Detection of areas associated with flood and erosion caused by a heavy rainfall using multitemporal landsat TM data

作者：Dhakal AS^*; Amada T; Aniya M; Sharma RR

来源：Photogrammetric Engineering and Remote Sensing, 2002, 68(3): 233-239.

The potential of multitemporal Landsat Thematic Mapper (TM) data was examined for its use in detecting areas affected by flood and erosion ftom a heavy rainfall, The study area is the Kulekhani watershed (124 km(2)) located in the central region of Nepal. Four change-detection techniques were compared for their effectiveness including (1) Spectral Image Differencing, (SID), (2) Tasseled Cap Brightness Image Differencing (TCBID), (3) Principal Component Analysis (PCA), and (4) Spectral Change Vector Analysis (SCVA). SID was performed on four raw bands (bands 1, 2, 3, and 7), and altogether seven new images (change images) were produced.
Visible bands were effective in detecting affected areas. SCVA (using bands 1, 2, and 3) was found to be most accurate for detecting areas affected by flood and erosion followed by SID (band 2), PCA (using bands 1, 2, and 3), SID (band 1), and SID (band 3). The change image produced from SCVA showed overall and Khat accuracies of 88.3 percent and 75.4 percent, respectively. The analysis of spatial agreement conducted among the seven change images, produced from different techniques, varied from 89 percent to 98 percent. The change image produced from SCVA showed high spatial agreements with change images produced from PCA, SID (band 3), and SID (band 2). SCVA and SID (band 3) showed the spatial agreement of 88.1 percent and 98.7 percent in the change and no-change p categories, respectively.

• 出版日期2002-3