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OGC Climate and Disaster Resilience Pilot 2024: D-123 Generative AI in Wildland Fire Management Engineering Report
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| Definitionskos:definition | As part of OGC Disasters and Climate Resilience Pilot IV (D123 — AI Advances of SDIs Report Section), this D-123 Generative AI in Wildland Fire (WF) Management Engineering Report focus was to assess the domain adaptation needed for Generative AI to support advancements in the wildland fire community as informed by user needs assessments as well as technical assessments of potential advances and efficiencies. The Wildland Fire community leverages data and advanced tools to enhance planning and operational decision-making, aiming to supplement rather than replace experiential knowledge and anecdotal evidence. GenAI, while early in its technical evolution, with a human-in-the-loop approach, offers transformative potential by enabling scalability in data processing beyond human capabilities. Exploring GenAI further, particularly in scenarios where significant efficiency gains are feasible, is imperative. Integrating GenAI into wildfire management necessitates a comprehensive strategy encompassing data, process, technical, and ethical considerations. This report explores the needed input, tools, challenges, and recommendations for next steps to implementing GenAI to support the Wildland Fire Management lifecycle. |
|---|---|
| Broaderbroader | http://www.opengis.net/def/doc-type/techpaper |
| http://purl.org/dc/terms/createdcreated | 2025-01-18 |
| Creatorcreator | Matt Tricomi, Kevin Hope |
| seeAlsoseeAlso | https://portal.ogc.org/files/?artifact_id=110241 |
| Statusstatus | valid |
| Notationnotation | 24-071 |
| Alternative LabelaltLabel | 24-071 |
| OGC Climate and Disaster Resilience Pilot 2024: D-123 Generative AI in Wildland Fire Management Engineering Report | |
| OGC document typedoctype | http://www.opengis.net/def/doc-type/techpaper |