Within the overall aim of developing and deploying beyond state-of-the-art Environmental Intelligence for better investment in nature-based solutions to achieve a triple-win for Environment, Economy and Employment, ReSET has the following goals:
Integrate: To develop the conceptual underpinnings and framework to better integrate environmental and social science, local knowledge, advanced sensor research and artificial intelligence
Build: To build upon the group's existing state of the art spatial policy support systems to develop a dynamic, hardware and software spatial investment toolkit (ReSET-IT) for coupled social and environmental systems
Link: To link these technological developments with existing local and European protocols and legislation to ensure that the knowledge advances and tools best support plausible policy levers for implementation of green investment
Apply: To apply dynamic scenario analysis of the employment, environmental and economic impacts of a variety of sustainable development post-COVID green recovery pathways at DEMO sites throughout Europe
Learn and teach: To facilitate effective green investment strategy, planning and evaluation by a range of stakeholders
The first 18 months of ReSET focused on the integrate, build, and apply goals. The link and learn and teach goals dominated the second half of the project . We examined the ethical, data, and health and safety implications of the proposed research and developed the protocols to be adhered to in interactions with stakeholders, and in data collection, management and dissemination. We developed our understanding of the policy and regulatory landscape for green investment across Europe allowing refinement of demonstration sites, and associated investments in nature-based solutions (NBS) past, present and future. Much work went into the development of new FreeStation sensors, data loggers as well as hardware and software IoT monitoring functionality for deployment across the range of investment types and locations identified. The focus of the research is to provide evidence of what works, where. We developed 7 instrumented sites with more than 86 data loggers collecting more than 45 million data points and applied Spatial policy support systems (hundreds of layers) available for 4 demonstration sites. We processed ~16 TB of global satellite data processed for applications of WaterWorld and Co$tingNature at 10-30 m resolution anywhere globally and ~1TB of audioecology data for understanding impacts of interventions on biophony/biodiversity. We developed open designs for a new third generation of FreeStations including air pollution, river, soil carbon and habitat quality. We built enhanced WaterWorld and Co$tingNature spatial policy support systems and an enhanced Metronamica land use, agent and activity based social science modelling, and a host of other tools. We engaged stakeholders through a workshop programme, policy briefs for each demo, conferences, training workshops and public engagement.
We conclude that: Data is not useful unless it is accessible and decision-making ready (i.e. intelligence, not data);Integration of heterogeneous intelligence streams to support live nature-based investments is challenging but essential, and must include social as well as biophysical aspects; Stakeholders want simple metrics and outcomes, but the realities of NbS performance are complex and uncertain: intelligent simplification is needed; Policy is moving fast so EI needs to keep up; Utility, relevance, credibility, accessibility and cost are key to EI uptake and must be the primary drivers of EI design; Environment, employment, economy triple-wins are possible but must be designed in to investments from the start
