One of the six research methods used by the Space Enabled research group is creating models of complex systems by drawing on techniques from systems engineering, social science, and earth science. One of the key ways we do this is through the Environment-Vulnerability-Decision-Technology (EVDT) Framework, a process for developing multi-disciplinary, interactive decision support systems (DSS) for a variety of sustainable development applications. This framework seeks to support the use of Earth Observation and socioeconomic data in a format usable by non-experts, while harnessing cloud computing, machine learning, economic analysis, complex systems modeling, and systems engineering. It is characterized by five basic elements: (1) the use of systems architecture & stakeholder analysis to identify needs and understand the context; (2) collaborative development of the DSS that continues stakeholder engagement past the initial systems architecting; (3) a concept of the sustainable development application as a complex socio-enviro-technical system, typically involving the Environment, Human Vulnerability and Societal Impact, Human Behavior and Decision-Making, and Technology Design; (4) an interactive decision-support system; and (5) A consideration towards modularity and re-use of DSS components in future applications.
In particular, the EVDT Framework draws from the fields of systems architecture (and other systems engineering techniques), GIS, collaborative planning, and remote observation, each of which have complementary aspects that can be brought to bear on development challenges, particularly those of relatively small spatial scales (municipalities to metropolitan regions) that tend to be underserved by major international development programs. Environmental models use physics-based simulations to estimate the behavior of natural features in the atmosphere, water, or vegetation. Human vulnerability and societal impact models estimate how people are impacted by environmental hazards, such as hurricanes, or ecosystems services, such as the benefits of forests, using physics-based simulations or economic regressions. Human decision-making models, which can be decentralized agent-based or centralized decision-logic, simulate the actions taken by humans in response to environmental features. The technology design model allows humans to explore options for technical systems (such as earth observation satellites) to improve awareness of the state of the environment. While significant benefit has come from addressing each domain individually in existing models, and yet more from considering certain groupings (such as the economic valuations that combine both decision-making and societal impact), capturing all four together in an integrated software model can enable us to overcome important challenges that lie at the intersections of these domains.
Over the past few years, the EVDT Framework has been used to develop DSSs for mangrove conservation in Brazil, flood resilience in Indonesia, invasive plant species management in Benin, cranberry bog renovation and wetland restoration in Massachusetts, and COVID-19 response in six major metropolitan areas around the world (for more information on the last of these, see the Vida Decision Support System project page). These projects involved both space and non-space stakeholders including the IPP (Rio de Janeiro’s municipal data agency), GGPEN (the Angolan space agency), MICITEC (Chile’s science ministry), the Universitas Diponegoro of Indonesia, and the Yurok tribe of modern day California, among others. Through these applications and collaborations, the EVDT framework has developed from a conceptual framing to a concrete process that is shown to be repeatable across geographic contexts. For more examples, see the publications page and this recent thesis.