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A Comparison of Two Object-Oriented Methods for Land-Use/Cover Change Detection with SPOT 5 Imagery

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Change detection techniques based on high-spatial resolution imageries have been widely applied in environment monitoring, land management, dynamic monitoring of the military battlefield. In this paper, two methods including (1) object-oriented change detection based on post-classification comparison (CDBPC), (2) object-oriented change detection based on multi-feature (CDBMF) were put forward and compared to determine which method was more effective. The ample spectral information, textural information, structure information of high-spatial resolution SPOT 5 imageries were utilized synthetically in both two methods. In contrast to CDBPC, CDBMF did change classification only once, thus it avoided the accumulated classification error. Accuracy assessment shows that CDBMF is more favorable for land-use/cover change detection, and the overall accuracy has been improved significantly from 80.00% to 86.67%.


Document Type: Research Article


Publication date: 2012-01-01

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