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Characterizing the responses of vegetation to climate change in the Tibet Plateau using remote sensing data
An, Chunchun1,2; Fan, Jianrong1; Zhang, Yanfen3; Yan, Dong4
2018
Source PublicationJOURNAL OF APPLIED REMOTE SENSING
ISSN1931-3195
Volume12Issue:1Pages:16035
SubtypeArticle
Contribution Rank1
AbstractIt is of great significance to investigate the changes in vegetation and its response to climate change in Tibet due to the sensitivity and vulnerability of the area to climate change. The spatiotemporal pattern of the normalized difference vegetation index (NDVI) and its trends between 2001 and 2015 were depicted using NDVI from the moderate resolution imaging spectroradiometer (MODIS). The responses of vegetation to climatic variables were analyzed through linear regression and correlation analysis with tropical rainfall measuring mission precipitation data and MODIS land surface temperature (LST) data. The results showed that (1) the average annual NDVI gradually decreased from the southeast to the northwest in accordance with the variations in LST and precipitation, (2) the annual NDVI increased from 2001 to 2015 at a rate of 0.3 x 10(-3) per year. The LST exhibited an average annual increase of 0.05 degrees C while precipitation remained relatively stable, (3) the correlation between NDVI and precipitation was positive in the central region, whereas it became negative in the southeast and northeast. The correlation between NDVI and LST was opposite of that between NDVI and precipitation, and (4) the increases in NDVI in the tropical monsoon rain forest and rain forest, subalpine coniferous forest, and alpine meadow vegetation types in the southeast depended more on LST than precipitation. In contrast, the increases in NDVI responded strongly to precipitation in the alpine bush and meadow, alpine grassland, alpine desert, and alpine desert steppe vegetation types in the northwest. (c) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Keywordclimate change normalized difference vegetation index tropical rainfall measuring mission precipitation land surface temperature Tibet
DOI10.1117/1.JRS.12.016035
Indexed BySCI
WOS KeywordLAKE OUTBURST FLOOD ; LAND-COVER CHANGE ; SPRING PHENOLOGY ; DRIVING FORCES ; CHANGE IMPACTS ; LOESS PLATEAU ; MODIS NDVI ; CHINA ; VARIABILITY ; DYNAMICS
Language英语
Quartile4区
Funding ProjectScience and Technology Service Network Initiative of the Chinese Academy of Science[KFJ-STS-ZDTP-015] ; National Natural Science Foundation of China[41661144028]
TOP
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000428022600001
Funding OrganizationScience and Technology Service Network Initiative of the Chinese Academy of Science ; National Natural Science Foundation of China
PublisherSPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/21476
Collection数字山地与遥感应用中心
Corresponding AuthorFan, Jianrong
Affiliation1.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu, Sichuan, Peoples R China;
2.Univ Chinese Acad Sci, Beijing, Peoples R China;
3.Sichuan Forestry Explorat & Design Inst, Chengdu, Sichuan, Peoples R China;
4.Univ Arizona, Sch Nat Resources & Environm, Tucson, AZ USA
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Corresponding Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
An, Chunchun,Fan, Jianrong,Zhang, Yanfen,et al. Characterizing the responses of vegetation to climate change in the Tibet Plateau using remote sensing data[J]. JOURNAL OF APPLIED REMOTE SENSING,2018,12(1):16035.
APA An, Chunchun,Fan, Jianrong,Zhang, Yanfen,&Yan, Dong.(2018).Characterizing the responses of vegetation to climate change in the Tibet Plateau using remote sensing data.JOURNAL OF APPLIED REMOTE SENSING,12(1),16035.
MLA An, Chunchun,et al."Characterizing the responses of vegetation to climate change in the Tibet Plateau using remote sensing data".JOURNAL OF APPLIED REMOTE SENSING 12.1(2018):16035.
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