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[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE; Remote sensing methods for locating and monitoring temporary ponds over large areas in arid lands were tested on a study site in Northern Senegal. Three main results are presented, validated with field data and intended to highlight different spectral, spatial and temporal characteristics of the methods: (1) Among several water indices tested, two Middle Infrared-based indices (MNDWIModified Normalized Difference Water Index and NDWI1Normalized Difference Water Index) are found to be most efficient; (2) an objective method is given prescribing the necessary sensor spatial resolution in terms of minimal detected pond area; and (3) the potential of multi-temporal MODIS imagery for tracking the filling phases of small ponds is illustrated. These results should assist in epidemiological studies of vector-borne diseases that develop around these ponds, but also more generally for land and water management and preservation of threatened ecosystems in arid areas.

A model for the spatial and temporal dynamics of dengue fever is proposed in this article. The vector population dynamics is derived from a diffusion equation that is based on environmental parameters at the scale of a remote-sensing image. Vectors and hosts populations are then classically divided into compartments corresponding to their respective disease status. The transmission processes between hosts and vectors are described by a set of differential equations. The link between the vector population diffusion model and the compartmental model enables one to describe both the spatial and temporal dynamics of the disease. Simulations in artificial and actual landscapes show the advantage of using remotely sensed and complementary meteorological data for modelling in a realistic way the geographic spread of a vector-borne disease such as dengue fever.

A model for the spatial and temporal dynamics of dengue fever is proposed in this article. The vector population dynamics is derived from a diffusion equation that is based on environmental parameters at the scale of a remote-sensing image. Vectors and hosts populations are then classically divided into compartments corresponding to their respective disease status. The transmission processes between hosts and vectors are described by a set of differential equations. The link between the vector population diffusion model and the compartmental model enables one to describe both the spatial and temporal dynamics of the disease. Simulations in artificial and actual landscapes show the advantage of using remotely sensed and complementary meteorological data for modelling in a realistic way the geographic spread of a vector-borne disease such as dengue fever.