Tracking and classifying Amazon fire events in near real time

Andela, Niels ORCID: https://orcid.org/0000-0002-8241-6143, Morton, Douglas C., Schroeder, Wilfrid, Chen, Yang, Brando, Paulo M. and Randerson, James T. 2022. Tracking and classifying Amazon fire events in near real time. Science Advances 8 (30) , eabd2713. 10.1126/sciadv.abd2713

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Abstract

Exceptional fire activity in 2019 sparked concern about Amazon forest conservation. However, the inability to rapidly separate satellite fire detections by fire type hampered fire suppression and assessment of ecosystem and air quality impacts. Here, we describe the development of a near–real-time approach for tracking contributions from deforestation, forest, agricultural, and savanna fires to burned area and emissions and apply the approach to the 2019 fire season in South America. Across the southern Amazon, 19,700 deforestation fire events accounted for 39% of all satellite active fire detections and the majority of fire carbon emissions (63%; 69 Tg C). Multiday fires accounted for 81% of burned area and 92% of carbon emissions from the Amazon, with many forest fires burning uncontrolled for weeks. Most fire detections from deforestation fires were correctly identified within 2 days (67%), highlighting the potential to improve situational awareness and management outcomes during fire emergencies.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Earth and Environmental Sciences
Publisher:	American Association for the Advancement of Science
ISSN:	2375-2548
Date of First Compliant Deposit:	31 March 2023
Date of Acceptance:	14 June 2022
Last Modified:	06 Jul 2023 16:42
URI:	https://orca.cardiff.ac.uk/id/eprint/158261

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