MULTI-SENSOR DATA FUSION FOR IDENTIFYING MALARIA ENVIRONMENTAL FEATURES

Zhichao Li (1) , Thibault Catry (1) , Nadine Dessay (2) , Emmanuel Roux (1) , Etienne Mahé (1) , F. Seyler (1)

1 UMR 228 Espace-Dev, Espace pour le développement
2 ESPACE - Expertise et spatialisation des connaissances en environnement

Malaria remains a persistent health problem in the cross-border area between French Guiana and Brazil. Various factors like environmental changes, population movements, etc. significantly influence the malaria transmission. In such context, optical and SAR data were used for producing a precise land cover map, including the resting and breeding sites of malaria vectors and human habitats. This study is a foundation for quantifying the degree of exposure of human populations to malaria vectors and thus for estimating and monitoring the malaria transmission risk.

Mots clés: Index Terms— Multi-sensor; optical and SAR; classification; remote sensing; malaria

Domaines: Sciences de l'environnement; Environnement et Société

Zhichao Li, Thibault Catry, Nadine Dessay, Emmanuel Roux, Etienne Mahé, et al.. MULTI-SENSOR DATA FUSION FOR IDENTIFYING MALARIA ENVIRONMENTAL FEATURES. IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium, Jul 2016, Beijing, China. ⟨10.1109/IGARSS.2016.7729653⟩. ⟨hal-01829725⟩