Vegetation Growth Trends of Grasslands and Impact Factors in the Three Rivers Headwater Region

Xiaoping Sun and Yang Xiao ()
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Xiaoping Sun: Jiangsu Key Laboratory for Bioresources of Saline Soils, Jiangsu Synthetic Innovation Center for Coastal Bio-Agriculture, Jiangsu Provincial Key Laboratory of Coastal Wetland Bioresources and Environmental Protection, School of Wetland, Yancheng Teachers University, Yancheng 224001, China
Yang Xiao: China-Croatia “Belt and Road” Joint Laboratory on Biodiversity and Ecosystem Services, CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization & Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, China

Land, 2022, vol. 11, issue 12, 1-10

Abstract: Areas of grassland improvement and degradation were mapped and assessed to identify the driving forces of change in vegetation cover in the Three Rivers headwater region of Qinghai, China. Based on linear regression at the pixel level, we analyzed the vegetation dynamics of the grasslands of this region using MODIS NDVI data sets from 2000 to 2010. Correlation coefficients were computed to quantitatively characterize the long-term interrelationship between vegetation NDVI and precipitation/temperature variability during this period. The use of time series residuals of the NDVI/precipitation linear regression to normalize the effect of precipitation on vegetation productivity and to identify long-term degradation was extended to the local scale. Results showed that significant improvements occurred in 26.4% of the grassland area in the Three Rivers Headwater region between 2000 and 2010. The study area, which represents about 86.4% of the total grassland area of this headwater region, showed a general trend of improvement with no obvious trend of degradation.

Keywords: NDVI; grassland; MODIS; precipitation variability; human activities (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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