NDVI variations of different terrestrial ecosystems and their response to major driving factors on two side regions of the Hu-Line

Abstract

Recent studies revealed that the greening in China has difficulty crossing the Hu-Line. However, the greening pattern and its driving factors remain unclear. Therefore, we explored NDVI spatio-temporal pattern and their key driving forces between southeastern and northwestern of the Hu-line from 2000 to 2020 using GDM (the geographical detector model) and trend analysis method. The following results were obtained: (1) Overall, NDVI showed a fluctuating upward trend in China over the study period, indicating greening. Although vegetation had improved significantly (48.11%) on the southeastern region of the Hu-line, it had significantly degraded (24.71%) on the northwestern region. The degradation of vegetation cover on unused and construction land was larger than the proportion of improvement. (2) GDM could identify the effect of single-factors on the NDVI variables on both side regions of the Hu-line. P (precipitation), POP (population density), and DEM (Digital Elevation), dominated NDVI’s spatial pattern in China. ET (evapotranspiration), ST (soil types) and POP had the strongest influence on the southeastern region, whereas P was the dominant factor on the northwestern region. In addition, POP, GDP (gross domestic product) and TEM (temperature) dominated the overall trend of NDVI. (3) Seven factors influenced and verged vegetation NDVI spatial distribution and change trends of vegetation were enhanced by their interaction. Overall, China is becoming greener. For various land-use types, natural factors (such as P and DEM) dominated vegetation NDVI pattern. Nevertheless, anthropogenic factors governed NDVI pattern of construction land. Anthropogenic factors mainly controlled NDVI tendency variations. The findings could effectively explain greening on both side regions of the Hu-line, and provide information for decision-making on vegetation restoration and ecological protection.

Keywords

• NDVI
• Hu-Line
• Geographical detector model
• Trend analysis
• Influencing factors