Image Processing Applications for Sustainable Site Planning in Urban Built Environment

Abstract

As per United States Green Building Council (USGBC) guidelines, sustainable site design tops the list of green design parameters. From a micro-level housing complex or neighborhood planning to a macro-level city planning, it has become mandatory to consider the factors responsible for sustainable designs of building sites. GPS and Remote Sensing are two signal processing applications that are essential tools to help architects, planners, and urban designers in the planning of sites for built spaces. They help to get multi-dimensional digital data required for all site features and characteristics which otherwise can be a very lengthy and complicated process, especially for remote site locations. In site planning, digital image processing is done for the environmental factors, natural factors (geology, topography, hydrology, soil, vegetation, wildlife, etc.), climatic factors, and existing land use. In this study, we evaluate and analyze the application of digital images for sustainable site planning with the help of a case study analysis of Dubai Silicon Oasis in Dubai. Normalized Difference in Vegetation Index (NDVI) and Normalized Difference in Water Index (NDWI) were derived for the case area using Landsat 8 dataset. Seasonal variation in NDVI and NDWI was observed in the study area. In this paper, we highlight the need for the inclusion of image processing applications in early site planning stages to make informed decisions. Appropriate size, shape, and placement of green and water components in the site plan would aid in heat mitigation.