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Model Simulation and Prediction of Decadal Mountain Permafrost Distribution Based on Remote Sensing Data in the Qilian Mountains from the 1990s to the 2040s
Zhao, Shangmin1; Zhang, Shifang1; Cheng, Weiming2,3,4; Zhou, Chenghu2,3,4
2019-01-02
Source PublicationREMOTE SENSING
ISSN2072-4292
Volume11Issue:2Pages:19
Corresponding AuthorZhao, Shangmin(zhaoshangmin@tyut.edu.cn)
AbstractBased on the results of remote sensing data interpretation, this paper aims to simulate and predict the mountain permafrost distribution changes affected by the mean decadal air temperature (MDAT), from the 1990s to the 2040s, in the Qilian Mountains. A bench-mark map is visually interpreted to acquire a mountain permafrost distribution from the 1990s, based on remote sensing images. Through comparison and estimation, a logistical regression model (LRM) is constructed using the bench-mark map, topographic and land coverage factors and MDAT data from the 1990s. MDAT data from the 2010s to the 2040s are predicted according to survey data from meteorological stations. Using the LRM, MDAT data and the factors, the probabilities (p) of decadal mountain permafrost distribution from the 1990s to the 2040s are simulated and predicted. According to the p value, the permafrost distribution statuses are classified as 'permafrost probable' (p > 0.7), 'permafrost possible' (0.7 >= p >= 0.3) and 'permafrost improbable' (p < 0.3). From the 1990s to the 2040s, the 'permafrost probable' type mainly degrades to that of 'permafrost possible', with the total area degenerating from 73.5 x 10(3) km(2) to 66.5 x 10(3) km(2). The 'permafrost possible' type mainly degrades to that of 'permafrost impossible', with a degradation area of 6.5 x 103 km(2), which accounts for 21.3% of the total area. Meanwhile, the accuracy of the simulation results can reach about 90%, which was determined by the validation of the simulation results for the 1990s, 2000s and 2010s based on remote sensing data interpretation results. This research provides a way of understanding the mountain permafrost distribution changes affected by the rising air temperature rising over a long time, and can be used in studies of other mountains with similar topographic and climatic conditions.
Keywordmountain permafrost logistic regression model model simulation and prediction mean decadal air temperature data Qilian Mountains
DOI10.3390/rs11020183
WOS KeywordQINGHAI-TIBET PLATEAU ; PARAMETERS ; REGIONS ; CHINA
Indexed BySCI
Language英语
Funding ProjectNational Key Research and Development Program[2017YFB0503603] ; National Natural Science Foundation of China[41631179] ; National Natural Science Foundation of China[41571388] ; National Natural Science Foundation of China[41771443] ; National Natural Science Foundation of China[41421001] ; National Natural Science Foundation of China[41590845] ; Major State Basic Research Development Program of China[2015CB954101]
Funding OrganizationNational Key Research and Development Program ; National Natural Science Foundation of China ; Major State Basic Research Development Program of China
WOS Research AreaRemote Sensing
WOS SubjectRemote Sensing
WOS IDWOS:000457939400078
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/49852
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhao, Shangmin
Affiliation1.Taiyuan Univ Technol, Coll Min Engn, Dept Surveying & Mapping, Taiyuan 030024, Shanxi, Peoples R China
2.Chinese Acad Sci, Inst Geog & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Shangmin,Zhang, Shifang,Cheng, Weiming,et al. Model Simulation and Prediction of Decadal Mountain Permafrost Distribution Based on Remote Sensing Data in the Qilian Mountains from the 1990s to the 2040s[J]. REMOTE SENSING,2019,11(2):19.
APA Zhao, Shangmin,Zhang, Shifang,Cheng, Weiming,&Zhou, Chenghu.(2019).Model Simulation and Prediction of Decadal Mountain Permafrost Distribution Based on Remote Sensing Data in the Qilian Mountains from the 1990s to the 2040s.REMOTE SENSING,11(2),19.
MLA Zhao, Shangmin,et al."Model Simulation and Prediction of Decadal Mountain Permafrost Distribution Based on Remote Sensing Data in the Qilian Mountains from the 1990s to the 2040s".REMOTE SENSING 11.2(2019):19.
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