An approach to linking remotely sensed data and areal census data

With the increasing availability of remotely sensed data and census data, discussing their relationship is one of the important issues in GIS data integration. This paper proposed an approach to linking three levels (macro, medium and micro) of land classifications with areal census data on hierarchical census boundaries. Specifically, a method of building the correlations between areal census dwelling data and residential densities classified by a remote sensing approach was demonstrated. First, a texture statistic (homogeneity) along with six Thematic Mapper (TM) bands (bands 1-5 and 7) was put together to classify residential density levels. The homogeneity slightly enhanced classification accuracy. Then, to test the correlations between census dwelling data and residential densities, a multiple linear regression was conducted. It was found that areal census dwelling data had higher correlations with areas of different residential densities than with the aggregated area of a whole residential area at an individual census zone level. Finally, the paper discussed that dis-aggregation of areal census data based on dwelling densities within the framework of remote sensing and GIS would be very useful for multidisciplinary studies, such as natural hazards risk assessment.