The spatiotemporal response of China's vegetation greenness to human socio-economic activities

Abstract

Climate change and human socioeconomic activities both strongly impact long-term vegetation greenness. It is more a challenge to evaluate the impacts of socioeconomic activities on vegetative greenness than climate change, partially due to the lack of appropriate quantitative indicators of the former. Here we examined the relationship between the remote sensing nighttime light (NTL) data and the Normalized Difference Vegetation Index (NDVI), which in this study are used as the proxies of socioeconomic activities and vegetation greenness, respectively. We first eliminated the vegetation greenness changes in response to climate change and calculated the human-activities-induced NDVI (HNDVI). After explored the spatiotemporal patterns of the HNDVI and NTL data across China from 1998 to 2018, we studied the relationship between the HNDVI and NTL at the grid and county levels, respectively. Our results show that the mean adjusted DN values of the NTL data (NTLI) continuously increase (+0.2938) across our study area from 1998 to 2018, whereas the HNDVI values fluctuate with a general upward trend (+0.0018). Most grids (91.2%) with increased HNDVI were found in rural areas, particularly in the Northeast forest shelterbelt and the Loess Plateau. By contrast, the HNDVI values in rapidly urbanized areas in Chinese major urban agglomerations mainly show a downward trend, especially in the Yangtze River Delta (YRD) urban agglomeration. The relationships between the NTLI and HNDVI are inconsistent over time and across space, which could be attributed to land use conditions, afforestation projects in rural areas, and greening activities in urban areas over different periods and regions.