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Information extraction of typical karst landform based on RS

机译:基于RS的典型喀斯特地貌信息提取

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Guizhou Province is the most typical karst landform area of Southwest China Karst, and how to exactly extract the typical karst landform information is important to the economic development of Guizhou. Not any method based on Remote Sensing (Hereinafter referred to as RS) to extract the karst landform were reported or published. For obtaining the accuracy information of karst landform, 10 meters resolution ALOS image is used to extract the karst landform information in Guanling County of Guizhou Province in this paper. The multiscale segmentations of RS images were finished and typical of karst landform in case study area were classified with the different segmentation rules created on the eCognition Developer platform. For mostly improving the accuracy of extraction information, the experiment areas are focused on the fengcong depressions, fengcong valleys, and fenglin basins. The results show that the fengcong depressions, fengcong valleys, and fenglin basins can be respectively well extracted from the images when the segmentation scale are respectively 280, 480 and 200, shape parameter is 0.8, and tightness parameter is 0.5. We believed the research would provide an important reference to extract the karst landform information in whole Guizhou, China or global level.
机译:贵州省是中国西南岩溶最典型的岩溶地貌区,如何准确提取典型的岩溶地貌信息对贵州的经济发展具有重要意义。没有报道或发表任何基于遥感(以下简称RS)的岩溶地貌提取方法。为了获得岩溶地貌的精度信息,本文采用10米分辨率的ALOS图像提取贵州省关岭县的岩溶地貌信息。完成了RS图像的多尺度分割,并使用在eCognition Developer平台上创建的不同分割规则对案例研究区的典型喀斯特地貌进行了分类。为了最大程度地提高提取信息的准确性,实验区域集中在峰丛洼地,峰丛谷和峰林盆地。结果表明,当分割尺度分别为280、480和200,形状参数为0.8,密封性参数为0.5时,可以分别从图像中很好地提取峰丛洼地,峰丛谷和峰林盆地。我们相信这项研究将为提取整个贵州,中国乃至全球范围内的喀斯特地貌信息提供重要参考。

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