Flood Damage Analysis using Landsat TM: Change Vector Analysis Approach

摘要

It is increased to utilize satellite image and get information little by little in nowadays. For example, satellite images are used to monitor landslides, earthquakes, volcanoes, ground subsidence and so on. Change detection and analysis is a powerful application of remote sensing, in that the spectral resolution of multi-band sensors can be used to advantage in monitoring both significant and subtle land cover changes over time. In this study, the Landsat TM data was used to detect change areas affected by flood from a heavy rainfall. The study area is the Nakdong River located in the Korean peninsular. Among the several change detection techniques, change vector analysis (CVA), principle component analysis (PCA) and image difference approachs are utilized in this paper. CVA uses any number of spectral bands from multi-date satellite data to produce change image that yield information of the magnitude and direction of differences pixel value. And accuracy assessment was carried out with a change image produced from three techniques. In result, CVA was found to be the most accurate for detecting areas affected by flood with the overall accuracy and Kappa coefficient of 97.27 percent and 94.45 percent, respectively.