Flood Inundation Mapping

Ask about this topic

Overview

Flood inundation mapping identifies where water spreads and, in some systems, estimates its depth or predicts how flooding will change. Methods combine satellite observations—especially Sentinel-1 radar, which can see through clouds, and optical imagery—with elevation data, using segmentation networks such as U-Net and transformer or foundation models. Multisensor fusion, generative image reconstruction, and physics-guided models help fill observation gaps and produce maps that are more consistent with terrain and water flow. A key challenge is reliable transfer to new flood events and landscapes: vegetation, buildings, clouds, sensor misalignment, and inconsistent reference maps can all undermine accuracy, while aggregate pixel scores may not reflect street-level usefulness or physical plausibility.

Latest papers

CardsList

27 papers3 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. Accuracy and efficiency of compact foundation models for surface-water mapping during floods

    Oct 26, 2026Parastoo Farajpoor, Mohammadreza NarimaniFlood Inundation MappingGeospatial Foundation Models

    Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, 95616, USA

  2. A Topology-Guided GeoAI Agentic Framework for Urban Flood Screening

    Oct 22, 2026Yutian Tao, Haoan Feng, Xin Xu +1Geospatial ReasoningFlood Inundation Mapping

    University of Maryland, College Park, Maryland, USA

  3. C-STRIDE: An Observation-Driven AI Digital Twin for Predicting Basin-Wide Flood Fields from Sparse Stream-Gauge Histories

    Sep 30, 2026Yanjie Tong, Phillip Si, Yuan Qiu +1Surrogate ModelingFlood Inundation Mapping

    School of Computational Science and Engineering, Georgia Institute of Technology, 756 West Peachtree Street Northwest, Atlanta, 30308, GA, USA

  4. A Model-Agnostic Physics-Guided Adapter for Few-Shot Transfer of Coastal Flood Prediction Models to Unseen Regions

    Sep 29, 2026Bilal Hassan, Areg Karapetyan, Samer MadanatFlood Inundation MappingFew-Shot Domain Adaptation

    Division of Engineering New York University Abu Dhabi Abu Dhabi, UAE

  5. A Controlled Evaluation of Model Rankings and Input Reliance in Surface Water Segmentation

    Aug 31, 2026Kittipat Phunjanna, Kristóf Karacs, Chayut NgamkhanongRemote Sensing Image SegmentationFlood Inundation Mapping

    Erasmus Mundus Joint Master in Image Processing and Computer Vision (IPCV) · Pázmány Péter Catholic University · Chulalongkorn University

  6. Real-time probabilistic tsunami forecasting via generative AI

    Aug 5, 2026Yusuke Oishi, Takashi Furumura, Fumihiko ImamuraUncertainty QuantificationProbabilistic Forecasting

    Fujitsu Research, Fujitsu Limited, Kawasaki, Japan. · Earthquake Research Institute, The University of Tokyo, Tokyo, Japan. · International Research Institute of Disaster Science, Tohoku University, Sendai, Japan.

  7. GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation

    Aug 3, 2026Gaetano Chiriaco, Luca Barco, Andrea Bragagnolo +2Remote Sensing Image SegmentationGeospatial Foundation Models

    Fondazione LINKS, Via Pier Carlo Boggio, 61, 10138 Torino, Italy · Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy

  8. Large scale cross-regional remote sensing flood monitoring framework for operative mapping and impact analysis

    Jul 30, 2026Ilya Novikov, Svetlana Illarionova, Ruslan Dzharkinov +6Remote Sensing Image SegmentationDisaster Damage Assessment

    Skolkovo Institute of Science and Technology, Moscow, 121205, Russia. · Trofimuk Institute of Petroleum Geology and Geophysics SB RAS, Novosibirsk, 630090, Russia. · King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia. +2

  9. Physics-Informed CNN-LSTM for Street-Scale Urban Flood Prediction: Reconciling Aggregate Accuracy and Street-Level Plausibility

    Jul 27, 2026Luc DCosta, Yidi Wang, Jonathan L. Goodall +1Convolutional RNNsFlood Inundation Mapping

    Chandra Robot Autonomy Lab, Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA · Link Lab, Multidisciplinary Research Center, University of Virginia, Charlottesville, VA 22904, USA · Hydroinformatics Research Group, Department of Civil and Environmental Engineering, University of Virginia, Charlottesville, VA 22904, USA

  10. High-Resolution Flood Mapping With Sentinel-1 and Sentinel-2 via Misalignment-Robust Cross-Sensor Learning and Generative Despeckling

    Jun 29, 2026David Ma, Jeremy Feinstein, Shreya Pandit +2Remote Sensing Image SegmentationFlood Inundation Mapping

    Argonne National Laboratory, Lemont, IL 60439 USA · Ohlone College, Fremont, CA 94539 USA

  11. Beyond Backscatter: AlphaEarth Land-Cover Priors for Rapid SAR Flood Segmentation Across Foundation Backbones

    Jun 28, 2026Sanjay Thasma, Yu-Hsuan Ho, Ali MostafaviRemote Sensing Image SegmentationGeospatial Foundation Models

    Department of Computer Science and Engineering, Texas A&M University, College Station, TX · Urban Resilience.AI Lab, Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX

  12. Flood Mapping from RGB imagery using a Vision Foundation Model

    Jun 23, 2026Vladyslav Polushko, Tilman Bucher, Ronald Rösch +3Remote Sensing Image SegmentationGeospatial Foundation Models

    Image Processing Department, Fraunhofer ITWM, Kaiserslautern, Germany · Institut für Optische Sensorsysteme, DLR, Berlin, Germany · ACIDA Lab, Hochschule Darmstadt, Darmstadt, Germany +1

  13. Explainable Flood Segmentation on Sentinel-1 SAR1 Imagery Using CNN and Transformer Architectures

    Jun 15, 2026Arundhuti Banerjee, David DaouRemote Sensing Image SegmentationExplainable Artificial Intelligence

    United Nations University’s Institute for Environment and Human Security (UNU-EHS) · Bonn, Germany 53113 · United Nations University’s InstituteBonn,forGermanyEnvironment53113and Human Security (UNU-EHS)

  14. Land cover and flood type govern the detection limits of satellite-based flood mapping across diverse global flood events

    Jun 5, 2026Venkatesh Kolluru, Rajat Shinde, Abdelhak Marouane +6Remote Sensing Image SegmentationGeospatial Foundation Models

    Earth System Science Center, University of Alabama in Huntsville, Huntsville, AL 35805, USA · Space and Earth Science Data Analysis, 7515 Mission Drive, Lanham, MD 20706 · NASA Marshall Space Flight Center, Huntsville, AL, 35808 USA.

  15. Advanced Flood Prediction with Physics-Guided Deep Learning: Combining UNet, FNO, and SAR/Optical Imagery

    Jun 2, 2026Tewodros Syum Gebre, Jagrati Talreja, Leila Hashemi-BeniFlood Inundation MappingPhysics-Informed ML

    Built Environment Department, College of Science and Technology, North Carolina A&T State University, Greensboro, NC 27405, USA · United Nations University Institute for Water, Environment and Health, Richmond Hill, ON, Canada

  16. Deep Learning for Remote Sensing to Improve Flood Inundation Mapping

    Jun 1, 2026Yogesh Bhattarai, Vijay Chaudhary, Wai Lim Kim +1Diffusion Models for Image RestorationFlood Inundation Mapping

    Department of Civil and Environmental Engineering Howard University Washington, D.C, 20060, USA. · Department of Computer Science and Electrical Engineering Howard University Washington, D.C, 20060, USA. · Department of Medicine Howard University Washington, D.C, 20060, USA.

  17. Overcoming "Physics Shock" in Earth Observation A Heteroscedastic Uncertainty Framework for PINN-based Flood Inference

    May 22, 2026Tewodros Syum Gebre, Jagrati Talreja, Matilda Anokye +1Remote Sensing Image SegmentationUncertainty Quantification

    Built Environment Department, College of Science and Technology, North Carolina A&T State University, Greensboro, NC 27405 USA · United Nations University Institute for Water, Environment and Health, Richmond Hill, ON, Canada

  18. Geometric Flood Depth Estimation: Fusing Transformer-Based Segmentation with Digital Elevation Models

    May 8, 2026Nhut Le, Ehsan Karimi, Maryam RahnemoonfarDepth EstimationFlood Inundation Mapping

    Lehigh University

  19. Cross-Polarization Fusion of VV AND VH SAR Observations for Improved Flood Mapping

    May 4, 2026Jagrati Talreja, Tewodros Syum Gebre, Leila Hashemi BeniRemote Sensing Image SegmentationFlood Inundation Mapping

    North Carolina A&T State University Greensboro, North Carolina, USA.

  20. FLoRA: Fusion-Latent for Optical Reconstruction and Flood Area Segmentation via Cross-Modal Multi-Task Distillation Network

    May 4, 2026Jagrati Talreja, Tewodros Syum Gebre, Leila Hashemi-BeniCross-Modal Knowledge DistillationMulti-Source Image Fusion

    Geomatics Program, College of Science and Technology, North Carolina A&T Technical State University, Greensboro, North Carolina 27411, USA · Institute for Water, Environment and Health, United Nations University, Richmond Hill, Ontario, Canada

  21. Continuous Flood Nowcasting in South Asia: A Multi-Sensor Ensemble Remote Sensing Framework for Flood Extent

    Apr 29, 2026Usman Nazir, Disha Gomathinayagam, Muhammad Kamran +1Flood Inundation MappingRemote Sensing

    Planetary Health Informatics (PHI) Lab, University of Oxford · Blavatnik School of Government, University of Oxford · PMIU Secretariat, Irrigation Department, Pakistan

  22. Urban Flood Observations: A hand-labeled training and validation dataset of post-flood inundation

    Apr 24, 2026Rohit Mukherjee, Hannah K. Friedrich, Beth Tellman +5Remote Sensing Image SegmentationFlood Inundation Mapping

    1Pacific Northwest National Laboratory, Richland, WA, USA · University of Arizona, Tucson, USA · University of Wisconsin–Madison, Madison, WI, USA +4

  23. A Deep U-Net Framework for Flood Hazard Mapping Using Hydraulic Simulations of the Wupper Catchment

    Apr 22, 2026Christian Lammers, Fernando Arévalo, Leonie Märker-Neuhaus +3Neural Surrogate ModelingU-Net

    Institute for Computing and Information Sciences Radboud University Nijmegen, Netherlands · Wupper Association (Wupperverband) Wuppertal, Germany

  24. Toward an Operational GNN-Based Multimesh Surrogate for Fast Flood Forecasting

    Apr 3, 2026Valentin Mercier, Serge Gratton, Lapeyre Corentin +1Flood ForecastingNeural Surrogate Modeling

    Toulouse INP, IRIT, EPE UT · Université de Toulouse, INP, IRIT, Toulouse, France · IRIT, EPE UT, Toulouse INP +3

  25. High Resolution Flood Extent Detection Using Deep Learning with Random Forest Derived Training Labels

    Mar 23, 2026Azizbek Nuriddinov, Ebrahim Ahmadisharaf, Mohammad Reza AlizadehFlood Inundation MappingRemote Sensing Image Segmentation

    Department of Civil Engineering, Florida State University, Tallahassee, FL, USA · Dept. of Biosystems & Agricultural Engineering, Michigan State University, East Lansing, MI, USA

  26. LLM-Powered Flood Depth Estimation from Social Media Imagery: A Vision-Language Model Framework with Mechanistic Interpretability for Transportation Resilience

    Mar 17, 2026Nafis Fuad, Xiaodong QianDepth EstimationIntelligent Transportation Systems

    Civil and Environmental Engineering Wayne State University 5050 Anthony Wayne Drive, Detroit, MI, USA, 48202 · Civil and Environmental Engineering Institute for AI and Data Science (AIDaS) Wayne State University 5050 Anthony Wayne Drive, Detroit, MI, USA, 48202

  27. Quantum-Enhanced Vision Transformer for Flood Detection using Remote Sensing Imagery

    Mar 14, 2026Soumyajit Maity, Behzad GhanbarianVision TransformerRemote Sensing Image Understanding

    iResearchE3 Lab, Department of Earth and Environmental Sciences, University of Texas at Arlington, Arlington, TX, USA