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This article delves into the participatory aspects of the implementation of nature-based solutions (NbS) in the Global South. It examines the practices of community engagement in several projects conducted in informal settlements and how they relate to project visions. Building on previous work on community engagement for urban upgrading projects, we examine the relationship between the methods used to engage communities and the goals that guide the design and implementation of NbS. In doing so, we explore engagement practices that can support the emergence of transformative approaches in historically disadvantaged areas. We discuss how the degree of participation offered by different methods, such as citizen science and serious games, can substantially influence the outcomes of NbS projects by making them more integrated and site-specific. We conclude by discussing how the transformative implementation of NbS entails a multi-stakeholder proactive approach that is capable of supporting changes in the socio-ecological systems. 

The WUDAPT (World Urban Database and Access Portal Tools project goal is to capture consistent information on urban form and function for cities worldwide that can support urban weather, climate, hydrology and air quality modeling. These data are provided as urban canopy parameters (UCPs) as used by weather, climate and air quality models to simulate the effects of urban surfaces on the overlying atmosphere. Information is stored with different levels of detail (LOD). With higher LOD greater spatial precision is provided. At the lowest LOD, Local Climate Zones (LCZ) with nominal UCP ranges is provided (order 100 m or more). To describe the spatial heterogeneity present in cities with great specificity at different urban scales we introduce the Digital Synthetic City (DSC) tool to generate UCPs at any desired scale meeting the fit-for-purpose goal of WUDAPT. 3D building and road elements of entire city landscapes are simulated based on readily available data. Comparisons with real-world urban data are very encouraging. It is customized (C-DSC) to incorporate each city's unique building morphologies based on unique types, variations and spatial distribution of building typologies, architecture features, construction materials and distribution of green and pervious surfaces. The C-DSC uses crowdsourcing methods and sampling within city Testbeds from around the world. UCP data can be computed from synthetic images at selected grid sizes and stored such that the coded string provides UCP values for individual grid cells.