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ARMA 12-379 Automatic Detection of Landslides Induced by the Wenchuan Earthquake and Subsequent Rainstorm

机译:ARMA 12-379自动检测汶川地震和随后的暴雨诱导的滑坡

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We developed a two-step detection approach to map landslides in Chenjiaba area, Beichuan County; Sichuan Province, China after the 2008 Wenchuan earthquake and a strong rainfall four months later. First, the variance information was assessed by image fusion technique. Different from traditional usage of image fusion technique, this paper aims to enhance the interesting features through combing multispectral image with high resolution and panchromatic image with relatively lower resolution. Four fusion technologies (PCA, Brovey, IHS and Wavelet) were tested. All the results contain the spectrum information of both earthquake and rainfall-induced landslides, except the one by wavelet transform based fusion method. The fusion results were assessed by visual inspection and IHS transform based fusion image shows the best performance. Second, fusion image was semi-automatically interpreted. The image interpretation was based on object-oriented analysis which not only the spectral information in pixel-based method was considered, but also the spatial and texture information of the image. Various landscape elements were classified by K Nearest Neighbor algorithm for landslide detection. Accuracy assessment was carried out by comparing those extracted ones with a manually prepared landslide inventory map. Results showed that this approach is capable of mapping different temporal landslides quickly and efficiently.
机译:我们制定了一项两步检测方法来映射蔡川县陈家坝地区的山体滑坡;四川省中国经过2008年汶川地震和四个月后的大雨。首先,通过图像融合技术评估方差信息。与传统的图像融合技术不同,本文旨在通过用高分辨率和具有相对较低分辨率的高分辨率和全形图像来梳理多光谱图像来增强有趣的特征。测试了四种融合技术(PCA,Brovey,IHS和小波)。所有结果都包含地震和降雨诱导的山体滑坡的频谱信息,除了基于小波变换的融合方法之外。通过目视检查评估融合结果,基于IHS变换的融合图像显示了最佳性能。其次,融合图像是半自动解释的。图像解释基于面向对象的分析,其不仅考虑了基于像素的方法的光谱信息,而且是图像的空间和纹理信息。通过K最近邻域算法进行各种景观元素进行滑坡检测。通过将提取的Landslide Inventory Map比较,通过将提取物的提取物进行比较来进行精度评估。结果表明,这种方法能够快速有效地映射不同的时间山体滑坡。

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