Poverty maps are important tools that provide information on the spatial distribution of poverty within a country. They are used to affect various kinds of decisions, ranging from poverty alleviation programmes to emergency response and food aid.
However, the use of poverty maps alone does not furnish an estimate of the causal linkage between poverty and the variables that influence it; such maps furnish only ‘visual’advice. For this reason, researchers usually look for the possible existence of empirical relationships between poverty and socio-economic indicators. They make use of statistical methods such as the econometric model that combines census and survey data as applied in South Africa and Ecuador (Hentschel et al., 2000).
Another characteristic of poverty map studies is that to date they have not taken account of the geographical components (location) and environmental data that may have an important impact on research results.
Environmental degradation contributes to poverty through worsened health and by constraining the productivity of those resources on which the poor rely. Moreover, poverty restricts the poor to acting in ways that harm the environment. Poverty is often concentrated in environmentally fragile ecological zones where communities face and contribute to different kinds of environmental degradation. In addition, demographic factors can be involved in complex ways (high population growth rates are associated with poverty) and exacerbate problems of environmental degradation.
In the social sciences, spatial contiguity in social and economic variables is a consequence of the instincts of individuals and of the patterns of behaviour and economic constraints that taken together help bind social space into recognizable structures. In a village or urban community, many of the households may have similar sources of income, and all households are affected by the same agroclimatic and geographic conditions. They also have other circumstances in common including road conditions, availability of public facilities for services such as health, water supply and education. Hence, it is reasonable to suppose that households living in the same area tend to act in similar ways and to influence one another.
In many countries, poverty and food security are highly heterogeneous phenomena showing a wide spatial variability. Large differences between the standard of living of populations in different geographical areas are common in both developed and developing countries. Spatial heterogeneity between areas can be introduced for a variety of reasons, including differences in agroclimatic conditions, geographic conditions (particularly access to main urban centres and markets), the presence of natural resources (particularly water for irrigation), other non-physical conditions (historical, ethnical, etc.) and facets of public policy (Jalan and Ravallion, 1998).
However, it is often difficult to measure heterogeneity in poverty and food security correctly using conventional analytical tools. The key problem is one of obtaining data that permit the measurement of poverty and food security at a level of disaggregation that is sufficient to capture the heterogeneity related to spatial variability.
