Forest Carbon Projects Can Support Wildfire Risk Management

Wildfire risk management is an important element of high-quality forest carbon projects—and good forestry in general. Technological advancements and modeling have given forest managers the ability to spatially analyze risk and implement early detection and response systems. However, mitigating wildfire risk often requires considerable investment. Fortunately, forest carbon projects provide a means for forest owners and managers to fund these activities.

Improved wildfire detection technologies, artificial intelligence, machine learning, and satellite imagery enable the analysis of vast datasets to predict fire ignition, spread, and can be an essential tool for mitigating wildfires when paired with investments in forest management (1). Moreover, NASA’s Fire Information for Resource Management System (FIRMS), and satellite imagery from sources like the European Service Agency offer real-time data to enable rapid response when wildfires break out (2) . Several organizations are working tirelessly to support the stakeholder’s efforts in wildfire management and emergency response. For example, the University of Southern California is developing innovative fire prediction tools to improve these efforts (3). Specifically related to carbon markets, American Carbon Registry has updated its risk assessment tool by incorporating satellite imagery to calculate fire risk to individual carbon projects.

By integrating real-time fire risk data with advanced modeling and risk assessment tools, proactive forest management can more efficiently reduce fire risk (4). In a forest carbon project area, land managers (or forest carbon project proponents) can identify high-risk areas and implement targeted fuel treatments, which not only help preserve existing carbon stocks but, in some cases, can increase growth and ultimately lead to additional carbon storage and credit generation for the project. This approach enhances forest resilience while promoting overall ecosystem health.

However, to fully harness the potential of these technologies, increased investment, widespread adoption of proactive fire management, and stronger support for community-based programs are essential. Forest carbon projects can provide an additional revenue stream to implement these wildfire risk mitigations. 

References:

1. Andrianarivony, H. S., & Akhloufi, M. A. (2024). Machine Learning and Deep Learning for Wildfire Spread Prediction: A Review. Fire, 7(12), 482.
2. FIRMS, https://www.earthdata.nasa.gov/data/tools/firms
3. University of the Southern California, https://today.usc.edu/using-ai-to-predict-wildfires/
4. Alcasena, F.; Rodrigues, M.; Gelabert, P.; Ager, A.; Salis, M.; Ameztegui, A.; Cervera, T.; Vega-García, C. Fostering Carbon Credits to Finance Wildfire Risk Reduction Forest Management in Mediterranean Landscapes. Land 2021, 10, 1104. https://doi.org/10.3390/land10101104