A METHOD TO GENERATE FLOOD MAPS IN 3D USING DEM AND DEEP LEARNING

8 citations as recorded by crossref.

1. U-net-based semantic classification for flood extent extraction using SAR imagery and GEE platform: A case study for 2019 central US flooding Z. Li & I. Demir https://doi.org/10.1016/j.scitotenv.2023.161757
2. SSegRef2Surf—Near Real-Time Photogrammetric Flood Monitoring and Refinement of Classified Water Surfaces M. Kögel et al. https://doi.org/10.3390/rs17081351
3. Using structure from motion for analyzing change detection and flood events in the context of flood preparedness: a case study for the Laufer Muehle area at the Aisch river in Germany for conducting near real-time analyses M. Kögel & D. Carstensen https://doi.org/10.1007/s12518-024-00561-y
4. An opportunity missed is an opportunity lost. Flood maps and their (non-)utilization by local government bodies in the Czech Republic K. Klemešová et al. https://doi.org/10.2478/mgr-2024-0011
5. An Evaluation of Risk-Based Agricultural Land-Use Adjustments under a Flood Management Strategy in a Floodplain M. Tariq et al. https://doi.org/10.3390/hydrology8010053
6. Three-Dimensional Inundation Mapping Using UAV Image Segmentation and Digital Surface Model A. Gebrehiwot & L. Hashemi-Beni https://doi.org/10.3390/ijgi10030144
7. High Resolution 3D Mapping of Hurricane Flooding from Moderate-Resolution Operational Satellites S. Li et al. https://doi.org/10.3390/rs14215445
8. Near real-time change detection tool for photogrammetric flood preparedness M. Kögel & D. Carstensen https://doi.org/10.1007/s10661-024-13597-9