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鄱阳湖区应用卫星遥感资料预测1998年洪水后钉螺分布状况
引用本文:林丹丹,周晓农,刘跃民,孙乐平,胡飞,杨国静,洪青标.鄱阳湖区应用卫星遥感资料预测1998年洪水后钉螺分布状况[J].中国血吸虫病防治杂志,2002,14(2):119-121.
作者姓名:林丹丹  周晓农  刘跃民  孙乐平  胡飞  杨国静  洪青标
作者单位:1. 江西省寄生虫病研究所,南昌330046
2. 江苏省血吸虫病防治研究所
摘    要:目的 了解1998年洪水后对鄱阳湖区洲滩钉螺分布的影响及其现状。方法 收集陆地卫星TM遥感资料和1999-2000年间鄱阳湖区洲滩钉螺孳生分布情况,遥感资料在ERDAS imaging 8.3软件上分析,建模分析并分别提取出植被指数和水域分布区域,并进行校正叠加,提取出钉螺的可疑孳生地。随机抽取卫星遥感资料分析所示的钉螺可疑孳生环境,分别与地面调查结果进行核对验证。结果 遥感资料分析结果预测钉螺可疑孳生地范围与近两年春季查出的有螺面积和分布范围基本相符,总符合率为76.92%(30/39),其中大型环境的符合率92.31%(12/13),中型环境符合率85.71%(12/14),小型环境符合率50.00%(6/12);但遥感资料分析结果也显示堤内有钉螺可疑孳生地。结论 应用地理信息系统和遥感技术预测钉螺孳生地对及时掌握血吸虫病流行范围和易感地带有重要意义。

关 键 词:卫星遥感  预测  洪水  钉螺  孳生地  鄱阳湖区
文章编号:1005-6661(2002)02-0119-03
修稿时间:2001年7月8日

PREDICTION OF SNAIL HABITATS IN THE MARSHLAND AROUND POYANG LAKE AFFECTED BY FLOOD IN 1998 USING REMOTE SENSING
Lin Dandan ,Zhou Xiaonong ,Liu Yueming ,Shun Leping ,Hu Fei ,Yang Guojing ,Hong Qingbiao Jiangxi Provincial Institute of Parasitic Diseases,Nanchang ,China, Jiangsu Institute of Parasitic Diseases,China.PREDICTION OF SNAIL HABITATS IN THE MARSHLAND AROUND POYANG LAKE AFFECTED BY FLOOD IN 1998 USING REMOTE SENSING[J].Chinese Journal of Schistosomiasis Control,2002,14(2):119-121.
Authors:Lin Dandan  Zhou Xiaonong  Liu Yueming  Shun Leping  Hu Fei  Yang Guojing  Hong Qingbiao Jiangxi Provincial Institute of Parasitic Diseases  Nanchang  China  Jiangsu Institute of Parasitic Diseases  China
Institution:Lin Dandan 1,Zhou Xiaonong 2,Liu Yueming 1,Shun Leping 2,Hu Fei 1,Yang Guojing 2,Hong Qingbiao 2 1 Jiangxi Provincial Institute of Parasitic Diseases,Nanchang 330046,China, 2 Jiangsu Institute of Parasitic Diseases,China
Abstract:Objective To understand the impact of the flood in 1998 on the snail distribution in the marshland around the Poyang Lake. Methods The Landsat TM images were purchased and Oncomelania snail distribution in the marshland were surveyed from 1999 to 2000. In accordance with the established model, the Normalized Difference Vegetation Index (NDVI) were extracted from images, then the classified time difference images were overlaid to show the potential snail habitats. The potential snail habitats were randomly selected and compared with the ground truth data of snail distribution. Results The coincidence between potential snail habitats from image analysis and ground truth data was high with the general coincidence rate 76 92% (30/39), including 92 31% (12/13) in large habitats, 85 71% (12/14) in medium habitats, and 50 00% (6/12) in small habitats. Howerer, potential snail habitats inside the embankment may exist. Conclusion It is promising to apply the remote sensing techniques in prediction of snail habitats and risk areas for transmission of schistosomiasis.
Keywords:Remote sensing  Prediction  Flood  Oncomelania  snail  Habitats
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