| Dengue fever is acute, hot property infectious disease, it is vector disease of distribution most widely, patient most, distributing primary in tropical and subtropical countries or regions, estimated at one hundred million cases to be infected annual in the world. Once being epidemiolocal, armed force will loss fight capability, Simultaneity, this virus can be large-scale cultured, its lyophilized powder can be preserved few years, it can be infected with aerosol and vector, so, it can be used in biological warfares and terror attacks. It mostly distributes in Guangdong, Fujian, Hainan and Taiwan at southeast along the coast. Meanwhile, because of global tendency and destroy of nature ecosystem, its prevention and control became more complicated. As vector aedes is affected by many environmental factors, its supervision and control is relatively difficulty, and new prevention means became quickly need. In order to find out the regularity of aedes vector dynamic change, we make use of spatialanalysis function of geographic information systems (GIS), extracting environmental agent information's function of satellite remote sensing and compressing index's function of principal component analysis's (PCA), explore affecting factor on dengue and aedes, and provide theory evidences to construction distribution model, prediction and prevention of aedes vector.We select Guangdong (Chaozhou) with high incidence of dengue disease as our study site, and have accidence exploration with fourth sects.Sect I : exploring relation between vector dynamic change and climate factors from epidemical analysis' view. The results indicate: Meteorology parameters correlating with aedes density are rainfall, sunlight, average air temperature, lowest average air temperature and relative humidity. Stepwise regression analysis leads to the regression equation,Viz.: YBI = 24.800 + 0.826X1 + 0.020X 2- 0.418 X 3 (X1 represents lowest average air temperature, X2 rainfall and X3, relative humidity).The logistic regression equation is Sect II : For further exploring character of vector spatial distribution in Guangdong, we established GIS of vector in Chaozhou and analyzed spatial autocorrelation, the results show that aedes distribution of supervision spots in Chaozhou wasn't stochastic rather than existing stated spatial cluster. All supervision spots have different densities with different distance, and the more thesupervision spots are close to water, the more the supervision spots are occupied and higher in density. Statistic analysis show that the density of the spots within 1000 meters to waterside is significantly higher than the spots which exceed 1000 meters to waterside (F=25.354, P<0.01). Exploratory spatial data analysis (ESDA) demonstrates aedes's spatial distribution has spatial autocorrelation. Its spatial distribution maps show that annual aedes epidemic situation change but basically maintain high, middle and low incidence three types distribution area, high density primary distributed in Xianqiao district, Guangtang tower and Tiepu tower of Chao'an county, and the low density area is north of Chaozhou. Kriging finally bring four cross-validation indices, they are MPE (mean prediction error) which reflecting predictive bias, RMSE (root-mean- square error) which estimating variance, ASE (average standard error) which reflecting consistency between predicate value and true value, and RMSSE (root-mean- square standard error) which being predictive error variation degree. Four indices of this study were ideal.Sect III : We use function of ERDAS8.5 which distill environmental factors from remote sensing image, and explore the relation between vector density and normalized difference vegetation index (NDVI).The result lead that vegetation covered all over Guangdong all through year, the mean NDVI of epidemical season and non- epidemical season were 142.95, 126.19, respectively. And epidemical area and non-epidemical area were 140.98, 140.98,respe...
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