Object-Oriented Classification Method on High Resolution Satellite Data

摘要

To traditional moderate or low resolution satellite data, the data processing or information detecting is only on a per-pixel basis because of the impacts to geometric accuracy of spatial resolution. Thereby only the spectral information is used for the classification. High spatial resolution sensors involves a general increase of spatial information and the accuracy of results may decrease on a per-pixel basis. In order to realize the full potential of the VHR image data, An object-oriented image analysis is implementation with the software cognition. It is based on fuzzy logic, allows the integration of different object features, such as spectral values, shape and texture. In this paper we analysis an object-oriented classification method using QuickBird panchromatic and multispectral data on the test area of the PuDong New district of Shanghai analysis includes two parts: first dividing the image data into segments and then classifying the segments by means of fuzzy approach of nearest neighbor classifier.