Summary

Since 2019, Open Geospatial Consortium (OGC) has invested in geospatial data and technology pilots to advance in the areas of Climate Resilience and Disasters. The Open Geospatial Consortium is an international voluntary consensus standards organization for geospatial content and location-based services, sensor web and Internet of Things, GIS data processing and data sharing. 

For the 2024 iteration, the Climate and Disaster Resilience Pilot 2024 (CDRP24) is focused on delivering impacts. These impacts are delivered via interoperable geospatial technologies and standards. All of which is to help combat climate and disasters. CDRP24 consists of individual threads that each work towards specific end-user, stakeholder, and technical goals that advance our climate and/or disaster understanding and readiness while also seeding collaboration between these two related domains. One of the components is seeking guidance on Generative AI in Disaster Management. Xentity is requested to provide an engineering report on targeted areas GenAI can augment Wildland Fire Management Data challenges.

Problem and Solution

The integration of Generative AI (GenAI) into wildland fire (WF) management presents a transformative opportunity to enhance preparedness, response, and recovery efforts. In this report, we will delve into the challenges faced by the WF community. Also, how the adoption of GenAI can mitigate or enhance these challenges. We’ll explore the potential benefits of GenAI within the National Incident Management System (NIMS) structure and provide recommendations for its adoption.

Generative AI is in its early stages and evolving rapidly, with challenges such as error management and prompt generation persisting. Moreover, adoption within the WF community may face hurdles due to rapid technological changes, legislation, and trust issues. Data augmentation and maintenance, along with ethical considerations, pose additional challenges, requiring a focus on MLOps and data governance. To address these challenges, a structured approach to GenAI adoption within the WF community involves aligning capabilities with the NIMS phases, ensuring targeted AI solutions for core stakeholders. Appendices provide core data needs, reference models, potential data sources, and field tools, ensuring a comprehensive approach to GenAI implementation. The conceptual solution will also tie into known US data sources, systems, reference models, and candidate GenAI tools.

Outcome and Benefit

The adoption of Generative AI within the WF community promises significant benefits. Its creativity and personalization abilities enable detailed fire behavior visualizations, optimizing resource allocation and response strategies. Adaptability and problem-solving skills aid in anticipating fire spread and behavior, minimizing damage. Emotional intelligence fosters empathetic interactions within firefighting teams, while multi-modal understanding integrates real-time geospatial data for comprehensive assessments. Ultimately, the integration of GenAI promises to revolutionize WF management, enhancing resilience and effectiveness in combating wildfires.