A MULTI-DIMENSIONAL ANALYTICS PLATFORM TO SUPPORT PLANNING AND DESIGN FOR LIVEABLE AND SUSTAINABLE URBAN ENVIRONMENT
- 1Centre for Spatial Data Infrastructures and Land Administration, Department of Infrastructure Engineering, The University of Melbourle, 3010 VIC, Parkville, Australia
- 2Singapore Environment Institute, National Environment Agency, 40 Scotts Road, #13-00 Environment Building, 228231, Singapore
- 3Land Survey Division, Singapore Land Authority, 55 Newton Road, #12-01, 307987, Singapore
Keywords: 3D Geospatial, BIM, CityGML, Urban Analytics, SDI, Urban Liveability
Abstract. New urban strategies encourage compact city and higher density urban development due to unprecedented city growth and rapid urbanisation. This has led to greater attention to multi-dimensional representation, modelling and analytics of urban settings among urban planners, decision makers, and researchers. Nowadays, urban planning and urban design practitioners and scholars leverage the advancements in computer technology and multi-dimensional visualisation in examining the development scenarios from physical, environmental, social, and economic aspects. However, many urban planners still rely on two-dimensional (2D) land information and urban designers use three-dimensional (3D) graphic-based engines to asses a proposed building or assess the impact of changing development regulations. This limits the decision makers from a holistic approach through integrating the urban systems with other application domains such as transport, environmental, and disaster management to ensure the liveability of cities. This paper describes the design, and development of a multi-dimensional and spatially enabled platform to support liveability planning in Singapore. A Quantitative Urban Environment Simulation Tool (QUEST), developed in Singapore, leveraged 3D mapping data captured under the Singapore Land Authority’s (SLA) 3D National Topographic Mapping project. SLA's 3D data including Building Information Model (BIM), CityGML, and other geospatial data (building footprints and land use) were processed and adapted as a service for a series of urban analytics. The paper concludes that the prerequisites for any urban environmental simulation system to be integrated with other application domains are 3D mapping data and a digital urban model, which must be spatially accurate and based on open data standards.