DISCRIMINATION OF VEGETATION-IMPERVIOUS SURFACE-SOIL CLASSES IN URBAN ENVIRONMENT USING HYPERSPECTRAL DATA

摘要

We present, in this paper, discrimination analysis performed for vegetation, impervious surfaces, and soil (VIS) classes in urban environment. We extracted spectral signatures of VIS classes from EO-1 Hyperion image and used Spectral Angle Mapper (SAM) for subsequent classification. Further, we recorded field signatures of some typical urban materials such as concrete, bitumen, soils etc. Preliminary analysis indicates that spectral resolution of 10 nm is sufficient to differentiate VIS classes at different level of class granularity. Image derived signatures (and field signatures) of VIS classes are separable and show distinct spectral curves at broader level. Image derived signatures show very good classification accuracy for VIS classes (87% average overall accuracy with 98% best and 77% worst accuracies). Inter class confusion between bare soil and stone quarry, and concrete (residential) is evident from results.