We are rapidly approaching the midpoint of the period set by the UN Agenda 2030 for transforming our activities on the planet Earth. Yet, many of the global issues we have begun with stand still while some of them took a much more severe course. The Sustainable Development Goals (SDGs) are unambiguous. What is unclear is the way to propel our socio-economic organizations into the desired performances. Regarding performance control, the built environment is arguably the most critical system. Every year, we add more urbanized land to the face of the planet without clearly envisioning its environmental effects and social outgrowth. As a result, we frequently find ourselves struggling with unpleasant consequences and unpredicted side effects. In our body of knowledge, there is a missing link between urban structure and performance. This paper offers a systemic breakdown of urban structural parameters and a coherent reading of its performance indicators intending to create a City Information Modelling (CIM) tool. The objective is to formulate the reciprocal relationship between the components of the built environment (as the designer's toolbox) and the system's outcome. To do so, this article moves from the Integrated Modification Methodology (IMM), exploring it through the lens of an Entity-Relationship (ER) schema, delving into its systemic approach to model the built environment as a Complex Adaptive System (CAS). IMM elucidates the intricate structure/performance relationships inherent in the complexity of the built environment. Building upon the successful IMM application in numerous urban transformation projects and retrofitting procedures, our focus is now on streamlining operational processes and accelerating workflow efficiency. Specifically, we seek to optimize the rapid assessment of correlations between structural changes and performance outcomes within the IMM framework. This work aims to operationalize the Agenda 2030, enabling a practical methodological interpretation of targets and indicators in SDG11.

Quality public spaces, especially pedestrian areas, play an essential role in cities. Communities gather in these spaces and benefit from the proximity to activities in a safe and car‐free environment. Pedestrian areas can have greenery, which helps address the issues raised by climate change. Repurposing existing roads is a priority in many cities worldwide whose aim is to improve their social and environmental performance. This study presents a systemic, data‐based approach that supports the transition from the current pervasive car‐based mobility model to a people‐centric, pedestrian‐based one. This transformative model leverages the structural properties of urban systems to reconfigure streets as integral components of a comprehensive strategy aimed at mitigating the effects of climate change. Image segmentation is used to assess the presence of people in the streets. The numerical evidence provided by metrics and indicators is complemented by visual evidence from local‐scale maps. The proposed method is tested on a portion of Bairro Cidade Nova in Rio de Janeiro within the framework of the Integrated and Sustainable Urban Regeneration Milan–Rio (REMIRIO) project, a city‐to‐city cooperation project between Milan (Italy) and Rio de Janeiro (Brazil) funded by the European Union which aims to implement pilot nature‐based solutions to address local environmental issues such as flooding and overheating. In particular, five North–South streets are compared to define customised pedestrianisation interventions within a more comprehensive super‐block strategy with the aim of improving the continuity of the existing green system and the ecosystem services. This precise network diagnostic process can be easily transferred to any urban system.

This study applies the Integrated Modification Methodology (IMM) to assess how morphology-driven, nature-based solutions reduce urban heat island (UHI) effects and flooding in Rio de Janeiro’s Cidade Nova. Multi-scale GIS diagnostics identify green continuity and vertical permeability as critical weaknesses. Simulations (Ladybug/Dragonfly) and hydrological modelling (rational method) quantify the intervention’s impact, including greening, material retrofits, and drainage upgrades. Results show a 38% increase in albedo, a 13% reduction in volumetric heat capacity, and a 30% drop in thermal conductivity. These changes reduce the peak UHI by 0.2 °C hourly, narrowing the urban–rural temperature gap to 3.5 °C (summer) and 4.3 °C (winter). Hydrologically, impervious cover decreases from 22% to 15%, permeable surfaces rise from 9% to 29%, and peak runoff volume drops by 27% (16,062 to 11,753 m³/h), mitigating flood risks. Green space expands from 7.8% to 21%, improving connectivity by 50% and improving park access. These findings demonstrate that IMM-guided interventions effectively enhance thermal and hydrological resilience in dense tropical cities, aligning with climate adaptation and the Sustainable Development Goals.