A rapid extraction of landslide disaster information research based on GF-1 image

Sai Wang, Suning Xu, Li Peng, Zhiyi Wang, Na Wang
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引用次数: 3

Abstract

In recent years, the landslide disasters occurred frequently because of the seismic activity. It brings great harm to people's life. It has caused high attention of the state and the extensive concern of society. In the field of geological disaster, landslide information extraction based on remote sensing has been controversial, but high resolution remote sensing image can improve the accuracy of information extraction effectively with its rich texture and geometry information. Therefore, it is feasible to extract the information of earthquake- triggered landslides with serious surface damage and large scale. Taking the Wenchuan county as the study area, this paper uses multi-scale segmentation method to extract the landslide image object through domestic GF-1 images and DEM data, which uses the estimation of scale parameter tool to determine the optimal segmentation scale; After analyzing the characteristics of landslide high-resolution image comprehensively and selecting spectrum feature, texture feature, geometric features and landform characteristics of the image, we can establish the extracting rules to extract landslide disaster information. The extraction results show that there are 20 landslide whose total area is 521279.31 ㎡.Compared with visual interpretation results, the extraction accuracy is 72.22%. This study indicates its efficient and feasible to extract earthquake landslide disaster information based on high resolution remote sensing and it provides important technical support for post-disaster emergency investigation and disaster assessment.
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基于GF-1图像的滑坡灾害信息快速提取研究
近年来,由于地震活动的影响,滑坡灾害频发。它给人们的生活带来了极大的危害。引起了国家的高度重视和社会的广泛关注。在地质灾害领域,基于遥感的滑坡信息提取一直存在争议,而高分辨率遥感影像丰富的纹理和几何信息可以有效提高信息提取的准确性。因此,对地表破坏严重、规模大的地震诱发滑坡进行信息提取是可行的。本文以汶川县为研究区,利用国内GF-1影像和DEM数据,采用多尺度分割方法提取滑坡影像对象,并利用尺度参数估计工具确定最佳分割尺度;综合分析滑坡高分辨率图像的特征,选取图像的光谱特征、纹理特征、几何特征和地形特征,建立提取规则,提取滑坡灾害信息。提取结果表明,滑坡共20处,总面积521279.31㎡。与目视解译结果比较,提取准确率为72.22%。研究表明,基于高分辨率遥感提取地震滑坡灾害信息是有效可行的,为灾后应急调查和灾害评估提供了重要的技术支持。
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