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Memórias do Instituto Oswaldo Cruz
Fundação Oswaldo Cruz, Fiocruz
ISSN: 1678-8060
EISSN: 1678-8060
Vol. 94, No. 2, 1999, pp. 273-276
Bioline Code: oc99053
Full paper language: English
Document type: Research Article
Document available free of charge

Memórias do Instituto Oswaldo Cruz, Vol. 94, No. 2, 1999, pp. 273-276

 en Can Remotely Sensed Meteorological Data Significantly Contribute to Reduce Costs of Tsetse Surveys?
Guy Hendrickx; Ayitou Napala; David Rogers; Patrick Bastiaensen & Jan Slingenbergh


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 generating tsetse distribution and abundance maps from remotely sensed data, using a
restricted amount of field data. A discriminant analysis model is tested using contemporary tsetse data and remotely sensed, low resolution data acquired from the National Oceanographic and Atmospheric Administration and Meteosat platforms. A split sample technique is adopted where a randomly selected part of the field measured data (training set) serves to predict the other part (predicted set). The obtained results are then compared with field measured data per corresponding grid-square. Depending on the size
of the 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 analysis for the prediction, not only of the tsetse distribution, but more importantly of their abundance. This opens up new avenues because satellite predictions and field data may be combined to strengthen or substitute one another and thus reduce costs of field surveys.

abundance - discriminant analysis - Glossina tachinoides - prediction - remote sensing - Togo

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