 Multitype Green-Space Modeling for Urban Planning Using GA and GISMeher Nigar Neema and Akira Ohgai Environment and Planning B, 2013, vol. 40, issue 3, 447-473 Abstract: Green spaces can facilitate sustainable urban environment in a number of ways: Purifying air and water, filtering noise, and stabilizing the microclimate. Therefore, city planners have to design optimal sites to provide new green spaces. The present study addresses the genetic-algorithm-based multiobjective modeling of optimal sites for multitype green spaces considering multiple objectives. A new model has been developed and applied to identify the optimum sites for green spaces, particularly parks and open spaces (POSs). We considered six criteria: population, air quality, noise level, air temperature, water quality, and recreational value, including barriers for placing new POSs. The model thus developed was applied to Dhaka as a case study. The spatial functions of GIS are used to quantify, analyze, and represent the six objective criteria of our model. The modeling results show a successful optimization of locations for new POS. In addition, a suitability analysis is performed to find locations of various POSs using GIS. This study provides an indication of how to site multitype green spaces to make a sustainable urban environment. Keywords: green space; sustainable environment; GIS; multiobjective modeling; Pareto optimum; genetic algorithm (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:40:y:2013:i:3:p:447-473 DOI: 10.1068/b38003 Access Statistics for this article More articles in Environment and Planning B |
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