A cokriging method for estimating population density in urban areas
Population information is typically available for analysis in aggregate socioeconomic reporting zones, such as census blocks in the United States and enumeration districts in the United Kingdom. However, such data mask underlying individual population distributions and may be incompatible with other information sources (e.g. school districts, transportation analysis zones, metropolitan statistical areas, etc.). Moreover, it is well known that there are potential significance issues associated with scale and reporting units, the modifiable areal unit problem (MAUP), when such data are used in analysis. This may lead to biased results in spatial modeling approaches. In this study, impervious surface fraction derived from Thematic Mapper (TM) imagery was applied to derive the underlying population of an urban region. A cokriging method was developed to interpolate population density by modeling the spatial correlation and cross-correlation of population and impervious surface fraction. Results suggest that population density can be accurately estimated using cokriging applied to impervious surface fraction. In particular, the relative population estimation error is ?0.3% for the entire study area and 1015% at block group and tract levels. Moreover, unlike other interpolation methods, cokriging gives estimation variance at the TM pixel level.
cokriging population interpolation remote sensing