利用高分辨率光学遥感图像检测震害损毁建筑物

地震发生后，利用高分辨率遥感图像进行建筑物损毁检测，有利于快速评估灾害损失。在分析损毁建筑物梯度分布的基础上，提出了一种利用梯度局部空间统计检测震害损毁建筑物的方法。首先用Prewitt算子提取图像梯度信息；然后对梯度图像进行局部空间统计，统计各建筑物屋顶内部梯度的空间相关性，得到初步损毁检测结果；最后，在先验知识的指导下进行极小值分析和阴影检测，进一步修正建筑物损毁检测结果。分别以玉树地震后的Quickbird卫星遥感图像和盈江地震后的光学航空图像为例进行实验，结果表明，利用梯度局部空间统计检测震害损毁建筑物的方法效果优于传统损毁检测方法，总体精度达到80%以上，能够有效检测损毁建筑物。

Detecting Damaged Buildings Caused by Earthquake from Remote Sensing Image Using Local Spatial Statistics Method

Damaged buildings detection from high-resolution remote sensing image helps to quick disaster losses evaluation after the earthquake. This paper presents a new method to detect damaged buildings using spectral gradient local spatial statistics, based on the analysis of gradient distribution characteristics of damaged buildings in the high-resolution remote sensing image. Firstly, spectral gradient image is obtained by Prewitt gradient operator. Secondly, local spatial statistics is used to evaluate the spectral gradient correlation within the roofs, and to generate the preliminary results. At last, the post processing steps, including minimal value analysis and shadow detection, are taken to optimize preliminary results and obtain the final results. The experiment results using a Quickbird image of Yushu earthquake and optical aerial image of Yingjiang earthquake demonstrate the effectiveness of the proposed method, which provides an overall accuracy of higher than 80%, are better than traditional methods.