Abstract
Malaria remains one of the most common vector-borne diseases what is predominantly located in the tropics. The study area is the cross-border area between French Guiana and Brazil where the level and intra-annuel dynamic of malaria transmission are variable, with the incidence rates which are relatively high in South America. The environmental risk factors, in particular, land use and land cover, significantly influence the presence, density and spatial distribution of disease vectors, Anopheles mosquitoes. Environmental information, population data and health systems database are rarely comparable on both sides of the Guyana-Brazil border which exclude the homogeneous and bilateral vision. Remote sensing permits to spatially characterize the environment on both sides of the border in an almost continuous and complete manner. The objective of this study is to characterize the favorable environment for the development of vectors and the vector-human interaction in the cross-border area between French Guiana and Brazil using remote sensing. A spatial landscape-based hazard index of malaria transmission was developed at the local scale. Such index allows spatializing the contribution of interaction between forest and non-forest areas on malaria transmission which was then implemented in the entire Amazon region. It quantifies and explains the influence of landscape on the interaction between human population and adult vectors. The identification of potential breeding sites of vectors was tested on a regional scale using the optical and SAR fusion for highlighting the spatial distribution of perennial and large wetlands (lakes, rivers, ponds etc.) and the interfaces with urban and forest environments. The distribution of vectors’ density is affected by physical and chemical properties of potential breeding sites which are related to soil typology. A conceptual model of soil evolution adapted to the Amazon region presents that geomorphological characteristics (altitude, curvature, etc.) are indicators of soil evolution. A soil classification was realized at the regional scale using altimetry data and the conceptual model. The methods, land use and land cover and malaria hazard maps established in this thesis will be integrated in the Observatory Sentinel of cross-border which is being built. This study also contributes to the exploitation of new knowledge about malaria transmission mechanism which can be used to define novel prevention strategies at the local and regional scales.