Enhanced detection of freeze‒thaw induced landslides in Zhidoi county(Tibetan Plateau,China)with Google Earth Engine and image fusion  

作　　者：Jia-Hui YANG Yan-Chen GAO Lang JIA Wen-Juan WANG Qing-Bai WU Francis ZVOMUYA Miles DYCK Hai-Long HE 

机构地区：[1]College of Natural Resources and Environment,Northwest A&F University,Yangling 712100,China [2]State Key Laboratory of Frozen Soil Engineering,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China [3]Department of Soil Science,University of Manitob1,Winnipeg MB R3T 2N2,Canada [4]Department of Renewable Resources,University of Albert1,Edmonton AB T6G 2H1,Canad

出　　处：《Advances in Climate Change Research》2024年第3期476-489,共14页气候变化研究进展（英文版）

基　　金：the Innovation Capability Support Program of Shaanxi Province(2023-JC-JQ-25);High-end Foreign Experts Recruitment Plan of China(G2021172006L and G2023172014L).

摘　　要：Freeze‒thaw induced landslides(FTILs)in grasslands on the Tibetan Plateau are a geological disaster leading to soil erosion.These landslides reduce biodiversity and intensify landscape fragmentation,which in turn are strengthen by the persistent climate change and increased anthropogenic activities.However,conventional techniques for mapping FTILs on a regional scale are impractical due to their labor-intensive,costly,and time-consuming nature.This study focuses on improving FTILs detection by implementing image fusion-based Google Earth Engine(GEE)and a random forest algorithm.Integration of multiple data sources,including texture features,index features,spectral features,slope,and vertical‒vertical polarization data,allow automatic detection of the spatial distribution characteristics of FTILs in Zhidoi county,which is located within the Qinghai‒Tibet Engineering Corridor(QTEC).We employed statistical techniques to elucidate the mechanisms influencing FTILs occurrence.The enhanced method identifies two schemes that achieve high accuracy using a smaller training sample(scheme A:94.1%;scheme D:94.5%)compared to other methods(scheme B:50.0%;scheme C:95.8%).This methodology is effective in generating accurate results using only~10%of the training sample size necessitated by other methods.The spatial distribution patterns of FTILs generated for 2021 are similar to those obtained using various other training sample sources,with a primary concentration observed along the central region traversed by the QTEC.The results highlight the slope as the most crucial feature in the fusion images,accounting for 93%of FTILs occurring on gentle slopes ranging from 0°to 14°.This study provides a theoretical framework and technological reference for the identification,monitoring,prevention and control of FTILs in grasslands.Such developments hold the potential to benefit the management of grassland ecosystem,reduce economic losses,and promote grassland sustainability.

关 键 词：Permafrost degradation Random forest Thaw slump Spatial distribution Tibetan Plateau 

分 类 号：P64[天文地球—地质矿产勘探]