Many residents in the Asia-Pacific region suffer direct and indirect damage due to increased fires exacerbated by greenhouse gas-induced warming. Fires causing devastation to forests, agriculture, and habitats, also lead to premature mortality due to deteriorating air quality, biodiversity loss, and accelerated climate change due to carbon dioxide emissions. This project proposes the creation of fire risk maps and projections on seasonal to decadal timescales, utilizing datasets from remote sensing, meteorology, environment, and socio-economics. Machine learning and artificial intelligence techniques will be employed to quantify regional variations in fire activity characteristics, including ignition, spread, duration, and intensity. Understanding the sensitivity of each fire-related component on fire activity will provide insights into regional fire systems and identify key contributors for future fire prevention. The project will also incorporate fire parameters into global climate model simulations to quantify additional carbon emissions due to fire-climate feedback. The outcomes of this project will contribute to a safer and more sustainable society in the Asia-Pacific region by aiding in policy-making against climate extremes, fire events, and carbon neutrality, thereby protecting properties, ecosystems, and reinforcing fire-related policies.
Project • CRRP2024-03MY-Kim