【摘要】 [目的]如何利用长时序遥感数据信息对贵州省植被净初级生产力(Net Primary Productivity, NPP)的时空变化特征及影响因子进行定量分析，对喀斯特区域生态质量评估和监测具有典型意义，可为该区域的碳平衡和生态保护研究提供科学依据。[方法]综合利用Theil-Sen趋势分析法、Mann-Kendall检验法、相关性分析法和地理探测器等模型方法，基于2000—2020年MODIS NPP数据，以及DEM、气温、降水、人口密度等多源数据，定量计算和解析贵州省NPP的时空演变特征及其影响因子。[结果]贵州省NPP的空间分布呈现中南和西南部高、北部和东部低的空间异质性特征。近20年来，贵州省NPP总体呈波动上升趋势，增长区主要分布在西部和西南部，减少区主要分布在中部及东南部。气温和降水对NPP的影响最为显著，其与NPP的正相关水平分别达85.27%和63.35%,升温对NPP有促进作用，而降水过多则对NPP有阻碍作用。[结论]单因子分析表明降水对NPP影响最大，而任意两个因子交互的影响力计算显示，降水与气温是2000—2020年对贵州省NPP影响作用最大的交互因子。更多还原

【Abstract】 [Objective] How to quantitatively analyze the spatiotemporal variation characteristics and impact factors of net primary productivity(NPP) of vegetation in Guizhou Province using long-term remote sensing data is of typical significance in ecological quality assessment and monitoring in karst regions, and can provide scientific basis for research on carbon balance and ecological protection in this region. [Methods] Model methods such as Theil Sen trend analysis, Mann Kendall test, correlation analysis, and geographic detectors were utilized to quantitatively calculate and analyze the spatiotemporal evolution characteristics and impact factors of NPP in Guizhou Province based on MODIS NPP data from 2000 to 2020, as well as multi-source data such as DEM, temperature, precipitation, and population density. [Results] The spatial distribution of NPP in Guizhou Province showed a spatial heterogeneity characteristic of high level in the south central and southwest, and low level in the north and east. In the past 20 years, the overall NPP of Guizhou Province had shown a fluctuating upward trend, with growth areas mainly distributing in the west and southwest, decrease areas mainly distributing in the central and southeast. Temperature and precipitation had the most significant impact on NPP, with a positive correlation level of 85.27% and 63.35%, respectively. Warming up could promote NPP, while excessive precipitation could hinder NPP. [Conclusion] Single factor analysis showed that precipitation had the greatest impact on NPP, while the calculation of the interaction between any two factors showed that precipitation and temperature were the most influential interaction factors on NPP in Guizhou Province from 2000 to 2020.更多还原