Application of Object-Oriented Approach to SPOT5 Image Classification:A Case Study in Haidian District,Beijing City
SPOT5 image is widely used in urban planning, investigation of land utilization, environmental management, public security etc.for its relatively high- resolution and cheap price. Classical classification approaches based on pixels have a low overall accuracy and can not satisfy the application demand in reality due to SPOT5 image having higher resolution and more local heterogeneity. In this paper, object - oriented approach is introduced into SPOT5 image classification. And a general approach and workflow are illustrated on applications of object - oriented approach for high - resolution image classification. Taking Haidian District; Beijing City as the test area, a case study on SPOT5 image classification with object- oriented approach is carried out. In order to verify the accuracy of object - oriented classification, a comparison between this approach and classical classification approaches has been carried out. The case study shows that the application of object- oriented approach on SPOT5 image classification not only can have more semantic information, reduce the "Pepper and Salt Phenomenon" effectively,but also can improve the overall classification accuracy of SPOT5 image.
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