Abstract
郭家钢,林丹丹,胡广汉,宁安,刘红云,吕尚标,李东,吴晓华,王蓉蓉,陈名刚,郑江,MarcelTanner.应用遥感技术快速确定鄱阳湖区钉螺孳生地的研究[J].Chinese journal of Epidemiology,2002,23(2):99-101
应用遥感技术快速确定鄱阳湖区钉螺孳生地的研究
Rapid identification of Oncomelania hupensis snail habitat in the Poyang Lake region by Geographic Information System (GIS) and Remote Sensing (RS)
Received:November 24, 2001  Revised:June 05, 2012
DOI:
KeyWord: 遥感技术  钉螺分布  血吸虫病
English Key Word: Remote sensing  Oncomelania hupensis snail distribution  Schistosomiasis
FundProject:世界卫生组织热带病研究规划署资助项目(ID990378)
Author NameAffiliation
GUO Jiagang Institute of Parasitic Diseases, Control and Prevention,Chinese Center Disease Control and Prevention,Shanghai 200025, China 
LIN Dandan 江西省寄生虫病研究所 
HU Guanghan 江西省寄生虫病研究所 
NING An 江西省寄生虫病研究所 
LIU Hongyun 江西省寄生虫病研究所 
LU Shangbiao 江西省寄生虫病研究所 
LI Dong 江西省寄生虫病研究所 
WU Xiaohua Institute of Parasitic Diseases, Control and Prevention,Chinese Center Disease Control and Prevention,Shanghai 200025, China 
WANG Rongrong Institute of Parasitic Diseases, Control and Prevention,Chinese Center Disease Control and Prevention,Shanghai 200025, China 
CHEN Minggang Institute of Parasitic Diseases, Control and Prevention,Chinese Center Disease Control and Prevention,Shanghai 200025, China 
ZHENG Jiang Institute of Parasitic Diseases, Control and Prevention,Chinese Center Disease Control and Prevention,Shanghai 200025, China 
Marcel TANNER Swiss Tropical Institute 
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Abstract:
      目的 应用地理信息系统和遥感技术 (GIS,RS)快速确定鄱阳湖区钉螺孳生地带及血吸虫病高危区域。方法 在鄱阳湖区内选择三个血吸虫病重度流行村周围的洲滩,用传统方法进行螺情调查,卫星定位仪 (GPS)记录有钉螺点的经纬度。运用ERDASIMAGINE软件对鄱阳湖区枯水期的卫星专题制图仪 (TM)遥感片进行计算机非监督分类,校正植被指数 (NDVI)和穗帽湿度变换指数 (TC)模型计算,并对有螺点相对应TM数据进行综合分析。结果 鄱阳湖区钉螺分布和孳生与洲滩湖草的生长状况及湿度有密切的关系,根据现场调查的钉螺分布图,有螺点主要分布在计算机非监督分类的 6、7和 8类中,进一步模型分析表明 :有螺点主要分布在NDVI >110和TC在 - 10~ 3之间,其准确率达 95 %以上。结论 本项研究提示 :运用计算机非监督分类法可大致确定 6、7和 8类为有螺植被环境,然后通过NDVI >110确定植被优质区为钉螺的孳生环境,最后通过TC =- 10~ 3可确定钉螺最佳孳生地。
English Abstract:
      Objective To identify Oncomelania hupensis snail habitats and areas with high transmission potential by GIS/RS. Methods Marshland areas near high endemic villages of schistosomiasis in the Poyang Lake region were selected. Corresponding map was digitized and (Landsat 5 TM) image was corrected according to the digital map. The image in dry seasons was calculated by both normalized difference vegetation index (NDVI) and tasseled cap model. Results Result showed that snails spots were distributed in class 6,7 and 8. Farther analysis of both NDVI and tasseled cap model showed that the snail habitats were mainly distributed in the areas where NDVI value was more than 110, and in tasseled cap wetness value between -10 to 3 with correction rate 94.93 %. Conclusion First step was to use unsupervised classification to define the class 6,7and 8 snail habitat environment. Second step was to extract the value by NDVI model, and to define a healthy vegetation as snail suspicious habitat when NDVI value was more than 110. Then the third step was to use tasseled cap wetness model to define the areas as snail habitats which value was between -10 to 3.
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