Geospatial Analysis of Building Structures in Megacity Dhaka: the Use of Spatial Statistics for Promoting Data-driven Decision-making

Information on spatial building structures is limited, but it can support efficient planning and management in the context of fast-growing big cities in many developing countries. In this paper, we present a spatial analysis approach that includes an estimate of building intensity in the megacity of Dhaka and a spatial analysis using spatial statistics. The entire city was divided into regular grids and the building intensity (both horizontal and vertical) was extracted using vector type building information; the spatial statistics were calculated on the basis of Moran's I and Gini indices. The variability of the estimated spatial statistics is interpreted according to co-relationship or clustering patterns with the location of the central business district (CBD) area as well as the public bus transit infrastructure (routes and stops). The results show that the residential building structure intensity is prominent and the concentrations are distributed all over the city. The mixed-use type building structures show highest clustering, with fewer outliers in the old part of the city. The vertical-use intensities indicate extreme clustering within highly intensified building activity in the nearby CBD area. The higher presence of low-low clustering of horizontal intensity indicated low development at the suburban area. However, the strongly clustered grid cells within residential sector as well as horizontal development classes are less accessible by bus transit within a defined catchment area, whereas the service sector and vertical development type seem to be more accessible. This type of geographic approach, visualization, and statistical information can help in making data-driven planning decisions with the advantage of monitoring urban development; however, the modeling sensitivity and uncertainties in the building data set remain open for further investigation.