Exploring the spatial and temporal changes in vegetation net primary productivity (NPP) and analyzing its complex relationship with influencing factors is crucial for assessing the carbon absorption capability of vegetation. However, most of the existing studies have been conducted from a temporal or spatial perspective, resulting in an unclear characterization of the spatio-temporal divergence between NPP and the main influencing factors. This paper tries to break through the lack of research on the spatiotemporal heterogeneity of the relationship between NPP and influencing factors and proposes a joint spatiotemporal analysis method that integrates natural and anthropogenic factors, uses correlation analysis to determine their relationship with NPP, then combines GeoDetector (GD) and Geographically Weighted Regression (GWR), and carries out an empirical study based on the data of 2001-2017, taking Yunnan Province as an example, to reveal the characteristics of influencing factors’ divergence in different time and space. The results indicate that: (1) NPP in Yunnan Province experienced fluctuations and increases from 2001 to 2017. (2) NDVI, precipitation, and temperature exert a substantial influence on the spatial and temporal variation of NPP, although this impact is diminishing. (3) Solar radiation, topography, and land use are secondary factors that affect the spatial and temporal differentiation of NPP, but their influence is increasing. (4) From 2001 to 2010, land use transfer was the main cause of NPP loss, but from 2010 to 2017, land use transfer was the main cause of NPP gain. The collective effect of anthropogenic activities and natural factors is considerably more substantial than the influence of any individual factor. This study aims to improve our understanding of how the NPP responds to climate change and urbanization. Additionally, it seeks to clarify spatial and temporal variations in NPP and identify its primary drivers. Furthermore, it can serve as a useful scientific foundation and point of reference for improving the performance of ecosystem carbon sinks and achieving carbon neutrality.