• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.146-155
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• 2006

A handful of previous studies have attempted to integrate socioeconomic data and remotely sensed data for urban quality of life assessment with their spatial dimension in a zonal unit. However, such a zone-based approach not only has the unrealistic assumption that all attributes of a zone are uniformly spatially distributed throughout the zone, but also has resulted in serious methodological difficulties such as the modifiable areal unit problem and the incompatibility problem with environmental data. An alternative to the zone-based approach can be a pixel-based approach which gets its spatial dimension through a pixel. This paper proposes a pixel-based approach to linking remotely sensed data with socioeconomic data in GIS for urban quality of life assessment. The pixel-based approach uses dasymetric mapping and spatial interpolation to spatially disaggregate socioeconomic data and integrates remotely sensed data with spatially disaggregated socioeconomic data for the quality of life assessment. This approach was implemented and compared with a zone-based approach using a case study of Fulton County, Georgia. Results indicate that the pixel-based approach allows for the calculation of a microscale indicator in the urban quality of life assessment and facilitates efficient data integration and visualization in the assessment although it costs an intermediate step with more processing time such as the disaggregation of zonal data. The results also demonstrate that the pixel-based approach opens up the potential for the development of new database and increased analytical capabilities in urban analysis.

• Spatial Information Research
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• v.22 no.3
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• pp.35-46
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• 2014

Population data are usually provided at administrative spatial units in Korea, so areal interpolation is needed for fine-grained analysis. This study aims to compare various methods of areal interpolation for population subgroups rather than the total population. We estimated the number of elderly people and single-person households for small areal units from Dong data by the different interpolation methods using 2010 census data of Seoul, and compared the estimates to actual values. As a result, the performance of areal interpolation methods varied between the total population and subgroup populations as well as between different population subgroups. It turned out that the method using GWR (geographically weighted regression) and building type data outperformed other methods for the total population and households. However, the OLS regression method using building type data performed better for the elderly population, and the OLS regression method based on land use data was the most effective for single-person households. Based on these results, spatial distribution of the single elderly was represented at small areal units, and we believe that this approach can contribute to effective implementation of urban policies.