Characteristics and Driving Factors of NDVI in the Pingluo Section of the Yellow River Basin from 2000 to 2020

Abstract

Pingluo County is strategically positioned within prominent economic zones including the National Silk Road Economic Belt, the Hubaoyin Energy Golden Triangle, and the Yellow City Belt of Ningxia. Investigating the temporal and spatial evolution characteristics of the normalized vegetation index (NDVI) and its relationship with driving factors is crucial for maintaining the ecological stability of this region. Univariate linear regression was employed to analyze the spatiotemporal evolution characteristics of NDVI in Pingluo County from 2000 to 2020. This was combined with the geographic detector model to explore the driving forces behind spatial differentiation in vegetation, considering both natural and anthropogenic factors. The results indicate that: (1) the vegetation cover in flat land areas fluctuated and increased from 2000 to 2020, with an annual average NDVI of 0.22 and an annual growth rate of 0.002. The spatial distribution is characterized by high values in the east and west, sporadic high values in the center, and banded low values in the north and south. Areas with an NDVI above 0.7 comprise 20.99% of the study area. (2) The NDVI change rate in Pingluo County from 2000 to 2020 was relatively low, averaging 0.0034. Over this period, 90% of the areas experienced increased vegetation cover, while 10% remained stable. (3) The P-value significance test results indicate that only 10% of the study area exhibited degradation, suggesting an overall improvement trend in vegetation over the past 21 years. (4) Among the driving factors, natural influences play a predominant role. Land surface temperature and evapotranspiration are the primary natural factors affecting NDVI changes in Pingluo County, while night light represents the key anthropogenic factor. The interaction between physical and geographical factors on NDVI is predominantly characterized by non-linear enhancement (78.57%) and two-factor enhancement (21.43%).