Evidence map›Paper›PMID 35886687›Full record

ArticleInternational journal of environmental research and public health2022

Study on Spatiotemporal Variation Pattern of Vegetation Coverage on Qinghai-Tibet Plateau and the Analysis of Its Climate Driving Factors.

Xiaoyu Deng, Liangxu Wu, Chengjin He, Huaiyong Shao

Abstract read
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Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Xiaoyu DengCollege of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China.
Liangxu WuCollege of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China.
Chengjin HeCollege of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China.
Huaiyong ShaoCollege of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As one of the most sensitive areas to global environmental change, especially global climate change, the Qinghai-Tibet Plateau is an ideal area for studying global climate change and ecosystems. There are few studies on the analysis of the vegetation's driving factors on the Qinghai-Tibet Plateau based on large-scale and high-resolution data due to the incompetence of satellite sensors. In order to study the long-term vegetation spatiotemporal pattern and its driving factors, this study used the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) to improve the spatial resolution of the GIMMS NDVI3g (8 km) data of the Qinghai-Tibet Plateau in 1990 and 1995 based on the MODIS NDVI (500 m) data. The research on the spatiotemporal pattern and driving factors of vegetation on the Qinghai-Tibet Plateau from 1990 to 2015 was carried out afterward, with combined data including topographic factors, annual average temperature, and annual precipitation. The results showed that there was a strong correlation between the actual MODIS NDVI image and the fused GIMMS NDVI3g image, which means that the accuracy of the fused GIMMS NDVI3g image is reliable and can provide basic data for the accurate evaluation of the spatial and temporal patterns of vegetation on the Qinghai-Tibet Plateau. From 1990 to 2015, the overall vegetation coverage of the Qinghai-Tibet Plateau showed a degrading trend at a rate of -0.41%, and the degradation trend of vegetation coverage was the weakest when the slope was ≥25°. Due to the influence of the policy of returning farmland to forests, the overall degradation trend has gradually weakened. The significant changes in vegetation in 2010 can be attributed to the difference in the spatial distribution of climatic factors such as temperature and precipitation. The area with reduced vegetation in the west was larger than the area with increased vegetation in the east. The effects of temperature and precipitation on the distribution, direction, and degradation level of vegetation coverage were varied by the areal differentiation in different zones.

Indexed as

Climate ChangeEcosystemChinaForestsTemperatureTibetclimate changedata fusionESTARFMtopographyvegetation coverage

Identifiers

PMID35886687
PMCPMC9324348

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.