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OALib Journal期刊
ISSN: 2333-9721
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The role of Remote Sensing and GIS for spatial prediction of vector-borne diseases transmission: A systematic review

Keywords: Ecological modeling , environmental variables , mapping , remote sensing and GIS , spatial prediction , vector-borne diseases transmission

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Abstract:

There have been several attemps made to the appreciation of remote sensing and GIS for the study of vectors,biodiversity, vector presence, vector abundance and the vector-borne diseases with respect to space and time.This study was made for reviewing and appraising the potential use of remote sensing and GIS applications forspatial prediction of vector-borne diseases transmission. The nature of the presence and the abundance of vectorsand vector-borne diseases, disease infection and the disease transmission are not ubiquitous and are confined withgeographical, environmental and climatic factors, and are localized. The presence of vectors and vector-bornediseases is most complex in nature, however, it is confined and fueled by the geographical, climatic andenvironmental factors including man-made factors. The usefulness of the present day availability of the informationderived from the satellite data including vegetation indices of canopy cover and its density, soil types, soil moisture,soil texture, soil depth, etc. is integrating the information in the expert GIS engine for the spatial analysis of othergeoclimatic and geoenvironmental variables. The present study gives the detailed information on the classicalstudies of the past and present, and the future role of remote sensing and GIS for the vector-borne diseasescontrol. The ecological modeling directly gives us the relevant information to understand the spatial variation ofthe vector biodiversity, vector presence, vector abundance and the vector-borne diseases in association withgeoclimatic and the environmental variables. The probability map of the geographical distribution and seasonalvariations of horizontal and vertical distribution of vector abundance and its association with vector-borne diseasescan be obtained with low cost remote sensing and GIS tool with reliable data and speed.

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