Automated recognition of urban objects for morphological urban analysis

Abstract

Abstract It has often been suggested that the physical structure of traditional urban settlements represents a time-tested response to the climatic constraints of a given location, particularly in hot-arid or other regions that are characterized by thermally harsh conditions. To test this premise, vernacular urban forms have been analyzed to identify patterns of built morphology which might have developed as a response to prevailing climatic conditions. This approach is often based on visual analysis and subjective and qualitative recognition of climate-related patterns. The current paper presents an alternative approach, using a quantitative methodology to support the systematic and automated recognition of urban morphological patterns. A parametric GIS model was developed for automated recognition of urban objects, employing the ability of GIS to recognize contextual relations among objects and perform a context-based recognition using basic rules that apply to the organization of urban form. The model was statistically tested for its accuracy with satisfying results. A case study is presented to demonstrate the workability of the model and its potential as a quantitative and systematic tool for quantitatively describing the morphology of urban surfaces for urban climate analysis. As a parametric model, it can be modified and applied to a large number of case studies for developing and updating databases of urban morphology, and these can serve as a basis for the recognition of morphological patterns in urban form.