Journal article
Modeling floodplain inundation using an integrated GIS with radar and optical remote sensing
Geomorphology, Vol.21(3-4), pp.295-312
1998
Abstract
Synthetic aperture radar images from multitemporal L-band JERS-1 and C-band ERS-1 satellites, a Landsat Thematic Mapper (TM) time-series, and GIS coverages were used in an integrative approach to model the potential of flood inundation within the lower Roanoke River floodplain, North Carolina. A digital elevation model (DEM) with one-meter vertical resolution was developed for the region from scan-digitized mylar separates of contour lines on USGS 7.5-min quadrangles. Several models representing potential wetness and potential flood inundation were generated from the DEMs using both raster (grid) and vector (network) analyses. The potential inundation surfaces were derived from regression models that related known flood elevations to river position and floodplain location. The GIS models were assessed by comparison to classifications of flood change-detection achieved through the radar data. Statistical results indicate that the GIS-derived models successfully identified flooded areas as mapped by the radar change-detections. Further, statistical tests assessed the ability of individual radar and optical (Landsat TM) images to discriminate flooding as predicted by the GIS models. Both JERS-1 and ERS-1 images identified areas of inundation at different flood levels.
Details
- Title
- Modeling floodplain inundation using an integrated GIS with radar and optical remote sensing
- Authors
- P A Townsend (Author) - University of North Carolina at Chapel Hill, United StatesStephen J Walsh (Author) - University of North Carolina at Chapel Hill, United States
- Publication details
- Geomorphology, Vol.21(3-4), pp.295-312
- Publisher
- Elsevier BV
- Date published
- 1998
- DOI
- 10.1016/S0169-555X(97)00069-X
- ISSN
- 0169-555X
- Organisation Unit
- University of the Sunshine Coast, Queensland
- Language
- English
- Record Identifier
- 99449303802621
- Output Type
- Journal article
Metrics
553 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Geography, Physical
- Geosciences, Multidisciplinary
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites