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The integration of urban agriculture into cityscapes necessitates a comprehensive understanding of multiple engineering and environmental factors, including urban fabric, building configurations, and dynamic energy and material flows. In contrast to rural settings, urban areas introduce complexities such as hygrothermal fluctuations, variable sunlight exposure and shadow patterns, diverse plant dimensions and shapes, and material interception. To address these challenges, this study presents an open-source Digital Twin model based on the use of a geographical information system (GIS) for near-real-time solar radiation mapping. This methodology aims to optimize crop productivity, enhance resilience, and promote environmental sustainability within urban areas and enables the near-time mapping of the salient features of different portions of the city using available open data. The work is structured into two main parts: (i) definition of the GIS-based Digital Twin model for mapping microclimatic variables (in particular solar radiation) to support sustainable urban agriculture design and (ii) application of the model to the city of Milan to verify its replicability and effectiveness. The key findings are connected to the possibility to integrate open data (solar radiation) with measurements in situ (illuminance and data referred to the specific crops, with related conversion coefficient) to develop a set of maps helpful for urban farmers but also for designers dealing with the synergy between buildings and urban farms. Initially tested on a neighborhood of Milan (Italy), the model will be applied in the Singapore context to verify analogies and differences. This correlation facilitates a more practical and straightforward examination of the relationships between solar irradiation and illuminance values of natural sunlight (involving both incident and diffuse light). The consistency of measurements allows for the precise documentation of these fluctuations, thereby enhancing the understanding of the influence of solar radiation on perceived luminance levels, particularly in urban environments characterized by diverse contextual factors such as vegetation, nearby structures, and geographical positioning.
Clementi et al. (Thu,) studied this question.