Targeting agricultural research for development in Tanzania: an example of the use of GIS for ex ante impact assessment at IITA
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Legg, C. (2007). Targeting agricultural research for development in Tanzania: an example of the use of CIS for ex ante impact assessment at llTA. In A.D. Alene, V.M. Manyong,S. Abele and D. Sanogo, Assessing the impact of agricultural research on rural livelihoods: achievements, gaps, and options (p. 61-74). Ibadan: IITA.
Permanent link to cite or share this item: https://hdl.handle.net/10568/91420
GIS targeting, combining a range of different datasets including climate, topography, population, protected areas, road networks, agricultural production, and markets, is becoming an important tool in planning agricultural research for development. The impact of agricultural investments can be maximized by targeting them to areas where biophysical conditions are optimal for selected crops, and where population densities and market access maximize the economic possibilities. Targeting can be tailored to specific institutional requirements, for example, to emphasize improved nutrition or export-orientated cash crops.Tanzania is the fifth most populous country in Africa, with a very high percentage of its population dependent on agriculture. The incidence of poverty and child malnutrition is high, but large areas of potentially productive agricultural land are only partly developed. There is great scope for increased agricultural production through the introduction of improved crop varieties and novel farming systems, but these must be concentrated in the areas where they will have the greatest impact. Areas of cultivable land were identified by combining topographic data (slopes and altitude) with climate data (eliminating arid areas) and maps of protected areas (no farming in national parks). These were then further processed to remove those areas where predictions of climate change indicate a significant reduction in rainfall by 2025. Relative ease of access to markets (settlements with populations in excess of 20 000) was calculated using maps of land cover, road networks, and slope maps. A combination of cultivable land with ease of access to markets and medium-to-high population densities defines prime targets for agricultural development. For each target area, crop suitabilities were assessed, based on biophysical parameters.