遥感技术用于洪水期间监测钉螺孳生地和钉螺扩散的研究

目的利用卫星专题制图仪(Thematic Mapper,TM)遥感图像,探索在洪水季节判别滩地钉螺孳生地和钉螺扩散趋势。方法将遥感资料通过ERDAS IMAGE 8.4软件将其转换为能够分析的栅格数据。用TM3、TM4、TM5波段数据对研究试区遥感数据重新进行假彩色合成,应用图像非监督分类(Unsupervised classfication)模型对假彩色合成图片进行非监督分类。根据现场实地调查情况,判别所分出的各类别的地物属性,并与未分类前图片进行比较。结果经过非监督分类后,可清楚地辨别所设定的10类地物特征,且与实地勘察结果相吻合。现场调查所获的钉螺分布及其扩散情况与该试区遥感分类图片相比较,发现钉螺分布区域均有草地、芦苇及柳林分布,钉螺扩散区域也仅局限于有草地和林地分布的地带,而同样被洪水淹没的无植被或植被稀少的滩地则未发现钉螺扩散。结论通过计算机处理的遥感资料不仅能够识别江水淹没范围、区分不同的水体(如江水和池塘水),而儿能够分辨出被洪水淹没滩地的植被分布情况。在洪水期间利用遥感技术能够监测钉螺孳生地的变化和钉螺潜在扩散趋势。

STUDY ON REMOTE SENSING TECHNOLOGY TO SUPERVISE SNAIL BREEDING AREAS AND SNAIL PERVASION IN INUNDATION

Objective To probe how to differentiate breeding areas and pervasion trend of snail in marshland areas during inundation through using satellite TM data. Methods To transform satellite data into raster deta through ERDAS IMAGE 8.4 software. TM satellite images were applied to false color composite using TM3, TM4, TM5, then using unsupervised classification model to classify the image. To differentiate the attribute of the classified earth substance according to locale survey, and compare with the unclassified false color composite image. Results Through unsupervised classification, the character of the ten types of earth substance can been distinguished distinctly, and inosculate with the reconnaissance results on the spot. Comparing snail distribution and snail pervasion acquired through field survey with the classified satellite image, we could find snail distribute on grass, bulrush, willow areas, and snail pervasion areas also limited on the grass and tree areas, and that snail didn't perverse to the submersed marshland with no vegetation or sparse vegetation. Conclusion Satellite data transacted through computer not only can identify the range of submersed areas by flood, distinguish different water (such as river water and pond water), but also can differentiate the distribution of vegetation on the marshland submersed by flood. We can supervise the change of snail breeding areas and the trend of snail pervasion during inundation by using remote sensing technology.