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MAPS ARE PICTORIAL depictions of the earth. When data are linked to geography, it is called georeferencing. The maps created with this process provide visualization of various indicators affecting humans. A seemingly simple concept, poverty maps are spatial representations of poverty assessments; however, assessing poverty is not a clear-cut process. As computer technology has advanced, it has become easier to create more detailed maps using large datasets and complex statistical models. Whereas the work is increasingly sophisticated, the map products are relatively simple to understand and they allow us to see statistics as a picture rather than as equations and tables.

The concept of poverty is multidimensional and uses a variety of determinants. In addition to the standard indicators of income level and Gross Domestic Product (GDP) per capita, other determinants might be consumption levels, education, health, economic opportunity, climatic factors, the existence of or access to services, infrastructure, etc. The determinants selected will vary according to the level of geography under consideration as well as the intended purpose of the map.

Geography and Data

Poverty maps are created by using specialized software called Geographic Information Systems (GIS) and a variety of data. The maps are built with layers depicting various elements appropriate to the geography being examined and the determinants selected by the researchers. The determinants of poverty can be joined using a statistical model and by creating layers within a map. It is important to understand that the earth's land and peoples are divided in multiple ways. The most obvious and immediate division is the use of geopolitical boundaries at the national level. Other layers might include a different level of boundaries (for example, states, regions, counties), topography, points representing services such as schools or hospitals, and data representing different variables.

Mapping poverty at the national level provides the ability to compare and assess the economic status and well-being of a nation's citizenry in relation to the citizens of other countries. However, aggregate nationallevel indicators can hide important differences among smaller geographical areas. For instance, mapping poverty for the United States as a whole will not show variances among states, counties, metropolitan regions, or within cities. Display of data in smaller geographic detail is called a disaggregated map. This makes it possible to display more detailed layers depicting essential elements such as schools, healthcare facilities, or grocery stores.

Display of data in smaller geographic detail is called a disaggregated map.

In many ways, disaggregated data provide a more accurate picture of spatial patterns. Continuing to use the United States as an example, poverty can be mapped according to state boundaries. While this provides more detail, and a level of detail that might be appropriate depending upon the purpose of the map, many variances will still be hidden. For greater understanding of spatial patterns of poverty within the states, data can be depicted at the county and/or city levels or even down to the level of the census block group. This is the smallest level of geography provided by the U.S. Census Bureau, which represents approximately 100 households while maintaining the confidentiality of each individual household. This level of geography allows us to see intricate patterns of variance and similarity among rural and urban populations that would otherwise go unrecognized. These principles of mapping data apply to other countries and regions of the world.

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