A GIS-based method for modeling urban-climate parameters using automated recognition of shadows cast by buildings

Abstract Projections for the next thirty years predict a rapid growth in urban population, particularly in the less developed regions. Constructing and updating GIS databases of 3D urban form is essential for analyzing spatial phenomena related to urbanization. One of these phenomena, urban climate, is influenced by urban morphology. A prerequisite for representing urban morphology is 3D data including the height of urban features. In cases where no city plans or field survey data are available, a viable option is to use remotely-sensed data for recognition of urban features. Often, the output of automated object recognition consists of footprints of urban features. A known method for calculating a feature's height for reconstructing 3D urban morphology is to use the shadows cast by those features. A GIS-based method for constructing 3D geodatabases of urban morphology from cast shadows and analyzing geometrical parameters for urban-climate analysis was developed. The method focuses on the aspect-ratio of inner courtyards and its relation to solar access. A case-study is presented to demonstrate the feasibility of this method. Results demonstrate that the method offers a reliable and low-cost process for constructing 3D geodatabases that can be applied to the analysis of urban-climate parameters in less developed regions, where costly data and sophisticated processing practices are less accessible. This method can enhance the understanding of microclimatic conditions and facilitate climate conscious and sustainable future urban planning in sprawling urban centers.

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