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With the rapid accumulation of population and industry, the urban service efficiency requirements in building sustainable and smart cities are increasingly becoming higher. However, current environmental assessment methods require large amounts of data, long assessment cycles, and tedious assessment processes; thus, they cannot quickly respond to the rapidly changing urban green space. To resolve the above problems, we present a multidimensional model for sustainable and smart cities equipped with RE-3DSG sensors to detect the real experience of residents and the three-dimensional structure of the urban green space. RE-3DSG sensors consist of two parts: The net ecosystem service (Net ES) and green volume ratio (GVR), where Net ES provides a solution consisting of runoff control, air purification, cooling, carbon sequestration, noise reduction, and recreational area establishment, while GVR assesses the spatial structure of urban built environment plant clusters. By implementing the proposed model, it is proven that it can assist users (usually decision makers in government departments) to improve the decision-making efficiency and increase the satisfaction of residents with urban green spaces, thereby achieving the goal of building a sustainable and smart city.

A Multidimensional Assessment Model Using RE–3DSG Sensors on Net ES and GVR for Sustainable and Smart Cities