Abstract
In the current scenario of massive urbanization and rapid grow of urban population, several mitigation and adaptation strategies are proposed to tackle the correlated environmental issues and the effects of climate change. All these solutions are highly related to the utilization of urban surfaces (i.e. building envelopes, streets, public spaces, etc.). The existing trends demonstrate the lack of a systemic approach able to integrate multiple possible functions and avoid sub-optimal solutions in pursuing multiple resiliency and sustainability objectives. For example, in cities, conflicts are arising between the surface uses for renewable energy production, urban agriculture, and green solutions. Urban planning is essential to manage conflicts among different surface uses and ensure their integration in the process toward the creation of resilient and sustainable cities. This involves making spatially explicit decisions about the types of surface use allowable, and the extent and location of these. This decision-making process needs to be supported by accurate and detailed information about the spatial distribution of a set of parameters. Indeed, many environmental and morphological features influence the distribution of surface uses in cities and affect priorities for their definition. These parameters not only include the morphological and geometrical features of the urban area, which can be easily assessed and are already part of “traditional” urban design processes. Hence, a clear understanding of the physical interaction between the built-up environment and the climate boundary conditions is also crucial to determine truly responsive strategies. The physical parameters can be assessed through networks of on-site weather stations and climate sensors; also, environmental simulation approaches can effectively support the definition of the microclimate features proper of each urban site. However, traditional products of environmental simulation tools, abstract climate maps or descriptive texts can be undecipherable and confusing to non-experts and lack the flexibility and adaptability necessary for informing design decisions in complex urban environments with competing demands. This paper presents a systematic framework to support planning decisions about the best possible mix of surface uses and their spatial arrangement in the urban environment based on accurate, detailed, diverse and spatially explicit information. The method implies the assembly of a multivariate spatial database of significant morphological and physical environmental parameters (e.g. air temperature, surface temperature, etc.) using environmental simulation techniques and on-site data collection. The three-dimensional visualization of this database represents a solid base to relate urban planning decisions on surface uses and their effects in terms of microclimatic conditions enhancement and on-site renewable energy production. Furthermore, it provides an easily understandable way to recognize specific elements of the urban environment and orient The application of the method in presented for an urban district in Bolzano, a middle size European city with moist continental climate. The results are discussed in relation to: (i) the application of the method to support urban planning decisions, (ii) its scalability and replicability to cities with different climate and morphological characteristics, and (iii) its suitability to be adopted as framework to inform urban planners and decision makers during the definition of environmentally-conscious solutions based on their impact on microclimate, human thermal comfort, and on-site renewable energy production