Publication

The Environment-Vulnerability-Decision-Technology Framework for Decision Support in Indonesia

Lombardo, Seamus, Steven Israel, Danielle Wood. "The Environment-Vulnerability-Decision-Technology Framework for Decision Support in Indonesia," IEEE Aerospace 2022, Big Sky, Montana, March 2022.

Abstract

Coastal flooding and land subsidence threaten the community of Pekalongan City, Indonesia. These environmental phenomena threaten coastal ecosystems, but also cause extensive economic damage and threaten agriculture and aquaculture industries. When addressing these environmental and socioeconomic challenges, local leaders are faced with the needs of multiple stakeholders as well as decisions on where and how to allocate limited resources to flood mitigation techniques (such as mangrove forest planting or human-made techniques such as sea walls). The coastal phenomena affecting Pekalongan City - such as flooding and land subsidence, as well as the effects these phenomena have on socioeconomic factors (such as agriculture, fisheries, and transportation) represent a complex system as defined in the aerospace System Engineering literature and are also challenging to the mental models of human decision-makers. This work employs Systems Architecture analysis to analyze options for how researchers from universities in the United States can help supplement the work of local leaders to improve coastal resilience in Pekalongan City. Systems Architecture Framework is well suited to this complex system and is employed to evaluate the Context (such as intersecting environmental and socioeconomic factors), analyze Stakeholders (which entails a complex network of local and national governments, NGOs, and universities), assess Stakeholder Needs and Objectives (which relate to economic stability, public health, and environmental restoration), and consider potential Functions and Forms (which could make use of the benefits of techniques from the aerospace field such as satellite remote sensing (SRS) data analyses and integrated modeling) to provide decision support for coastal resilience. This effort focuses on addressing the Function of aiding local decision makers in understanding environmental phenomena, related socioeconomic impacts, and potential policy options and technology investments by analyzing potential Forms for decision support. The results of this Systems Architecture analysis conclude that the intersecting sociotechnical factors of the complex system of coastal flooding in Pekalongan City necessitate an integrated modeling framework to support the decision making of local leaders. Researchers in the United States propose to use the Environment-Vulnerability-Decision-Technology (EVDT) integrated modeling framework as a form to address this function. EVDT considers the interactions between the Environment, Societal Impact, Human Decision-Making, and Technology Design to support decision-making. The EVDT framework is being applied to develop an accessible, Decision Support System (DSS) employing additional Forms of integrated modeling and SRS data analyses to support decision makers. The goal of applying EVDT and employing SRS data to develop this DSS is to aid leaders by helping them understand complex relationships between these disparate societal factors, adapt to changes within the community, and address the needs of multiple stakeholders. The EVDT framework is being utilized to develop a DSS that outputs descriptive and predictive models (which utilize inputs of both SRS data and local socioeconomic information). These models allow decision makers to examine historical data and explore the relationships between these interrelated societal factors under different simulated conditions to evaluate potential policies or technological investments. This work describes the System Architecture analysis and how EVDT is a Form well suited to address the Stakeholder Needs, Objectives, and Desired Outcomes resulting from this analysis. This work also provides a description of initial efforts to develop a DSS prototype informed by inputs from the System Architecture analysis and employing EVDT and SRS data analyses.

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