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利用卫星数据预测蓖麻硬蜱(Ixodes ricinus (L.))的出现情况。

Using satellite data to forecast the occurrence of the common tick Ixodes ricinus (L.).

作者信息

Daniel M, Kolár J

机构信息

Institute of Tropical Health, Postgraduate School of Medicine and Pharmacy, Prague, Czechoslovakia.

出版信息

J Hyg Epidemiol Microbiol Immunol. 1990;34(3):243-52.

PMID:2273241
Abstract

To forecast the incidence of the common tick, Ixodes ricinus, the authors used the finding that some types of vegetation may indicate the presence of the tick. To obtain the necessary information in a scope which would enable its practical application in medicine to prevent populational exposure to ticks, remote sensing data were utilized as obtained from the Multispectral Scanner operating aboard Landsat 5. A file was selected from the full scene representing a territory which measured 41 by 41 kilometers and in the centre of which there was an area known to have consistently high tick numbers, as revealed in a 25-year continuous study of I. ricinus, and which proved to be a natural focus of tick-borne encephalitis. This area (Potepl) was taken as a model and was compared with its surroundings. Six landscape classes were examined (1--coniferous forest, 2--leaved forest, 3--mixed forest, 4--water basins, 5--glades, 6--housing developments), the former three being of crucial importance to evaluate the probability of tick presence. The 6th category is significant in assessing human exposure to ticks. Data processing was carried out by supervised classification using the Baye's decision rule of maximum likelihood. The findings were obtained both in a graphic form and in the form of statistical reviews as regards the presence of appropriate landscape categories.

摘要

为预测蓖麻硬蜱这种常见蜱虫的发病率,作者利用了某些植被类型可能表明蜱虫存在这一发现。为在能使其在医学上实际应用以预防人群接触蜱虫的范围内获取必要信息,使用了从搭载在陆地卫星5号上的多光谱扫描仪获取的遥感数据。从代表一块41×41公里区域的全场景中选取了一个文件,该区域中心有一个已知蜱虫数量一直很高的区域,这是在对蓖麻硬蜱进行的为期25年的持续研究中发现的,并且该区域被证明是蜱传脑炎的一个自然疫源地。这个区域(波特普尔)被用作模型,并与其周边区域进行比较。研究了六种景观类别(1——针叶林,2——阔叶林,3——混交林,4——水域,5——林间空地,6——住宅区),前三种对于评估蜱虫存在的可能性至关重要。第六类在评估人类接触蜱虫方面具有重要意义。数据处理通过使用最大似然贝叶斯决策规则的监督分类进行。关于适当景观类别的存在情况,研究结果以图形形式和统计综述形式呈现。

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