Study on the classification of hyperspectral data in urban area

A new method for classifying hyperspectral remote sensing data in urban area is described in this paper, that combines the edge detection and spectral analysis together. Due to the varied surface scene in city and limitation of imaging spectrometer's signal-to-noise ratio, normal classification based on pixels were not satisfied for thematic classification and mapping in urban area. This technique will improve such situation, which perform every classes with not only their similar spectral features but also the object's geometric and edge characters.