BUILDING COMMUNITY RESILIENCE THROUGH GEOSPATIAL INFORMATION DASHBOARDS

Abstract. This article discusses a dashboard toolkit designed at the Knowledge Exchange for Resilience at the Arizona State University to integrate and analyze multi-agency data offering many ways of visualizing big data representable, contextualizable, and intelligible to a non-expert target audience. We outline a community-driven approach to identify pressing resiliency issues and deploy dashboard tools on targeted areas for significant community benefit. Our research builds on the offerings of data science to aid community-focused decision support systems to enable evidence-based and real-time decision-making. We hypothesize that building community resilience in response to emerging challenges requires a combination of timely data at the local scale and easy-to-use decision support tools. This research particularly focuses on augmenting the capacity of communities through dashboard technologies to comprehend rapidly evolving issues and address them in a timely and efficient manner. Our work contributes to a rapidly growing research domain around geospatial data visualization technologies that are increasingly playing a vital role in the shaping of government policies, including resiliency planning and disaster response. This study argues that dashboards that are action-oriented, easy-to-use, and locally embedded within the community have much more potential to be used as a decision-support system. The findings indicate that community-based knowledge networks catalyzed and influenced by modern technologies might provide a model to negotiate the gaps between ecosystem-based and social-science-focused conceptualization of community resilience.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: BUILDING COMMUNITY RESILIENCE THROUGH GEOSPATIAL INFORMATION DASHBOARDS ; volume:XLVIII-4/W5-2022 ; year:2022 ; pages:151-157 ; extent:7 ; The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVIII-4/W5-2022 (2022), 151-157 (gesamt 7)

Klassifikation und Themen

• Klassifikation: Wirtschaft

Beteiligte, Orts- und Zeitangaben

• Urheber: Praharaj, S. ; Wentz, E.

Weitere Informationen

• DOI: 10.5194/isprs-archives-XLVIII-4-W5-2022-151-2022
• URN: urn:nbn:de:101:1-2022102005225699891259
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:35 MESZ