Object-oriented hierarchical identification of earthquake-induced landslides based on high-resolution remote sensing images

LI Chenhui; HAO Lina; XU Qiang; WANG Yi; YAN Lihua

doi:10.6046/zrzyyg.2022013

2023 Vol. 35, No. 1

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Article navigation > Remote Sensing for Natural Resources > 2023 > 35(1): 74-80

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LI Chenhui, HAO Lina, XU Qiang, WANG Yi, YAN Lihua. 2023. Object-oriented hierarchical identification of earthquake-induced landslides based on high-resolution remote sensing images. Remote Sensing for Natural Resources, 35(1): 74-80. doi: 10.6046/zrzyyg.2022013

Citation:

LI Chenhui, HAO Lina, XU Qiang, WANG Yi, YAN Lihua. 2023. Object-oriented hierarchical identification of earthquake-induced landslides based on high-resolution remote sensing images. Remote Sensing for Natural Resources, 35(1): 74-80. doi: 10.6046/zrzyyg.2022013

Object-oriented hierarchical identification of earthquake-induced landslides based on high-resolution remote sensing images

1. School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China；
2. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu 610059, China

Received Date: 12 January 2022

Revised Date: 15 March 2023

Publish Date: 20 March 2023

Abstract

Abstract

Earthquake-induced landslides are unnegligible secondary earthquake disasters and tend to cause severe casualties and property loss. Remote sensing identification of earthquake-induced landslides is an important means of the investigation and assessment of post-earthquake disasters. With GF-1 remote sensing images as a data source, this study identified the earthquake-induced landslides in the Xiongmaohai area in Jiuzhaigou using the object-oriented classification method. Specifically, the rule set for hierarchical identification of earthquake-induced landslides was constructed based on multi-scale segmentation and multi-conditional threshold classification. The aim is to fully utilize the features of ground objects, reduce the mixing of ground objects with similar spectra, and improve the identification precision of landslides. The identification results show that about 2.18 km2 of landslide area was extracted near the Xiongmaohai scenic spot, with a general identification accuracy of up to 98.11%. Therefore, the method proposed in this study can quickly identify earthquake-induced landslides, with high identification accuracy and applicable identification rules, and, thus, can be used as a reference and basis for the emergency investigation and rapid loss assessment of post-earthquake disasters.
- earthquake-induced landslide /
- object-oriented /
- hierarchical identification of landslides /
- slope variability

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References

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