Landslide identification in Jinsha River basin based on high-resolution remote sensing:taking Wangdalong village of Batang county as an example

doi:10.13474/j.cnki.11-2246.2022.0109

Bulletin of Surveying and Mapping ›› 2022, Vol. 0 ›› Issue (4): 51-55.doi: 10.13474/j.cnki.11-2246.2022.0109

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Landslide identification in Jinsha River basin based on high-resolution remote sensing:taking Wangdalong village of Batang county as an example

DING Yonghui¹, ZHANG Qing¹, YANG Chengsheng¹, WANG Meng², DING Hui³

1. School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China;
2. Sichuan Institute of Geological Survey, Chengdu 610081, China;
3. Xi'an Center of China Geological Survey, Xi'an 710054, China

Received:2021-06-15 Online:2022-04-25 Published:2022-04-26

Abstract

Abstract: Because of the steep terrain,the development of soft rock,and the concentration of rainfall on both sides of the Jinsha River basin,the landslide disasters are densely distributed in the basin.High-resolution remote sensing is an important means of landslide identification,but the visual interpretation method for large-scale landslide hazard identification has the characteristics of heavy workload and low efficiency.In this paper,the object-oriented classification method is used to identify the large-scale landslides in Jinsha River basin.The spectrum,shape and space characteristics of landslides are used to identify the landslides in the region.At the same time,the Wangdalong village section of Batang county in the Jinsha River basin is selected for the identification and extraction of landslides.In this area,18 landslides are identified by object-oriented classification method,12 of which are the same as the results of visual interpretation,and the consistency is 75%.In addition,3 hidden landslides are found which are not identified by visual interpretation.The results show that the recognition effect of this method is good,which can provide a reference for the subsequent large-scale landslide identification extraction and landslide cataloging work in the Jinsha River basin and even along the Sichuan-Tibet railway.

Key words: Jinsha River landslide, optical remote sensing, object-oriented analysis, landslide identification, disasterprevention and reduction

CLC Number:

P237

DING Yonghui, ZHANG Qing, YANG Chengsheng, WANG Meng, DING Hui. Landslide identification in Jinsha River basin based on high-resolution remote sensing:taking Wangdalong village of Batang county as an example[J]. Bulletin of Surveying and Mapping, 2022, 0(4): 51-55.

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Landslide identification in Jinsha River basin based on high-resolution remote sensing:taking Wangdalong village of Batang county as an example

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