###### Abstract
Combining the high spatial resolution of Landsat data with the high temporal resolution of MODIS data better captures vegetation dynamics in complex mountainous terrain. This fusion allows us to overcome the limitations of using either dataset alone and provides a more accurate assessment of GPP variations. Thus, multi-source data fusion was central to this study. Northwestern Hubei is one of the most important ecological zones in central China, with a high forest coverage rate and complex environments. The topography is particularly complex in the region, with the elevation ranging from 42 m to 3103 m. The core area, Shennongjia Forestry District, shows an elevation difference over 2700 m, only covering a 3253 km\({}^{2}\) region. This unique topographic setting supports 3767 vascular plant species, and features 11 vegetation types across a complete altitudinal spectrum from low to high elevations. The rich biodiversity makes it critically important to research the changes in vegetation in this region, which also supports its recognition as the first site in China to be simultaneously recognized under three major global conservation designations. Shennongjia is also the only administrative region in China named after a forest area, as a key national nature reserve featuring well-preserved primeval forests and key ecological functional zones. Northwestern Hubei is a transitional zone from subtropical to temperate climate; however, due to the great elevation differences, the precipitation and temperature also show obvious spatial heterogeneity, with the regions at higher altitudes showing lower temperatures and receiving more precipitation, which favors forest growth. In this condition, the distribution of vegetation is also shaped by the vertical zonation and climatic gradients, making its distribution exhibit strong spatial heterogeneity [30; 31; 32; 33; 34]. As a result, it is of great significance to study the variations and responses of vegetation photosynthesis in northwestern Hubei with complex mountainous topography. Although many previous studies have reached many conclusions on vegetation diversity and distribution in Shennongjia due to its high biodiversity, the distribution and variations in vegetation photosynthetic carbon sequestration still remain poorly understood and deserve further investigation [35; 36; 37]. Thus, in this study, we targeted northwestern Hubei, using high-resolution remote sensing imagery from multiple sources, regional meteorological data, and land cover data, employing an LUE model to estimate regional GPP. We further integrated a digital elevation model (DEM) and meteorological data to systematically analyze the spatiotemporal trends and driving factors of GPP, aiming to reveal the dynamic characteristics and driving mechanisms of vegetation carbon sequestration, thereby enriching the theoretical research on this topic in the region. The spatiotemporal trends and driving factors of GPP were also systematically analyzed across different time scales and elevations. In addition, GPP was estimated using the CASA model, and cross-validation was performed with MODIS GPP and GOSIF GPP products to evaluate the reliability and consistency of the results.