Analysis of Spatiotemporal Changes in NDVI-Derived Vegetation Index and Its Influencing Factors in Kunming City (2000 to 2020)

Vegetation is a fundamental component of ecosystems and plays a vital role in maintaining ecological processes. It contributes to soil conservation, climate regulation, and landscape quality. Kunming, widely known as the “Spring City,” relies heavily on vegetation to sustain its ecological and social environment. This study employs moderate resolution imaging spectroradiometer (MODIS) and Normalized Difference Vegetation Index (NDVI) data in combination with temperature, precipitation, population, and gross domestic product (GDP) records to analyze the spatiotemporal dynamics and driving factors of NDVI-derived vegetation index in Kunming from 2000 to 2020 using trend and correlation analyses. We derived fractional vegetation coverage (FVC) from MODIS NDVI using the pixel dichotomy model, analyzed its temporal trends with linear regression, and applied pixel-wise Pearson correlation analysis to identify the spatial relationship between FVC and precipitation. The main findings can be summarized as follows: (1) The NDVI-derived vegetation index pattern in Kunming is generally higher in the west than in the east and higher in mountainous areas than in plains and basins. From 2000 to 2020, overall NDVI-derived vegetation index increased, with the mean NDVI rising from 0.48 to 0.545. Notably, the NDVI values in 2010 and 2012 declined sharply, likely due to drought conditions caused by reduced rainfall in the preceding years. (2) During the study period, 26.86% of the area showed moderate (NDVI slope: 0.005–0.016) improvement and 10.35% showed significant (NDVI slope: 0.016–0.063) improvement, while 10.28% exhibited degradation. Spatially, improvements were concentrated in Xundian County, parts of Dongchuan District, northern Luquan County, and northern border areas adjoining Yiliang and Shilin Counties. Areas with clear degradation were primarily located in Kunming’s main urban area and along the corridor from the airport to Songming. (3) Correlation analysis revealed that 53.3% of areas exhibited a positive relationship between temperature and NDVI-derived vegetation index, while 18.6% showed a significant negative correlation, mainly in the lower Pudu River basin, the Fumin–Luquan border, and the basin areas of Songming and Shilin Counties. This negative relationship may be attributed to increased evapotranspiration under higher temperatures, which exacerbates soil moisture loss and imposes drought stress on vegetation, thereby inhibiting plant growth. Similarly, 53% of areas showed a positive correlation between precipitation and FVC, whereas only 8.3% showed a significant negative correlation, underscoring the strong influence of precipitation on vegetation dynamics in Kunming. (4) Over the past two decades, Kunming’s GDP increased tenfold. In comparison with NDVI-derived vegetation index data for the same period, this indicates that areas of higher GDP are often associated with lower NDVI-derived vegetation index.