Mapping Spatial Variability in Health and Wealth Indicators in Accra, Ghana Using High Spatial Resolution Imagery

Wednesday, 17 December 2014: 4:36 PM
Ryan Engstrom, George Washington University, Washington, DC, United States and Eric Ashcroft, National Academy of Science, Washington, DC, United States
There has been a tremendous amount of research conducted that examines disparities in health and wealth of persons between urban and rural areas however, relatively little research has been undertaken to examine variations within urban areas. A major limitation to elucidating differences with urban areas is the lack of social and demographic data at a sufficiently high spatial resolution to determine these differences. Generally the only available data that contain this information are census data which are collected at most every ten years and are often difficult to obtain at a high enough spatial resolution to allow for examining in depth variability in health and wealth indicators at high spatial resolutions, especially in developing countries. High spatial resolution satellite imagery may be able to provide timely and synoptic information that is related to health and wealth variability within a city. In this study we use two dates of Quickbird imagery (2003 and 2010) classified into the vegetation-impervious surface-soil (VIS) model introduced by Ridd (1995). For 2003 we only have partial coverage of the city, while for 2010 we have a mosaic, which covers the entire city of Accra, Ghana. Variations in the VIS values represent the physical variations within the city and these are compared to variations in economic, and/or sociodemographic data derived from the 2000 Ghanaian census at two spatial resolutions, the enumeration area (approximately US Census Tract) and the neighborhood for the city. Results indicate a significant correlation between both vegetation and impervious surface to type of cooking fuel used in the household, population density, housing density, availability of sewers, cooking space usage, and other variables. The correlations are generally stronger at the neighborhood level and the relationships are stable through time and space. Overall, the results indicate that information derived from high resolution satellite data is related to indicators of health and wealth within a developing world city and that the even if the imagery is collected 10 years after the census information, the relationships are still significant.