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首页> 外文期刊>Geospatial Health >Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters
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Mapping urban and peri-urban breeding habitats of Aedes mosquitoes using a fuzzy analytical hierarchical process based on climatic and physical parameters

机译：使用基于气候和物理参数的模糊层次分析法绘制伊蚊的城市和城市近郊繁殖栖息地

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The spread of dengue fever depends mainly on the availability of favourable breeding sites for its mosquito vectors around human dwellings. To investigate if the various factors influencing breeding habitats can be mapped from space, dengue indices, such as the container index, the house index and the Breteau index, were calculated from Ministry of Public health data collected three times annually in Phitsanulok, Thailand between 2009 and 2011. The most influential factors were found to be temperature, humidity, rainfall, population density, elevation and land cover. Models were worked out using parameters mostly derived from freely available satellite images and fuzzy logic software with parameter synchronisation and a predication algorithm based on data mining and the Decision Tree method. The models developed were found to be sufficiently flexible to accommodate additional parameters and sampling data that might improve prediction of favourable breeding hotspots. The algorithm applied can not only be used for the prediction of near real-time scenarios with respect to dengue, but can also be applied for monitoring other diseases influenced by environmental and climatic factors. The multi-criteria model presented is a cost-effective way of identifying outbreak hotspots and early warning systems lend themselves for development based on this strategy. The proposed approach demonstrates the successful utilisation of remotely sensed images to map mosquito breeding habitats.
机译：登革热的扩散主要取决于其在人类住所周围的蚊媒的有利繁殖地的可用性。为了调查是否可以从太空中绘制出影响繁殖栖息地的各种因素，根据2009年至2008年间泰国彭世洛府每年收集三次的公共卫生数据，计算出登革热指数，例如容器指数，房屋指数和布雷托指数。和2011年。影响最大的因素是温度，湿度，降雨，人口密度，海拔和土地覆盖。使用主要来自免费卫星图像的参数和具有参数同步功能的模糊逻辑软件以及基于数据挖掘和决策树方法的预测算法，对模型进行了建模。发现所开发的模型具有足够的灵活性，可以容纳其他参数和采样数据，从而可以改善对有利育种热点的预测。所应用的算法不仅可以用于预测有关登革热的近实时情况，而且还可以用于监视受环境和气候因素影响的其他疾病。提出的多准则模型是一种确定爆发热点的经济有效方式，而预警系统则可根据该策略为发展提供依据。所提出的方法证明了成功利用遥感图像绘制蚊子繁殖栖息地的地图。

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