面向对象的高分辨率遥感影像建筑物变化检测

Object-oriented Detection of Building Changes Based on High Spatial Resolution Remote Sensing Image

以武汉市东湖高新技术开发区部分区域为研究区,提出基于面向对象的高分辨率遥感影像建筑物变化检测法.利用BMI算法提取建筑物,利用CVA算法进行变化检测得到全部对象差异度,利用EM算法的贝叶斯阈值计算方法确定变化阈值.结果表明,基于面向对象的变化检测总体精度为89.48%,Kappa系数为0.86,优于基于像元的变化检测,为高分辨率遥感影像建筑物的变化检测提供了一种新的思维方式和方法.

Based on the object-oriented method of building change detection,a new method of building change detection based on high-resolution remote sensing image is proposed.BMI algorithm was used to extract buildings,CVA algorithm was used to detect changes to obtain all object differences,and the bayesian threshold calculation method of EM algorithm was used to determine the change threshold.The results show that the overall accuracy of object-based change detection is 89.48%and the Kappa coefficient is 0.86,which is superior to pixel-based change detection and provides a new way of thinking and method for the change detection of buildings with high-resolution remote sensing image.