The dataset contains the predicted areas of suitability for two tsetse fly species (palpalis and tachinoides). All of the distributions have been produced using variations of the same methodology - by modelling the "known" presence and absence of the flies (usually the 1977 Ford and Katondo maps modified with more recent information collected from national and international agencies and researchers). The modelling process relies on logistic regression of fly presence against a wide range of predictor variables for a large number of regularly spaced sample points for each area. The predictor variables include remotely sensed (satellite image) surrogates of climate - vegetation, temperature, moisture - which have been subjected to Fourier processing to provide an additional set of season and timing related measures for each parameter. Demographic, topographic and agroecological predictors are also used. These models are then applied to the predictor imagery to determine the predicted areas of suitability for tsetse. Data are provided at 1 kilometre resolution. The maps were produced in December 2002 for FAO/IAEA Joint Division by Environmental Research Group Oxford (ERGO Ltd) in collaboration with the Trypanosomosis and Land Use in Africa (TALA) research group.

Eco-climatic zones were produced taking into account land-surface and atmospheric characteristics (the photosynthetic activity, the temperature of the earth?s surface, the atmospheric drying power, the rainfall, the potential evapotranspiration, the length of growing period for plants, the surface elevation). Most of these features could be accurately predicted using satellite data; some others needed a combination of remotely sensed and ground-based data. Remotely sensed data were acquired by NOAA-AVHRR sensor and by Meteosat satellite. The AVHRR satellite data were available in dekadal images for a 13 year series from 1982-1994. Meteosat imagery runs from 1988 to 1997. The information layer was produced for FAO in January 1999 by Environmental Research Group Oxford (ERGO Ltd) in collaboration with the Trypanosomosis and Land Use in Africa (TALA) research group at the Department of Zoology, University of Oxford.

This dataset is an aggregated version of the original national Africover landcover multipurpose database. A 26-class legend is used to aggregate the classes present in the original full resolution, multipurpose landcover database. A single legend is applicable to the eight trypanosomiasis-affected countries mapped during Africover project (Burundi, Democratic Republic of the Congo, Kenya, Rwanda, Somalia, Sudan, Uganda and United Republic of Tanzania).

The dataset contains the predicted areas of suitability for three tsetse fly species (f. fuscipes, morsitans and pallidipes). All of the distributions have been produced using variations of the same methodology - by modelling the "known" presence and absence of the flies (usually the 1977 Ford and Katondo maps modified with more recent information collected from national and international agencies and researchers). The modelling process relies on logistic regression of fly presence against a wide range of predictor variables for a large number of regularly spaced sample points for each area. The predictor variables include remotely sensed (satellite image) surrogates of climate - vegetation, temperature, moisture - which have been subjected to Fourier processing to provide an additional set of season and timing related measures for each parameter. Demographic, topographic and agroecological predictors are also used. These models are then applied to the predictor imagery to determine the predicted areas of suitability for tsetse. Data are provided at 1 kilometre resolution. The maps were produced in December 2001 for FAO/IAEA Joint Division by Environmental Research Group Oxford (ERGO Ltd) in collaboration with the Trypanosomosis and Land Use in Africa (TALA) research group.

This dataset is an aggregated version of the original national Africover landcover multipurpose database. A 26-class legend is used to aggregate the classes present in the original full resolution, multipurpose landcover database. A single legend is applicable to the eight trypanosomiasis-affected countries mapped during Africover project (Burundi, Democratic Republic of the Congo, Kenya, Rwanda, Somalia, Sudan, Uganda and United Republic of Tanzania).

Rinderpest is an OIE List A disease. The standards, included in the International Animal Health Code, and known as the 'OIE Rinderpest Pathway', are the requirements that must be met to obtain official OIE recognition of country/zone freedom from this disease .The map shows the countries and zones by countries that are self-declared provisionally free from rinderpest disease. This information published by the OIE is derived from declarations made by the official Veterinary Services of Member Countries to OIE. The map shows also the countries recognised by OIE, as free from rinderpest disease and rinderpest infection.

The dataset contains the predicted areas of suitability for five tsetse fly species (morsitans, pallidipes, austeni, brevipalpis and swynnertoni). All of the distributions have been produced using variations of the same methodology - by modelling the "known" presence and absence of the flies (usually the 1977 Ford and Katondo maps modified with more recent information collected from national and international agencies and researchers). The modelling process relies on logistic regression of fly presence against a wide range of predictor variables for a large number of regularly spaced sample points for each area. The predictor variables include remotely sensed (satellite image) surrogates of climate - vegetation, temperature, moisture - which have been subjected to Fourier processing to provide an additional set of season and timing related measures for each parameter. Demographic, topographic and agroecological predictors are also used. These models are then applied to the predictor imagery to determine the predicted areas of suitability for tsetse. Data are provided at 1 kilometre resolution. The maps were produced in May 2003 for FAO/IAEA Joint Division by Environmental Research Group Oxford (ERGO Ltd) in collaboration with the Trypanosomosis and Land Use in Africa (TALA) research group.

This dataset is an aggregated version of the original national Africover landcover multipurpose database. A 26-class legend is used to aggregate the classes present in the original full resolution, multipurpose landcover database. A single legend is applicable to the eight trypanosomiasis-affected countries mapped during Africover project (Burundi, Democratic Republic of the Congo, Kenya, Rwanda, Somalia, Sudan, Uganda and United Republic of Tanzania).

This dataset is an aggregated version of the original national Africover landcover multipurpose database. A 26-class legend is used to aggregate the classes present in the original full resolution, multipurpose landcover database. A single legend is applicable to the eight trypanosomiasis-affected countries mapped during Africover project (Burundi, Democratic Republic of the Congo, Kenya, Rwanda, Somalia, Sudan, Uganda and United Republic of Tanzania).

This dataset is an aggregated version of the original national Africover landcover multipurpose database. A 26-class legend is used to aggregate the classes present in the original full resolution, multipurpose landcover database. A single legend is applicable to the eight trypanosomiasis-affected countries mapped during Africover project (Burundi, Democratic Republic of the Congo, Kenya, Rwanda, Somalia, Sudan, Uganda and United Republic of Tanzania).