6. Conclusion

The work presented in this chapter represents incremental improvement in wildfire decision support by integrating information on suppression difficulty with information on demand for protection of important fire-susceptible assets. By summarizing tSDI within PODs, and further by summarizing area-adjusted tSDI values in different analysis units, we are able to pinpoint areas of high concern in relation to suppression opportunity and risk transmission. We identified a case study landscape where a high density of human development in areas with increased fire hazard presents significant forest and fire management challenges. More importantly, we were able to work with local managers to assimilate this information into ongoing assessment and planning processes. As of this writing, the layers we developed on tSDI, dWUI, and F2F are being incorporated into a geodatabase that will be delivered to the Arapaho and Roosevelt National Forests to facilitate landscape prioritization and support real-time fire incident response.

In summary, we developed techniques to study the opportunity and viability of conducting fire suppression to manage fire risks at high priority locations, and to facilitate targeted identification of those high priority areas. Results can help fire managers understand how and where fire management activities could be planned and implemented to mitigate fire threats. In this chapter, we demonstrated not only proof-of-concept, but also results that delivered actionable information to local fire managers. We aim to continue to improve techniques and relevance of decision support through additional science-management partnerships, and hope this chapter inspires other fire scientists to do the same.
