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首页> 外文期刊>Computers & geosciences >A new technique for landslide mapping from a large-scale remote sensed image: A case study of Central Nepal
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A new technique for landslide mapping from a large-scale remote sensed image: A case study of Central Nepal

机译：一种基于大规模遥感影像的滑坡测绘新技术：以尼泊尔中部为例

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摘要

This paper presents a new technique for landslide mapping from large-scale Landsat8 images. The method introduces saliency enhancement to enhance the landslide regions, making the landslides salient objects in the image. Morphological operations are applied to the enhanced image to remove most background objects. Afterwards, digital elevation model is applied to further remove the ground objects of plain areas according to the height of landscape, since most landslides occur in mountainous areas. Final landslides are extracted by the proposal regions from selective search. The study area covers 2 degrees x2 degrees, making it more similar with practical cases, such as emergency response and landslide inventory mappings. The proposed method performs satisfactorily by detecting 99.1% of the landslides in the image, and obtains an overall accuracy of 99.8% in the landslides/background classification problem, which gets further validated in another Landsat8 image of a different site. The experiment shows that the proposed method is feasible for landslide detection from large-scale area, which may contribute to the further landslide-related research.
机译：本文提出了一种从大规模Landsat8图像进行滑坡映射的新技术。该方法引入了显着性增强以增强滑坡区域，使滑坡成为图像中的显着对象。将形态学操作应用于增强的图像以去除大多数背景对象。此后，由于大多数滑坡发生在山区，因此应用数字高程模型根据景观高度进一步去除平原地区的地面物体。建议区域从选择性搜索中提取最终的滑坡。研究区域覆盖2度x2度，使其与实际案例更加相似，例如应急响应和滑坡清单映射。该方法通过检测图像中99.1％的滑坡而表现令人满意，并且在滑坡/背景分类问题中获得了99.8％的总体准确度，并在不同地点的另一幅Landsat8图像中得到了进一步的验证。实验表明，该方法对于大面积滑坡的检测是可行的，可能有助于进一步的滑坡相关研究。

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  • 来源
    《Computers & geosciences》 |2017年第3期|115-124|共10页
  • 作者

    Yu Bo; Chen Fang;

  • 作者单位

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China;

    Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China|Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Hainan Key Lab Earth Observat, Sanya 572029, Peoples R China|Univ Chinese Acad Sci, Beijing 100049, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Landslide detection; Selective search; Saliency enhancement; Morphological operation;

    机译：滑坡检测;选择性搜索;显着性增强;形态学操作;

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