Assessing vegetation dynamics and human impacts in natural and urban areas of China: Insights from remote sensing data

Abstract

Vegetation changes and human activities in both natural and urban environments have played a crucial role in carbon cycling and sustainable development globally. However, there is an insufficient comparison in national vegetation changes across regions with varying intensities of human activities to those natural areas. Based on urban boundary and night-time light datasets, we have identified and extracted rural, urban-low activity, and urban-high activity areas within China. Geodetector model was applied and conducted to assess the vegetation impacts of seven distinct natural and human factors on vegetation. Results show that overall vegetation change trend was characterized by Significant greening from 2000 to 2020. Areas with less than 1% Significant degradation are predominantly located in the southeastern China. Despite the dominance of forest growth, cropland in urban areas exhibits more stability under human control. Human involvement has significant restraint on vegetation growth from rural to urban, while there was little difference in vegetation growth between areas with strong human activity and areas with weak human activity. Moreover, human factors and land use/land cover have gradually become the dominant impact combinations in the eastern China over the past 20 years. The influence of temperature is increasing annually in southern China but decreasing in northern China. Meanwhile, factors related to water (e. g. precipitation and soil moisture) had more pronounced influences on western China. Our results provide a comprehensive insight in vegetation dynamic change in areas under different degrees of human activities, as well as the alterations in main driving factors on spatial heterogeneity of vegetation.

Keywords: China vegetation changes; Geodetecter; Google Earth Engine; Rural areas; Urban areas.