Vegetation greenness dynamics and responses to climate and human activities under land cover change in Guangdong, China

To understand the spatiotemporal variations of vegetation greenness and the differences in its response to climate and human activities based on land cover change in subtropical region, this paper focused on the spatiotemporal characteristics of vegetation greenness (indicated by NDVI) and its sensitivity to temperature, precipitation and human activities (indicated by nighttime light (NTL)) under different land cover scenarios in Guangdong, China. The contributions of climate and human activities under land cover change to the variations in vegetation greenness were quantified using Lindeman, Merenda and Gold method (LMG). The conclusions revealed that (1) NDVI was significantly higher in regions with land cover change. This might be because the conversion from grassland to evergreen forest increased vegetation density. (2) NDVI in regions with unchanged land cover exhibited higher correlations with temperature and NTL. At the grid scale, NDVI was more sensitive to temperature rather than precipitation and was significantly correlated with NTL in most regions. (3) At the province scale, LMG multivariate regression model indicated that land cover change was the dominant factor affecting vegetation greenness with a contribution of 54.2%, while the contribution of climate factors was relatively low with temperature contributing 18.2% which was greater than the contribution of precipitation (2.2%). This paper contributes to a deeper understanding of the mechanisms underlying vegetation responses to the combined effects of climate change and human activities, providing a scientific basis for regional ecological quality assessment and ecosystem management.