Spectral Classification of Man-made Materials in Urban Area Using Hyperspectral Data

초록

Hyperspectral data has a great advantage to classify various surface materials that are spectrally similar. In this study, we attempted to classify man-made materials in urban area using Hyperion data. Hyperion imagery of Seoul city was initially processed to minimize radiometric distortions caused by sensor and atmosphere. Using color aerial photographs and topographic maps, we defined five man-made surfaces (concrete, asphalt road, buildings, roof, soil, shadow) for the classification in Seoul. The hyperspectral data showed the potential to identify those man-made materials that were difficult to be classified by multispectral data. However, the classification of road and buildings was not quite satisfactory due to the relatively low spatial resolution of Hyperion image. Further, the low radiometric quality of Hyperion sensor was another limitation to the application in urban area.