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Chinese Journal of Applied Ecology ›› 2023, Vol. 34 ›› Issue (11): 2919-2928.doi: 10.13287/j.1001-9332.202311.023

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Spatiotemporal variation and driving factor of vegetation coverage from 2000 to 2020 in southern Jiangxi Province, China.

LIU Dongdong, PAN Ping, FU Jia, OUYANG Xunzhi*   

  1. Key Laboratory of National Forestry and Grassland Administration for the Protection and Restoration of Forest Ecosystem in Poyang Lake Basin, College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China
  • Received:2023-06-21 Revised:2023-09-18 Online:2023-11-15 Published:2024-05-15

Abstract: Vegetation plays a critical role in the water and carbon cycling and energy flow, serving as an indicator for regulating land carbon balance and reflecting climate change and human activities. We analyzed the spatiotemporal variations of normalized difference vegetation index (NDVI) during the growing season in southern Jiangxi from 2000 to 2020, using statistical methods, including the Mann-Kendall test, Theil-Sen Median analysis, Hurst index, and coefficient of variation. We employed the geodetector model to comprehensively assess the impacts of climate, topography, soil and human factors on spatial differentiation of vegetation NDVI. The results showed NDVI exhibited an upward fluctuating trend with a rate of 0.003 per year from 2000 to 2020. The proportion of high-grade and medium-high-grade NDVI areas were 55.8% and 41.9%, respectively, while the areas with low and relatively low fluctuations accounted for 92.3%. The proportions of areas showing extremely significant improvement and significant improvement were 40.4% and 19.4%, respectively. In contrast, the combined proportion of areas displaying extremely significant degradation and significant degradation was only 2.2%. The proportions of areas demonstrating continuous improvement and future improvement were 28.0% and 60.2%, respectively. Elevation, precipitation, relative humidity, temperature, landform type, land use type, population density, and nighttime light were identified as the major factors for the vairations of NDVI in the study area, followed by slope, soil type, and GDP, while slope aspect and vegetation type had indirect influence. Throughout the study period, NDVI in southern Jiangxi was overall stable, with future changes primarily indicating improvement. Notably, human factors such as land use type, population density, and nighttime light index exhibited an upward trend in their impacts on NDVI.

Key words: normalized difference vegetation index, geographic detector, natural factor, human factor, southern Jiangxi Province