Urban land cover information extraction combining spectral feature and oriented-object analysis

It is well known that land cover change has important implication on urban planning, urban environment evaluation and so on. However, urban land cover information is not easy to be extracted because of its inner complexity resulting from human impact. Under this circumstance, the accurate recognition and classification of different land use types on urban area from remote sensing data has become an important task. This paper introduces an effective method, which relies on the typical ground objects' spectral responding features and interacting mechanisms, to undertake classification hierarchically. It can, effectively, reduce spectral variation in the scene origin from complex pattern of urban fields.