This deliverable provides an overview of the current urban greening and relevant data ecosystems across the six Urban ReLeaf pilot cities. Understanding these data ecosystems lays the groundwork to identify current and future opportunities for citizen-based observations to complement official data streams. The deliverable starts by examining the global and European vision in urban greening and sustainability and the critical importance of the open data ecosystem. It describes the current state of cities and the urgent need to cope with climate change and several phenomena, such as the Urban Heat Island (UHI) effect, and the degradation of the quality of air and life in urban environments. Furthermore, we explain the term “urban greening”, and the willingness of the wider public to contribute to this cause, while stressing the complexity to achieve this goal. Key drivers are global and European initiatives as well as research programmes. In this context, we briefly describe the goals of the most relevant flagships and initiatives of the Group on Earth Observation (GEO). Furthermore, being inspired by the Open Knowledge Foundation, we introduce the necessity of adopting the concepts of not only Open Data but also of Open Data Ecosystems, and, thus, accelerate the transformation of the existing ecosystem from its linear unsustainable shape to circular, where data assets will not “live only once” but simply will be a piece of the wider “data puzzle space”. As part of T3.1, ICCS, in collaboration with all the city partners, maps and synthesizes the existing data assets of each Urban ReLeaf pilot city, based on the Open Data Institute’s (ODI) Data Landscape Playbook (DLP) methodology. The DLP has four well-defined steps (referred to as ‘plays’) :(i) define the problem, (ii) map the data ecosystem (iii) assess the existing infrastructure, and (iv) assess the policy, regulation, and ethical context. For the first play, a customised 3-tier methodology was formulated to collect insights from Urban ReLeaf city partners and transform them into high-level scenarios, categorised into four use cases. In the subsequent plays of the DLP, key data asset characteristics were identified (i.e., data owners, data formats and interfaces, data location, update frequency, etc.). Finally, in the fourth play, we recorded information regarding the ethical content and the level of openness of each data source. We present our qualitative and quantitative analyses as well as mapping the formal and soft value exchanges, to identify citizen-powered observations to complement official data streams. In the final chapter, we attempted to expand the initially identified data ecosystem and present other open-access datasets that could be explored.