A dataset of spatial distribution of NDVI and the influencing factors in Xinjiang (2000–2021)

<p indent="0mm">Vegetation cover change has a profound impact on the ecological environment. While current studies mostly focus on the response analysis of NDVI and climate, often overlooking non-linear factors such as topography and soil characteristics, which also play important roles in the dynamics. Therefore, high-quality datasets of vegetation cover changes and influencing factors are of great significance in terrestrial ecosystem research. Based on the GEE platform, we acquired MODIS remote sensing data and ERA5-Land Monthly Averaged dataset, and used the ArcGIS software to process TIF data into numerical data, followed by further processing (data cleaning, normalization, etc. ) using the Python toolkit. Finally, we produced a dataset of spatial distribution pattern of NDVI and influencing Factors in Xinjiang from 2000 to 2021 comprising 14 fields and 2,756 entries. The Kriging interpolation method was used to interpolate the acquired data, and 13 spatial interpolation maps of influence factors were obtained. This dataset can be used to model the relationship between vegetation cover changes and their influencing factors in Xinjiang. It can provide basic data for different influencing factors affecting NDVI changes, and further support regional scientific research for agricultural technology, environmental development and management, etc.