基于变化向量分析（CVA）的土地利用／覆盖变化动态监测（Ⅱ）—变化类型的确定方法

以光谱直接比较为基础的变化向量分析法是一种非常有效的土地利用／覆盖变化动态监测方法，在双窗口变步长阈值搜寻方法确定变化和非变化像元的基础上，提出了参考图像分类并结合变化向量方向余弦最小距离分类的变化类型确定方法，同时应用该方法在北京市海淀区进行了实验研究，得到了较为理想的结果。变化类型的判断精度达到70％以上，显示了新方法的优越性和技术可行性。

Land Use/Cover Change Detection with Change Vector Analysis (CVA): Change Type Determining

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.