Apports de la combinaison d’images satellites optique et RADAR dans l’étude des maladies à transmission vectorielle : cas du paludisme à la frontière Guyane française – Brésil
The distribution of mosquito vectors of malaria is controlled by various factors such as climate, land cover and land use, or human activities. In the Amazon region, endemic foci of malaria persist, particularly on the border between French Guiana and Amapa State in Brazil. This area, long by 300 km...
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| Autores principales: | , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN FR PT |
| Publicado: |
Confins
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/f381bd6d3b744b7c9db1a529e4e7e601 |
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| Sumario: | The distribution of mosquito vectors of malaria is controlled by various factors such as climate, land cover and land use, or human activities. In the Amazon region, endemic foci of malaria persist, particularly on the border between French Guiana and Amapa State in Brazil. This area, long by 300 km, presents many difficulties in collecting informations necessary for the health management of the local populations. In this type of geographical context, with few, isolated and cross-border data, a methodology based on the exploitation of remote sensing images is particularly appropriate. Remote sensing data have wide spatial coverage, and a large range of spatial resolutions. Here we present an approach combining high resolution and very high spatial resolution optical and SAR satellite data. Our method makes it possible to map the different types of land cover in the tropical border context French Guiana - Brazil, characterized by a persistent cloud cover. The results show that the complementarity of optical and RADAR sensors allows the production of multi-scale mapping of land use/land cover (LULC) independently from cloud cover. In particular, we produced LULC classifications to generate spatialized indicators and characterize the relationship between suitable habitats for malaria vectors and environmental factors. Through a discussion on the application of composite LULC classifications for the assessment of malaria exposure risk at various scales, this case study illustrates the interest of satellite remote sensing approaches to characterize landscape elements and land cover, which can account for the distribution of vector populations in connection with arboviruses transmission. |
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