40. Ergin Ataman reported on FAO’s efforts, in collaboration with CG Centers and UNEP, to develop a global GIS database, the main aim of which is to create a global environmental database and a modelling/analysis infrastructure for assisting in the implementation and monitoring of the World Food Summit Plans of Action.
41. Poverty mapping can use one of two approaches. A bottom-up approach using socio-economic data aggregated at the subnational level such as survey and census data. Or, a top-down approach using satellite imagery, existing global environmental maps and GIS models. Some examples of maps already made were provided, including maps of rain-fed food production and potential yields/ha, electrical power consumption, road density, the distribution of GDP/km2, nutrition levels, etc. It was noted in discussion, that many countries do not unfortunately keep data on GDP for fisheries separate from the agriculture sector.
42. One of the main problems in poverty mapping is to combine socio-economic data aggregated by administrative boundaries with environmental data based on natural boundaries. But despite these difficulties, combining the data is important, because environmental data such as agro-ecological zones, are often important in terms of food production (potential), market accessibility and vulnerability.
43. Detailed GIS maps can provide a powerful tool to inform about (likely) concentrations of poor and vulnerable people in relation to: agro-ecological zones, marginal or productive lands, major food crop and livestock production systems, market access, and livelihood systems. But problems with making such poverty maps include the large amount of data required, comparability of the information across regions and countries, and the difficulties of standardizing poverty criteria.
