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Earthquake-induced landslide recognition using high-resolution remote sensing images

  • role： First author第一作者
  • Affiliation：

    China Institute of Geo-Environment Monitoring, Beijing 100081, China

  • Email：penglmail@126.com
  • Introduction：彭令(1984—　)，男，博士研究生，研究方向为地质灾害与遥感应用。E-mail：penglmail@126.com
PENG Ling1,  
  • Affiliation：

    China Institute of Geo-Environment Monitoring, Beijing 100081, China

XU Suning1,  
  • Affiliation：

    China Institute of Geo-Environment Monitoring, Beijing 100081, China

MEI Junjun1,  
  • Affiliation：

    Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China

SU Fenghuan2

Resümee

Earthquake-induced landslides are the most common geological disasters caused by large seismic activities in mountainous areas, and they are known for their suddenness, destructiveness, and extensive distribution range. These landslides often result in severe casualties and economic losses. Currently, regional earthquake-induced landslides are mainly obtained by visual interpretation and computer data extraction from remote sensing images. These methods are objective, time-consuming, and low in precision. Thus, they cannot address the requirement of practically conducting emergency surveys and disaster evaluations after earthquakes. In this study, with the main data source of high-resolution remote sensing images from ZY-3 and GF-1, as well as the study area of the Wenchuan earthquake region, objects of multilevel landslides were established using the multi-scale optimum partition method based on an in-depth analysis of seismic landslide features. A recognition rule set of multi-dimensional landslides was also built by combining topographic and image features, such as spectrum, texture, and geometry. Additionally, recognition models for landslide stratification were proposed based on the recognition models of high-resolution images and an understanding of the scenes. Through all of the preceding efforts mentioned, the spatial distribution of the seismic landslide, as well as the sliding source, transport, and depositional areas, can be identified. The analysis results of the experimental area showed a minimum recognition accuracy of 81.89%, with the depositional zone of landslides being the easiest zone to recognize, and the established method can be generalized. These findings may provide technical support for post-earthquake emergency investigations and further promote the application of high-resolution remote sensing data from Chinese satellites for landslides recognition.

Schlüsselwort

earthquake-induced landslides;landslide recognition;high-resolution remote sensing;Chinese satellite;Wenchuan earthquake

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