建水县位于长江上游，地处南盘江流域，具有重要的生态区位，对其进行典型岩溶石漠化地区碳储量估算及其影响因子分析，可为其碳储量提高和石漠化治理提供依据。以西南典型石漠化地区建水县为研究区，基于Landsat 5 Collection 1 Tier 1 Surface Reflectance、Landsat 8 Collection 1 Tier 1 Surface Reflectance、DEM （digital elevation model）等数据，利用GEE（google earth engine）平台和InVEST（integrated valuation of ecosystem services and trade-offs）模型估算、预测其碳储量，并利用地理探测器进行影响因子分析。结果表明：①2000—2020年建水县以潜在石漠化和无石漠化为主，已石漠化面积整体减少115 km²，无石漠化面积增加21 km²，石漠化状况整体得到改善。②建水县碳储量整体表现为“南北高、中部低”的空间分布特征；2000年、2010年和2020年碳储量分别为116.293、113.310、118.363 t，呈先减后增趋势；初步预测2030年碳储量增至129.981 t。③影响研究区碳储量变化的主要因子是气温，因子间的交互作用对碳储量变化的影响大于单一因子，坡度与气温交互作用最强，呈非线性增强。建水县碳储量呈先减后增趋势，受自然因素、社会因素影响，空间上呈“南北高、中部低”的分布特征。

In order to estimate carbon storage and investigate its influencing factors in typical karst rocky desertification regions, Jianshui County, located in the upper reaches of the Yangtze River and within the Nanpan River Basin, was selected for study due to its significant ecological position. Data from Landsat 5 Collection 1 Tier 1 Surface Reflectance, Landsat 8 Collection 1 Tier 1 Surface Reflectance, and digital elevation model (DEM) were used to conduct the analysis. The google earth engine (GEE) platform and the integrated valuation of ecosystem services and trade-offs (InVEST) model was used to estimate and predict carbon storage, while the geodetector tool was employed to analyze influencing factors. The results show that, between 2000 and 2020, Jianshui County was predominantly classified as potential rocky desertification and non-desertification, with the rocky desertification area found to have decreased by 115 km² overall, and the non-desertification area increased by 21 km², reflecting an improvement in desertification conditions. Carbon storage displayed a spatial distribution pattern of "higher in the north and south, lower in the center," with recorded values of 116.293 t, 113.310 t, and 118.363 t in 2000, 2010, and 2020, respectively, demonstrating an initial decrease followed by an increase. Projections suggest that carbon storage may reach 129.981 t by 2030. Temperature (q=0.672) was identified as the primary factor affecting changes in carbon storage, with the interactions between factors shown to have a stronger effect on carbon storage than individual factors, especially the interaction between slope and temperature (q = 0.998), indicating a non-linear enhancement. It is concluded that carbon storage in Jianshui County exhibits a trend of initial decrease followed by increase, influenced by both natural and social factors, with a spatial pattern of "higher in the north and south, lower in the center."