Remotely sensed surrogates of meteorological data for the study of the distribution and abundance of arthropod vectors of disease.
This paper gives an overview of how certain meteorological data used in studies of the population dynamics of arthropod vectors of disease may be predicted using remotely sensed, satellite data. Details are given of the stages of processing necessary to convert digital data arising from satellite sensors into ecologically meaningful information. Potential sources of error in these processing steps are also highlighted. Relationships between ground-measured meteorological variables (saturation deficit, ground temperature and rainfall) and data from both the National Oceanic and Atmospheric Administration's, polar-orbiting, meteorological satellites and the geostationary, Meteosat satellite are defined and examples detailed for Africa. Finally, the current status of existing satellite platforms and future satellite missions are reviewed and potential data availability discussed. How such satellite-based predictions have proved valuable in understanding the distribution of tsetse fly species in Côte d'Ivoire and Burkina Faso will be the subject of a future review.
Hay
S I
SI
Department of Zoology, University of Oxford, U.K.
Tucker
C J
CJ
Rogers
D J
DJ
Packer
M J
MJ
D000349:Africa; D000818:Animals; D001179:Arthropod Vectors; D005544:Forecasting; D014943:Global Health; D008685:Meteorological Concepts; D011157:Population Dynamics; D017215:Satellite Communications / Q000639:trends; D012815:Signal Processing, Computer-Assisted