":"9691","DOI":"10.3390\/app11209691","article-title":"Deep learning semantic segmentation for water level estimation using surveillance camera","volume":"11","author":"Muhadi","year":"2021","journal-title":"Appl. Sci."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106910_b104","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1109\/TAI.2022.3200028","article-title":"Physics-informed neural networks for modeling water flows in a river channel","volume":"5","author":"Nazari","year":"2024","journal-title":"IEEE Trans. Artif. Intell."},{"key":"10.1016\/j.envsoft.2026.106910_b105","series-title":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","first-page":"1525","article-title":"Reducing uncertainties of a chained hydrologic-hydraulic models to improve flood forecasting using multi-source earth observation data","author":"Nguyen","year":"2023"},{"issue":"11","key":"10.1016\/j.envsoft.2026.106910_b106","doi-asserted-by":"crossref","DOI":"10.1029\/2022WR033155","article-title":"Dual state-parameter assimilation of SAR-derived wet surface ratio for improving fluvial flood reanalysis","volume":"58","author":"Nguyen","year":"2022","journal-title":"Water Resour. Res."},{"issue":"5","key":"10.1016\/j.envsoft.2026.106910_b107","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/MAP.2022.3143442","article-title":"Polarimetric weather radar: overview of principles and applications","volume":"64","author":"Notaros","year":"2022","journal-title":"IEEE Antennas Propag. Mag."},{"key":"10.1016\/j.envsoft.2026.106910_b108","series-title":"Postgis","author":"Obe","year":"2025"},{"key":"10.1016\/j.envsoft.2026.106910_b109","series-title":"Openfoam","author":"OpenC.F.D. Ltd","year":"2025"},{"key":"10.1016\/j.envsoft.2026.106910_b110","first-page":"1","article-title":"A transformer-based multi-scale difference enhancement network for change detection","author":"Pan","year":"2025","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b111","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1109\/IGARSS.2019.8900330","article-title":"Detecting urban changes with recurrent neural networks from multitemporal sentinel-2 data","author":"Papadomanolaki","year":"2019","journal-title":"IGARSS 2019 - 2019 IEEE Int. Geosci. Remote. Sens. Symp."},{"key":"10.1016\/j.envsoft.2026.106910_b112","first-page":"1680","article-title":"An efficient data compression and storage technique with key management authentication in cloud space","volume":"35","author":"Pinnapati","year":"2024","journal-title":"Indones. J. Electr. Eng. Comput. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b113","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.isprsjprs.2025.04.036","article-title":"Continuous flood monitoring using on-demand SAR data acquired with different geometries: methodology and test on COSMO-SkyMed images","volume":"225","author":"Pulvirenti","year":"2025","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b114","series-title":"Pytorch","author":"PyTorch Community","year":"2025"},{"issue":"17","key":"10.1016\/j.envsoft.2026.106910_b115","doi-asserted-by":"crossref","first-page":"4161","DOI":"10.3390\/rs14174161","article-title":"A detection approach for floating debris using ground images based on deep learning","volume":"14","author":"Qiao","year":"2022","journal-title":"Remote. Sens."},{"issue":"22","key":"10.1016\/j.envsoft.2026.106910_b116","doi-asserted-by":"crossref","first-page":"4328","DOI":"10.3390\/rs16224328","article-title":"Flooded infrastructure change detection in deeply supervised networks based on multi-attention-constrained multi-scale feature fusion","volume":"16","author":"Qin","year":"2024","journal-title":"Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b117","doi-asserted-by":"crossref","DOI":"10.1016\/j.pce.2024.103675","article-title":"UAV-based DEM augmentation using ConSinGAN for efficient flood parameter prediction with machine learning and 1D hydrodynamic models","volume":"135","author":"Rana","year":"2024","journal-title":"Phys. Chem. Earth, Parts A\/B\/C"},{"key":"10.1016\/j.envsoft.2026.106910_b118","series-title":"2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","first-page":"80","article-title":"IoT-based flash flood detection and alert using TensorFlow","author":"Rashid","year":"2021"},{"key":"10.1016\/j.envsoft.2026.106910_b119","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"779","article-title":"You only look once: unified, real-time object detection","author":"Redmon","year":"2016"},{"key":"10.1016\/j.envsoft.2026.106910_b120","doi-asserted-by":"crossref","DOI":"10.1016\/j.renene.2024.120157","article-title":"Generation and validation of comprehensive synthetic weather histories using auto-regressive moving-average models","volume":"224","author":"Rigby","year":"2024","journal-title":"Renew. Energy"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b121","doi-asserted-by":"crossref","first-page":"237","DOI":"10.3390\/ijerph19010237","article-title":"Drone-based water level detection in flood disasters","volume":"19","author":"Rizk","year":"2022","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"10.1016\/j.envsoft.2026.106910_b122","series-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","first-page":"234","article-title":"U-net: convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.envsoft.2026.106910_b123","series-title":"GDAL","author":"Rouault","year":"2025"},{"key":"10.1016\/j.envsoft.2026.106910_b124","first-page":"1","article-title":"Multimodal fusion transformer for remote sensing image classification","volume":"61","author":"Roy","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b125","doi-asserted-by":"crossref","DOI":"10.1080\/19475705.2024.2375545","article-title":"Proposal of a flood damage road detection method based on deep learning and elevation data","volume":"15","author":"Sakamoto","year":"2024","journal-title":"Geomatics, Nat. Hazards Risk"},{"key":"10.1016\/j.envsoft.2026.106910_b126","doi-asserted-by":"crossref","DOI":"10.1175\/BAMS-D-18-0166.1","article-title":"An overview of using weather radar for climatological studies: successes, challenges, and potential","volume":"100","author":"Saltikoff","year":"2019","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"10.1016\/j.envsoft.2026.106910_b127","series-title":"Proceedings of the 16th International Conference on Agents and Artificial Intelligence","first-page":"1028","article-title":"Explainable deep semantic segmentation for flood inundation mapping with class activation mapping techniques:","author":"Sanderson","year":"2024"},{"issue":"18","key":"10.1016\/j.envsoft.2026.106910_b128","doi-asserted-by":"crossref","first-page":"3450","DOI":"10.3390\/rs16183450","article-title":"A first extension of the robust satellite technique RST-FLOOD to sentinel-2 data for the mapping of flooded areas: the case of the emilia romagna (Italy) 2023 event","volume":"16","author":"Satriano","year":"2024","journal-title":"Remote. Sens."},{"issue":"9","key":"10.1016\/j.envsoft.2026.106910_b129","doi-asserted-by":"crossref","first-page":"2519","DOI":"10.5194\/hess-26-2519-2022","article-title":"Guidance on evaluating parametric model uncertainty at decision-relevant scales","volume":"26","author":"Smith","year":"2022","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b130","article-title":"A learning approach for river debris detection","volume":"107","author":"Sole Gomez","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"issue":"18","key":"10.1016\/j.envsoft.2026.106910_b131","doi-asserted-by":"crossref","first-page":"3600","DOI":"10.3390\/rs13183600","article-title":"Land use land cover classification with u-net: advantages of combining sentinel-1 and sentinel-2 imagery","volume":"13","author":"Sol\u00f3rzano","year":"2021","journal-title":"Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b132","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2023.129703","article-title":"The use of crowdsourced social media data to improve flood forecasting","volume":"622","author":"Songchon","year":"2023","journal-title":"J. Hydrol."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b133","doi-asserted-by":"crossref","first-page":"14604","DOI":"10.1038\/s41598-024-65430-5","article-title":"Extraction of water bodies from high-resolution remote sensing imagery based on a deep semantic segmentation network","volume":"14","author":"Sun","year":"2024","journal-title":"Sci. Rep."},{"issue":"5","key":"10.1016\/j.envsoft.2026.106910_b134","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.3390\/rs14051189","article-title":"Random forest classification of land use, land-use change and forestry (LULUCF) using sentinel-2 data\u2014A case study of czechia","volume":"14","author":"Svoboda","year":"2023","journal-title":"Remote. Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b135","series-title":"TensorFlow","author":"TensorFlow Community","year":"2022"},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b136","doi-asserted-by":"crossref","first-page":"18","DOI":"10.3390\/s18010018","article-title":"Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using sentinel-2 imagery","volume":"18","author":"Thanh Noi","year":"2018","journal-title":"Sensors"},{"key":"10.1016\/j.envsoft.2026.106910_b137","series-title":"Apache airflow","author":"The Apache Software Foundation","year":"2025"},{"issue":"2","key":"10.1016\/j.envsoft.2026.106910_b138","doi-asserted-by":"crossref","first-page":"973","DOI":"10.5194\/nhess-23-973-2023","article-title":"Performance of the flood warning system in Germany in july 2021 \u2013 insights from affected residents","volume":"23","author":"Thieken","year":"2023","journal-title":"Nat. Hazards Earth Syst. Sci."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106910_b139","doi-asserted-by":"crossref","first-page":"1359","DOI":"10.5194\/hess-21-1359-2017","article-title":"Weather radar rainfall data in urban hydrology","volume":"21","author":"Thorndahl","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b140","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.rse.2011.05.028","article-title":"GMES sentinel-1 mission","volume":"120","author":"Torres","year":"2012","journal-title":"Remote Sens. Environ."},{"issue":"8","key":"10.1016\/j.envsoft.2026.106910_b141","doi-asserted-by":"crossref","first-page":"4435","DOI":"10.5194\/hess-25-4435-2021","article-title":"Deep learning for automated river-level monitoring through river-camera images: An approach based on water segmentation and transfer learning","volume":"25","author":"Vandaele","year":"2021","journal-title":"Hydrol. Earth Syst. Sci."},{"issue":"4","key":"10.1016\/j.envsoft.2026.106910_b142","doi-asserted-by":"crossref","first-page":"831","DOI":"10.2166\/wpt.2023.048","article-title":"HEC-ras 2D modeling for flood inundation mapping: A case study of the krishna river basin","volume":"18","author":"Vashist","year":"2023","journal-title":"Water Pr. Technol."},{"key":"10.1016\/j.envsoft.2026.106910_b143","article-title":"River water segmentation in surveillance camera images: A comparative study of offline and online augmentation using 32 CNNs","volume":"119","author":"Wagner","year":"2023","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"10.1016\/j.envsoft.2026.106910_b144","series-title":"PyTelTools","author":"Wang","year":"2017"},{"key":"10.1016\/j.envsoft.2026.106910_b145","series-title":"WhiteboxTools open core","author":"Whitebox Geospatial Inc","year":"2024"},{"key":"10.1016\/j.envsoft.2026.106910_b146","doi-asserted-by":"crossref","DOI":"10.3389\/fbuil.2024.1482330","article-title":"Development of methodology for Calculating Flooded Area and flood volume in Small Urban Areas based on unmanned aerial vehicle images","volume":"10","author":"Woo","year":"2024","journal-title":"Front. Built Environ."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b147","doi-asserted-by":"crossref","first-page":"6789","DOI":"10.1038\/s41598-025-86471-4","article-title":"Deep learning-based debris flow hazard detection and recognition system: A case study","volume":"15","author":"Wu","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.envsoft.2026.106910_b148","first-page":"1","article-title":"Remote sensing image compression based on high-frequency and low-frequency components","volume":"62","author":"Xiang","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106910_b149","doi-asserted-by":"crossref","first-page":"2297","DOI":"10.1007\/s11069-021-05138-1","article-title":"Variation of uncertainty of drainage density in flood hazard mapping assessment with coupled 1D\u20132D hydrodynamics model","volume":"111","author":"Yang","year":"2022","journal-title":"Nat. Hazards"},{"key":"10.1016\/j.envsoft.2026.106910_b150","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.isprsjprs.2025.03.005","article-title":"Map-assisted remote-sensing image compression at extremely low bitrates","volume":"223","author":"Ye","year":"2025","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"10.1016\/j.envsoft.2026.106910_b151","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"10239","article-title":"CAMSIC: Content-aware masked image modeling transformer for stereo image compression","author":"Zhang","year":"2025"},{"issue":"13","key":"10.1016\/j.envsoft.2026.106910_b152","doi-asserted-by":"crossref","first-page":"7367","DOI":"10.3390\/app13137367","article-title":"YOLOv5-FF: detecting floating objects on the surface of fresh water environments","volume":"13","author":"Zhang","year":"2023","journal-title":"Appl. Sci."},{"issue":"2","key":"10.1016\/j.envsoft.2026.106910_b153","doi-asserted-by":"crossref","first-page":"390","DOI":"10.3390\/rs16020390","article-title":"A framework for fine-grained land-cover classification using 10 m sentinel-2 images","volume":"16","author":"Zhang","year":"2024","journal-title":"Remote. Sens."},{"issue":"1","key":"10.1016\/j.envsoft.2026.106910_b154","first-page":"74","article-title":"Real-time rescue target detection based on UAV imagery for flood emergency response","volume":"7","author":"ZHAO","year":"2024","journal-title":"J. Geod. Geoinf. Sci."},{"key":"10.1016\/j.envsoft.2026.106910_b155","article-title":"Detection of urban flood inundation from traffic images using deep learning methods","volume":"38","author":"Zhong","year":"2023","journal-title":"Water Resour. Manag."},{"issue":"3","key":"10.1016\/j.envsoft.2026.106910_b156","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1109\/JMASS.2025.3542124","article-title":"Transformer-based semantic segmentation for flood region recognition in SAR images","volume":"6","author":"Zhou","year":"2025","journal-title":"IEEE J. Miniaturization Air Space Syst."},{"key":"10.1016\/j.envsoft.2026.106910_b157","article-title":"ChangeViT: unleashing plain vision transformers for change detection in remote sensing images","volume":"172","author":"Zhu","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.envsoft.2026.106910_b158","series-title":"2022 3rd International Conference on Geology, Mapping and Remote Sensing (ICGMRS)","first-page":"619","article-title":"Research on UAV remote sensing multispectral image compression based on CNN","author":"Zhu","year":"2022"},{"issue":"24","key":"10.1016\/j.envsoft.2026.106910_b159","doi-asserted-by":"crossref","first-page":"4020","DOI":"10.3390\/w14244020","article-title":"Potential of two SAR-based flood mapping approaches in supporting an integrated 1D\/2D HEC-RAS Model","volume":"14","author":"Zotou","year":"2022","journal-title":"Water"},{"key":"10.1016\/j.envsoft.2026.106910_b160","doi-asserted-by":"crossref","first-page":"623","DOI":"10.5194\/isprs-archives-XLVIII-3-2024-623-2024","article-title":"Satellite-based land cover classification in the itaja\u00edriver basin: methods and analysis","volume":"XLVIII-3-2024","author":"Zucatelli","year":"2024","journal-title":"Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci."}],"container-title":["Environmental Modelling &amp; Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815226000575?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815226000575?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T18:44:24Z","timestamp":1774032264000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1364815226000575"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":160,"alternative-id":["S1364815226000575"],"URL":"https:\/\/doi.org\/10.1016\/j.envsoft.2026.106910","relation":{},"ISSN":["1364-8152"],"issn-type":[{"value":"1364-8152","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Computer vision in flash flood forecasting: A narrative review of applications, integration pathways, and future directions","name":"articletitle","label":"Article Title"},{"value":"Environmental Modelling & Software","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.envsoft.2026.106910","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"106910"}}