目的　通过 SRS、GIS、PCA三者在实际中的应用 ,找出登革热 (DF)及媒介空间分布的主要影响因素。方法　利用 ERDAS8.5软件从 AVHRR卫星图像中提取各监测点 NDVI、利用 Krig-ing在 Arc GIS8.1上作 DF发病和媒介的空间分布图和利用主成分分析法找出影响其分布的主要成分。结果　从 NOAA- AVHRR卫星图片提取全省 1995年度平均 NDVI为 135 ,DF流行区域的珠江流域和韩江流域的 NDVI要高于广东省其它地方 ,流行季节的 NDVI要高于非流行季节 ,且差异都有统计学意义。 GIS对 DF分析表明 ,广东省的两个高发区域是珠江三角洲和韩江三角洲 ,DF发病和伊蚊密度的 MPE、RMSE、ASE、RMSSE分别为 0 .0 18、0 .377、0 .372、0 .981和 0 .0 17、0 .32 8、0 .338、1.0 2 6。主成分分析显示四个主要成分综合了原 17个指标的 91.5 2 4 %。结论　三者的联合应用可以从不同的角度上克服和弥补在 DF防治上的不足 Objective To find out the main influencing factors of dengue fever (DF) and its spatial distribution through the application of SRS, GIS and PCA in practice. Methods The NDVI was extracted from AVHRR satellite images by using ERDAS 8.5 software. Kriging was used to map the incidence and distribution of DF in Arc GIS8.1 and the principal component analysis (PCA) was used to find out the main components influencing its distribution . Results The NDVI of the whole province in 1995 was extracted from the NOAA-AVHRR satellite imagery. The NDVI of the Pearl River and Hanjiang River basins in DF endemic areas was higher than that of other parts of Guangdong Province. The NDVI of epidemic season was higher than that of non-epidemic season, All have statistical significance. GIS analysis of DF showed that the two high incidence areas in Guangdong Province were the Pearl River Delta and the Hanjiang Delta. The MPE, RMSE, ASE and RMSSE of DF incidence and Aedes mosquitoes were 0.018,0.377 and 0.372, respectively, 0 .981 and 0 .0 17,0 .32 8,0 .338,1.0 2 6. The principal component analysis showed that the four major components integrated 91.5% of the original 17 indicators. Conclusions The joint application of the three can overcome and compensate deficiencies in DF control from different perspectives