This paper presents a new methodological approach for analysing the impacts of climate change on the urban habitat and improving the quality of life for citizens. The study falls within the diagnostic phase of the Climate Change and Urban Health Resilience (CCUHRE) research project applied to the rationalist neighbourhood of Monticelli, a suburb of Ascoli Piceno (Italy). The methodological approach tests innovative and multidisciplinary cognitive tools to quantify the impacts of climate change and create refined risk maps combining remote sensing, spatial data, satellite images, and thermal fluid dynamic (CFD) simulations. These tools created an atlas of green areas and surfaces using scientific indexes that describe the relationship between the urban form and heat and between the type of ground and materials. The information yielded by geoprocessing will allow critical aspects in the context to be addressed with site-specific strategies. In fact, through downscaling, it is possible to analyse the thermal fluid dynamics characteristics of the most significant urban areas and identify the related weather/climate characteristics, perceptual scenarios, and thermal stressed regions. The results have provided a dataset that defines the degree of vulnerability of the neighbourhood and identifies the areas exposed to thermal risk.

Green Infrastructure (GI) is crucial for urban climate adaptation, providing ecosystem services like mitigating the urban heat island effect and enhancing stormwater management, alongside benefits for public health and biodiversity. Effective GI implementation remains challenging, particularly in dense, rapidly urbanized mid-Adriatic coastal cities, classified as climate hotspots like other Mediterranean contexts. This paper presents a replicable applied trans-scalar methodology for detailed GI design scenarios, developed through the EU-funded LIFE+ A_GreeNet project to bridge the theory–practice gap and enable pilot implementations in multiple Italian mid-Adriatic coastal municipalities. The research details a comprehensive, multi-disciplinary, five-phase process applied to the Sant’Antonio district of San Benedetto del Tronto—a dense, trafficked urban area projected to face “extremely strong heat stress” by 2050. Design interventions included spatial optimization, strategic species replacement, the creation of vegetated bioretention basins, and systematic pavement de-sealing. The application of the model demonstrated significant improvements: a substantial increase in permeable surface area (+194%), a measurable reduction in the UTCI index (average ENVI-MET simulated reduction of 1.17 °C by 2030), and a series of benefits resulting from increased green space and enhanced meteorological water management. This research offers local authorities a tangible model to accelerate climate-adaptive solutions, showing how precise GI design creates resilient, comfortable, and human-centered urban spaces.

Mitigating the Urban Heat Island (UHI) effect is a critical challenge for contemporary urban design, impacting thermal comfort and public space usability. Effective mitigation requires understanding human flow dynamics within Local Climate Zones (LCZ), which define urban microclimates. Current analyses are often limited by static methodologies and fragmented datasets. This study introduces City Rhythm, an interactive web-based platform that enables dynamic (hourly/weekly) analysis of inferred human presence, LCZ classification and UHI risk. The platform simultaneously visualises spatiotemporal patterns, allowing users to overlay modelled Presence Points with LCZ and UHI maps, correlating them with inferred demographic and interest data. For example, it can identify peaks in vulnerable populations, like the elderly, in compact LCZ areas during high-risk UHI periods. City Rhythm innovatively explores human-environment interactions through multi-source data integration and dynamic modelling, identifying critical areas of high human presence and UHI risk, analysing user characteristics and providing data-driven strategies for UHI mitigation and enhanced thermal comfort.

This paper is proposed to investigate procedures which can deal with graphic formalize of numeric data relating to climatic and environmental conditions. In a scientific domain characterised by prevalence of mathematical models and statistical surveys, the possibility of making images as such becomes an additional tool for morphological research of architectural solutions influenced by environmental conditions. This methodology, along with new augmented reality technology, actually, promotes new way of dealing with the project immediately highlighting defects and weaknesses: as architectural pre-visualization has always been the architect’s domain, today, pre-visualization of environmental data becomes a useful tool for design.