G. Hendrickx et al., Can remotely sensed meteorological data significantly contribute to reducecosts of tsetse surveys?, MEM I OSW C, 94(2), 1999, pp. 273-276
A 0.125 degree raster or grid-based Geographic Information System with data
on tsetse, trypanosomosis, animal production, agriculture and land use has
recently been developed in Togo. This paper addresses the problem of gener
ating tsetse distribution and abundance maps from remotely sensed data, usi
ng a restricted amount of field data. A discriminant analysis model is test
ed using contemporary, tsetse data and remotely sensed, low resolution data
acquired from the National Oceanographic and Atmospheric Administration an
d Meteosat platforms, A split sample technique is adopted where a randomly
selected part of field measured data (training set) sei? es to predict the
other part (predicted set). The obtained results are their compared with fi
eld measured data per corresponding grid-square. Depending on the size of t
he training set the percentage of concording predictions varies from 80 to
95 for distribution figures and from 63 to 74 for abundance. These results
confirm the potential of satellite data application and multivariate analys
is for the prediction, not only, of the tsetse distribution, but more impor
tantly of their abundance. This opens lip new avenues because satellite pre
dictions and field data may be combined to strengthen or substitute one ano
ther and thus reduce costs of field surveys.