Spatial-Temporal Evolution Characteristics and Driving Force Analysis of NDVI in Hubei Province, China, from 2000 to 2022

Abstract

Exploring the characteristics of vegetation dynamics and quantitatively analyzing the potential drivers and the strength of their interactions are of great significance to regional ecological environmental protection and sustainable development. Therefore, based on the 2000–2022 MODIS NDVI dataset, supplemented by climatic, topographic, surface cover, and anthropogenic data for the same period, the Sen+Mann–Kendall trend analysis, coefficient of variation, and Hurst exponent were employed to examine the spatial and temporal characteristics and trends of NDVI in Hubei Province, and a partial correlation analysis and geographical detector were used to explore the strength of the influence of driving factors on the spatial differentiation of NDVI in vegetation and the underlying mechanisms of interaction. The results showed that (1) the mean NDVI value of vegetation in Hubei Province was 0.762 over 23 years, with an overall increasing trend and fluctuating upward at a rate of 0.01/10a (p < 0.005); geospatially, there is a pattern of “low east and high west”; the spatial change in NDVI shows a trend of “large-scale improvement in the surrounding hills and mountains and small-scale degradation in the middle plains”; it also presents the spatial fluctuation characteristics of “uniform distribution in general, an obvious difference between urban and rural areas, and a high fluctuation of rivers and reservoirs”, (2) the future trend of NDVI in 70.76% of the region in Hubei Province is likely to maintain the same trend as that of the 2000–2022 period, with 70.78% of the future development being benign and dominated by sustained improvement, and (3) a combination of partial correlation analysis and geographical detector analysis of the drivers of vegetation NDVI change shows that land cover type and soil type are the main drivers; the interactions affecting the distribution and change characteristics of NDVI vegetation all showed two-factor enhancement or nonlinear enhancement relationships. This study contributes to a better understanding of the change mechanisms in vegetation NDVI in Hubei Province, providing support for differentiated ecological protection and project implementation.