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[丘陵山区环境遥感替代指标与钉螺分布的关系]

[Relationship between environmental remote sensing alternate indexes and Oncomelania snail distribution in hilly and mountainous areas].

作者信息

Dong Yi, Li Zhao-Hui, Feng Xi-Guang, Dong Xing-Qi

机构信息

Yunnan Provincial Institute of Endemic Disease Control and Prevention, Dali 671000, China.

出版信息

Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2011 Jun;23(3):258-61.

Abstract

OBJECTIVE

To analyze the relationship between Oncomelania snail distribution and environmental remote sensing indexes in hilly and mountainous areas.

METHOD

The normalized different vegetation index (NDVI), land surface temperature (LST), humidity index (Wetness) of 85 snail spots in Dali City were extracted for statistical analysis by TM image, and the land-use types were classified. LST, NDVI, Wetness, snail density and land-use types were overlaid and analyzed by using a weight of suitability model of ArcGIS 9.2, and snail appropriate distribution range in Dali City was calculated.

RESULTS

The distribution of LST, NDVI, Wetness values of the investigated snail points were approximately normal, and most of the snail points distributed nearby the average values of the remote sensing alternate indexes, then gradually reduced to the ends. More than 90% of the snail spots were distributed in the land type with crops and grassland. The environments in Dali City were divided into unsuitable snail environment (0-14 points), suitable snail environment (15-21 points), and optimum snail environment (22-26 points) by the weight suitability mode.

CONCLUSIONS

Environmental remote sensing indicators can reflect the environmental factors affecting snail distribution directly. Combining remote sensing with GIS and field survey can describe, judge and forecast the distribution of snails.

摘要

目的

分析丘陵山区钉螺分布与环境遥感指标之间的关系。

方法

利用TM影像提取大理市85个钉螺点位的归一化植被指数(NDVI)、地表温度(LST)、湿度指数(Wetness)进行统计分析,并对土地利用类型进行分类。运用ArcGIS 9.2的适宜性权重模型对LST、NDVI、Wetness、钉螺密度及土地利用类型进行叠加分析,计算大理市钉螺适宜分布范围。

结果

所调查钉螺点位的LST、NDVI、Wetness值分布近似正态,多数钉螺点位分布于遥感替代指标平均值附近,向两端逐渐减小。90%以上的钉螺点位分布于农作物与草地的土地类型。通过权重适宜性模型将大理市环境分为钉螺不适宜环境(0 - 14分)、钉螺适宜环境(15 - 21分)、钉螺最适宜环境(22 - 26分)。

结论

环境遥感指标能直接反映影响钉螺分布的环境因素。遥感与GIS及实地调查相结合可描述、判断和预测钉螺分布。

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