Vegetation changes and influencing factors in different watersheds of Henan Province based on GEE and geographic detectors.

Clarifying vegetation changes and the driving factors can provide references for ecological restoration and sustainable social development. We analyzed vegetation distribution and trend changes in Henan Province and its basin zoning (Haihe River basin zoning, Yellow River basin zoning, Huaihe River basin zoning, Yangtze River basin zoning), with fractional vegetation cover data from 2000 to 2020 based on the Google Earth Engine platform, and by combining Theil-Sen Median trend analysis, Mann-Kendall test, and Hurst index. We also utilized factor detection and factor interaction to explore the individual and mutual influences of natural and anthropogenic factors on vegetation at different scales. The results showed that the fractional vegetation cover (FVC) in Henan Province exhibited a distribution pattern of higher coverage in the south and lower in the north during the study period, predominantly characterized by moderate to high vegetation coverage. The Yangtze River basin zoning had the highest coverage. FVC in Henan Province and its zoning exhibited a consistent pattern of fluctuating upward trends, with all areas showing significant improvement. Particularly, the Yangtze River basin zoning had the largest area of improvement. According to the Hurst index, apart from the possibility of continued improvement in the Huaihe River basin zoning, other zoning would be likely to shift from improvement to degradation in the future. Vegetation changes in Henan Province and its zoning were the result of combined effects of anthropogenic and natural factors, with the influence of these factors changing over time and the dominant factors varying by region. Anthropogenic factors such as land use/cover type and nighttime lighting had a stronger impact on vegetation than natural factors like elevation, slope, and annual mean low temperature. The interaction between factors, particularly between anthropogenic and natural factors, exhibited a nonlinear enhancing pattern.