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《Journal of Remote Sensing》 2001-05
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Land Use/Cover Change Detection with Change Vector Analysis (CVA): Change Type Determining

CHEN Jin, HE Chun-yang, ZHUO Li (Institute of Resource Science, Beijing Normal University, Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education of China, Beijing Normal University, Beijing 100875, China)  
Remote sensing provides a viable source of data from which land use/cover changes information can be extracted efficiently and cheaply. During the past two decades, there has been a growing interest in the development of change detection technique based on remote sensing data, and a number of techniques for accomplishing change detection using satellite image data have been formulated, applied, and evaluated. As a direct spectral comparison approach, change vector analysis (CVA) is an effective method for land use/cover detection. Based on the method named as Double-Windows Flexible Pace Searching for change magnitude threshold determination, which was proposed in the previous paper, the change pixels have been detected successfully from the TM image in 1991 and 1997. This paper presents new methods of determining change direction (change type) which combines single image classification and minimum distance categorizing based upon change vector direction cosine. Furthermore, This new method is applied to land use/cover change detection in the image of Haidian district of Beijing and the result is satisfactory. The overall precision rate of distinguishing change type arrives above 70%. It shows that the new method have many advantages and is practicable.
【Fund】: 国家自然科学基金重大项目 ( 39899374);; 教育部高等学校重点实验室访问学者基金资助
【CateGory Index】: TP751.1
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