中国科学:地球科学英文版 · 2021年第1期62-79,共18页

Mapping the permafrost stability on the Tibetan Plateau for 2005–2015

作者:Youhua RAN,Xin LI,Guodong CHENG,Zhuotong NAN,Jinxing CHE,Yu SHENG,Qingbai WU,Huijun JIN,Dongliang LUO,Zhiguang TANG,Xiaobo WU

摘要:Data scarcity is a major obstacle for high-resolution mapping of permafrost on the Tibetan Plateau(TP).This study produces a new permafrost stability distribution map for the 2010 s(2005–2015)derived from the predicted mean annual ground temperature(MAGT)at a depth of zero annual amplitude(10–25 m)by integrating remotely sensed freezing degree-days and thawing degree-days,snow cover days,leaf area index,soil bulk density,high-accuracy soil moisture data,and in situ MAGT measurements from 237 boreholes on the TP by using an ensemble learning method that employs a support vector regression model based on distance-blocked resampled training data with 200 repetitions.Validation of the new permafrost map indicates that it is probably the most accurate of all currently available maps.This map shows that the total area of permafrost on the TP,excluding glaciers and lakes,is approximately 115.02(105.47–129.59)×10^4 km^2.The areas corresponding to the very stable,stable,semi-stable,transitional,and unstable types are 0.86×10^4,9.62×10^4,38.45×10^4,42.29×10^4,and 23.80×10^4 km^2,respectively.This new map is of fundamental importance for engineering planning and design,ecosystem management,and evaluation of the permafrost change in the future on the TP as a baseline.

发文机构:Northwest Institute of Eco-Environment and Resources Institute of Tibetan Plateau Research CAS Center for Excellence in Tibetan Plateau Earth Sciences University of Chinese Academy of Sciences Institute of Urban Study Key Laboratory of Virtual Geographic Environment Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application School of Science National-Local Joint Engineering Laboratory of Geo-Spatial Information Technology

关键词:MountainpermafrostThirdPoleRemotesensingStatisticallearning

分类号: P64[天文地球—地质矿产勘探]

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