Title :
Postflood damage evaluation using Landsat TM and ETM+ data integrated with DEM
Author :
Gianinetto, Marco ; Villa, Paolo ; Lechi, Giovanmaria
Author_Institution :
Politecnico di Milano Univ., Milan, Italy
Abstract :
In recent decades, radar and optical satellite imagery have been used for evaluating flooding extent. In this paper, a straightforward technique based on the sequential use of the spectral-temporal principal component analysis, logical filtering, and image segmentation integrated with the digital elevation model was developed as a decisional support tool for the allocations of the resource destined for the flooded areas. The mapping technique was first applied to the catastrophic event that occurred in the Piemonte Region (Italy) in November 1994, which was the worst event of the past century for that region, with 44 casualities and over 2000 homeless. Next, it was applied to the Obion/Forked Deer inundation that occurred in Tennessee (U.S.) between November and December 2001, in which heavy damage to the infrastructure was reported. Two Landsat-5 Thematic Mapper (path 194, row 28/29) and two Landsat-7 Enhanced Thematic Mapper Plus (path 23, row 35) images were processed, two of them collected before and two after the events. The method proposed proved to be an effective approach for evaluating flood extent and for assessing the damage produced by the flooding. An overall accuracy of 85.6%, a user accuracy of 87.5%, and a producer accuracy of 97.5% were achieved, and an agreement of 83% between ground measures and remotely sensed data in the estimation of flood water volumes was also achieved on a regional scale.
Keywords :
disasters; floods; geophysical signal processing; hydrological techniques; image segmentation; principal component analysis; terrain mapping; AD 1994 11; AD 2001 11 to 12; ETM+ data; Italy; Landsat-5 Thematic Mapper; Landsat-7 Enhanced Thematic Mapper Plus; Obion/Forked Deer inundation; Piemonte Region; Tennessee; USA; catastrophic event; damage assessment; digital elevation model; flood extent; flood water volume estimation; image processing; image segmentation; infrastructure damage; inundation maps; logical filtering; postflood damage evaluation; remote sensing; resource allocations; spectral-temporal principal component analysis; Digital filters; Floods; Laser radar; Optical filters; Optical sensors; Principal component analysis; Radar imaging; Remote sensing; Satellites; Spaceborne radar; Algorithms; Landsat; image processing; inundation maps;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2005.859952