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An area change detection method of remote sensing image using historical land use graph

机译:历史土地利用图的遥感图像的区域改变检测方法

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Kinds of historical vector graphs have been gradually accumulated by ground truth data or other reliable sources, but these data have not been fully adopted to detect change in remote sensing circle. In this paper we describe a novel change detection method. The key feature of the new method is the use of a piece of historical land using vector graph. By combing one satellite image and the vector graph after necessary geometric rectification, we could detect change region of the satellite image corresponding to patches in the vector graph. Through adopting coefficient of part change and coefficient of entire change, the study calculates statistics indexes of image corresponding to patches of vector graph with different coefficient groups and assesses the computing results by kappa matrix. According to analytical results, the coefficient of entire change is more important to the number of commission error than the coefficient of part change. This method is benefit to the reuse of historical vector graphs. As the image-processing work of this method is based on patches of historical vector graph, it helps to the development of different vector graphs.
机译:各种历史矢量图已被地面真实数据或其他可靠源逐渐累积,但这些数据尚未完全采用以检测遥感圆圈的变化。在本文中,我们描述了一种新颖的变化检测方法。新方法的关键特征是使用一块历史土地使用矢量图。通过在必要的几何整流之后梳理一个卫星图像和矢量图,我们可以检测与矢量图中的贴片相对应的卫星图像的变化区域。通过采用部分变化系数和整个变化系数,研究计算与不同系数组的矢量图斑块对应的图像的统计指标,并评估Kappa矩阵的计算结果。根据分析结果,整个变化系数对于佣金误差的数量比零件变化系数更重要。这种方法有利于历史矢量图的重用。随着该方法的图像处理工作基于历史矢量图的斑块,它有助于开发不同的矢量图。

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