Use of thermal and vegetation index data from earth observing satellites to evaluate the risk of schistosomiasis in Bahia, Brazil
Use of thermal and vegetation index data from earth observing satellites to evaluate the risk of schistosomiasis in Bahia, Brazil
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DOI：
10.1016/s0001-706x(01)00105-x
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发表时间：
2001-04-27
期刊：
影响因子：
2.7
通讯作者：
Reis, R
中科院分区：
文献类型：
--
作者：
Bavia, ME;Malone, JB;Reis, R
利用区域农业气候特征图建立了一个地理信息系统。环境卫星提供的植被指数和地表温度数据，以及巴西巴伊亚270个城市的曼氏血吸虫病流行记录，包括蜗牛宿主分布情况，以研究感染的时空动态，并确定影响血吸虫病分布的环境因素。初步分析表明，人口密度和每年干旱期的持续时间（月）是疾病的重要决定因素。1994年，与巴西国家空间研究所合作，从国家海洋和大气层管理局（诺阿）-11号卫星的高级甚高分辨率辐射计传感器的数据档案中，大约每隔两个月（六对昼夜）选出了涵盖巴伊亚州的昼夜图像数据。制作了这些图像的合成镶嵌图，以制作以下地图：（1）归一化差异植被指数（NDVI）0至+1之间的平均值;（2）0至15摄氏度范围内的平均日温差。对于每一个城市。计算了3 x 3像素（9平方公里）网格的NDVI和dr，并分析了其与血吸虫病流行的关系。结果显示，在95%置信水平下，通过斯皮尔曼等级相关系数，患病率与dT（rho =-0.218）和NDVI（rho = 0.384）存在统计学显着关系。结果支持使用NDVI，DT，干旱期气候应力因素和人口密度的GIS环境风险评估模型在巴西血吸虫病的发展。(C)2001 Elsevier Science B. V.保留所有权利。
A geographic information system (GIS) was constructed using maps of regional agroclimatic features. vegetation indices and earth surface temperature data from environmental satellites, together with Schistosoma mansoni prevalence records from 270 municipalities including snail host distributions in Bahia, Brazil to study the spatial and temporal dynamics of infection and to identify environmental factors that influence the distribution of schistosomiasis. In an initial analysis, population density and duration (months) of the annual dry period were shown to be important determinants of disease. In cooperation with the National Institute of Spatial Research in Brazil (INPE), day and night imagery data covering the state of Bahia were selected at approximately bimonthly intervals in 1994 (six day-night pairs) from the data archives of the advanced very high resolution radiometer (AVHRR) sensor of the National Oceanic and Atmospheric Administration (NOAA)-11 satellite. A composite mosaic of these images was created to produce maps of: (1) average values between 0 and + 1 of the normalized difference vegetation index (NDVI); and (2) average diurnal temperature differences (dT) on a scale of values between 0 and 15 degreesC. For each municipality. NDVI and dr were calculated for a 3 x 3 pixel (9 km(2) area) grid and analyzed for relationships to prevalence of schistosomiasis. Results showed a statistically significant relationship of prevalence to dT(rho = - 0.218) and NDVI (rho = 0.384) at the 95% level of confidence by the Spearman rank correlation coefficient. Results support use of NDVI, dT; dry period climatic stress factors and human population density for development of a GIS environmental risk assessment model for schistosomiasis in Brazil. (C) 2001 Elsevier Science B.V. All rights reserved.