To assess the carbon balance of terrestrial ecosystems, it is crucial to consider the net primary productivity (NPP) of vegetation. Understanding the response of NPP in Xinjiang’s vegetation to climate factors and human activities is essential for ecosystem management, the Belt and Road Initiative, and achieving carbon neutrality goals. Based on the CASA model, this study uses meteorological data, DEM data, and land cover data, employing trend analysis and partial derivative analysis methods to investigate the temporal trends and spatial distribution of NPP in Xinjiang from 2000 to 2020. Additionally, it quantifies the contributions of climate factors and human activities to NPP fluctuations. The key findings are: (1) The average annual NPP is 101.52 gC/m², with an upward trend, showing an overall growth rate of 0.447 gC/m²/yr. Spatially, NPP is higher in northern Xinjiang than in the south, and in mountainous areas compared to basins. (2) Over 21 years, climate factors contributed an average of 1.054 gC/m²/yr, while human activities contributed 0.239 gC/m²/yr to NPP changes. Among climate factors, temperature, precipitation, and sunshine duration contributed 0.003, 0.169, and 0.588 gC/m²/yr, respectively, all showing positive effects on NPP. (3) Forests have the highest average NPP at 443.96 gC/m², with an annual growth rate of 2.69 gC/m²/yr. When forest is converted to cropland, the net loss in NPP is −1.94 gC/m², and the loss is even greater in conversion to grassland, reaching −17.33 gC/m². (4) The changes in NPP are driven by both climate factors and human activities. NPP increased in 77.25% of the area, while it decreased in 22.69%. Climate factors have a greater positive impact than human activities.

Glaciers, often regarded as “frozen reservoirs”, play a crucial role in replenishing numerous rivers in arid regions, contributing to ecological balance and managing river flow. Recently, the rapid shrinkage of the glaciers in the East Tianshan Mountains has affected the water quantity in the Karez system. However, studies on glacier changes in this region are limited, and recent data are scarce. This study utilizes annual Landsat composite images from 1990 to 2022 obtained via the Google Earth Engine (GEE). It utilizes a ratio threshold approach in conjunction with visual analysis to gather the glacier dataset specific to the Turpan–Hami region. The Open Global Glacier Model (OGGM) is used to model the flowlines and mass balance of around 300 glaciers. The study analyzes the glacier change trends, distribution characteristics, and responses to climate factors in the Turpan–Hami region over the past 30 years. Additionally, future glacier changes through the end of the century are projected using CMIP6 climate data. The findings indicate that the following: (1) From 1990 to 2022, glaciers in the research area underwent considerable retreat. The total glacier area decreased from 204.04 ± 0.887 km² to 133.52 ± 0.742 km², a reduction of 70.52 km², representing a retreat rate of 34.56%. The number of glaciers also decreased from 304 in 1990 to 236 in 2022. The glacier length decreased by an average of 7.54 m·a⁻¹, with the average mass balance at −0.34 m w.e.·a⁻¹, indicating a long-term loss of glacier mass. (2) Future projections to 2100 indicate that under three climate scenarios, the area covered by glaciers could diminish by 89%, or 99%, or even vanish entirely. In the SSP585 scenario, glaciers are projected to nearly disappear by 2057. (3) Rising temperatures and solar radiation are the primary factors driving glacier retreat in the Turpan–Hami area. Especially under high emission scenarios, climate warming will accelerate the glacier retreat process.