Detailed Record



MAPPING NEWLY INUNDATED AREAS IN POST-FLOOD LANDSAT IMAGES USING THRESHOLDING TECHNIQUES


Abstract Identifying newly inundated areas following flood events is essential for planning rescue missions. These maps must be generated quickly as the spatial extent of the inundated areas might change during a single flood event. Several methods exist for generating such maps and several rely on one or more geospatial data to exclude existing waterbodies in an affected area. In this study, we tested a rapid flood mapping method that uses a pair of pre- and post-flood satellite images on seven sites throughout the US. We derived Normalized Difference Water Index (NDWI) and Modified NDWI (MNDWI) images from pre- and post-flood Landsat images and identified the optimal threshold values that highlighted newly inundated areas at these sites. The accuracy of the inundation maps was determined using manually interpreted verification data from the pairs of satellite images. Image analysts have identified the optimal threshold values between 25 and 40 minutes. Maps of newly inundated areas derived from differencing MNDWI and NDWI images had higher overall accuracy > 93%. Results obtained in this study confirms the utility of this rapid flood mapping technique to identify inundated areas using pre- and post-flood satellite images.
Authors Ramesh Sivanpillai University of WyomingORCID , Margarita V. Oreshkina University of WyomingORCID , Phyllis D. Bear University of Wyoming , I. Boettcher University of Wyoming , T. Bradshaw University of Wyoming , I. Coleman University of Wyoming , John Gifford University of Wyoming
Journal Info Copernicus Publications | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences , vol: XLVIII-M-3-2023 , pages: 235 - 239
Publication Date 9/5/2023
ISSN 1682-1750
TypeKeyword Image article
Open Access gold Gold Access
DOI https://doi.org/10.5194/isprs-archives-xlviii-m-3-2023-235-2023
KeywordsKeyword Image Flood Inundation Modeling (Score: 0.628142) , Surface Water Mapping (Score: 0.61781) , Urban Flooding (Score: 0.57112) , Hydrological Modeling (Score: 0.531264) , Watershed Prioritization (Score: 0.526299)