首页> 外文期刊>Acta tropica: Journal of Biomedical Sciences >A geographic information and remote sensing based model for prediction of Oncomelania hupensis habitats in the Poyang Lake area, China.
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A geographic information and remote sensing based model for prediction of Oncomelania hupensis habitats in the Poyang Lake area, China.

机译:基于地理信息和遥感的prediction阳湖地区钉螺生境预测模型。

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摘要

A model was developed using remote sensing and geographic information system technologies for habitat identification of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum, in the Poyang Lake area, China. In a first step, two multi-temporal Landsat TM 5 satellite images, one from the wet and the second from the dry season, were visually classified into different land-use types. Next, the normalized difference vegetation index was extracted from the images and the tasseled-cap transformation was employed to derive the wetness feature. Our model predicted an estimated 709 km2 of the marshlands in Poyang Lake as potential habitats for O. hupensis. Near-ground temperature measurements in April and August yielded a range of 22.8-24.2 degrees C, and pH values of 6.0-8.5 were derived from existing records. Both climatic features represent suitable breeding conditions for the snails. Preliminary validation of the model at 10 sites around Poyang Lake revealed an excellent accuracy for predicting the presence of O. hupensis. We used the predicted snail habitats as centroids and established buffer zones around them. Villages with an overall prevalence of S. japonicum below 3% were located more than 1200m away from the centroids. Furthermore, a gradient of high-to-low prevalence was observed with increasing distance from the centroids. In conclusion, the model holds promise for identifying high risk areas of schistosomiasis japonica and may become an important tool for the ongoing national schistosomiasis control programme. The model is of particular relevance for schistosome-affected regions that lack accurate surveillance capabilities and are large enough to be detected at most commercially available remote sensing scales.
机译:利用遥感和地理信息系统技术开发了一个模型,用于识别the阳湖地区日本血吸虫的中间寄主蜗牛-钉螺的栖息地。第一步,从视觉上将两幅多时相Landsat TM 5卫星图像,分别从潮湿季节和第二幅干旱季节,视觉上分为不同的土地利用类型。接下来,从图像中提取归一化的差异植被指数,并使用流苏变换来得出湿度特征。我们的模型预测了Po阳湖709平方公里的沼泽地可能是湖h的潜在栖息地。在4月和8月的近地温度测量结果表明,温度范围为22.8-24.2摄氏度,pH值6.0-8.5来自现有记录。这两个气候特征都代表了蜗牛的适宜繁殖条件。对Po阳湖周围10个地点的模型进行的初步验证表明,该方法可很好地预测h.ensis的存在。我们将预测的蜗牛栖息地用作质心,并在它们周围建立了缓冲区。总体流行率低于3%的村庄位于距质心1200m以上的地方。此外,随着距质心的距离增加,观察到了从高到低的患病率梯度。总之,该模型有望确定日本血吸虫病的高危地区,并可能成为正在进行的国家血吸虫病控制计划的重要工具。该模型与受血吸虫病影响的地区特别相关,这些地区缺乏精确的监视功能,并且足够大,无法在大多数市售遥感尺度上进行检测。

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