Assessment of the spread of forest fires in the Southwestern Amazon

• Grant number: 25/25555-2
• Support Opportunities: Scholarships in Brazil - Program to Stimulate Scientific Vocations
• Start date: January 11, 2026
• End date: February 20, 2026
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Sonaira Souza da Silva
• Grantee: Bianca Yumi Simote Ishikawa
• Host Institution: Centro Multidisciplinar. Universidade Federal do Acre (UFAC). Campus Floresta. Cruzeiro do Sul , SP, Brazil

Abstract

The Amazon rainforest is characterized as a humid tropical forest, covering approximately 6 million square kilometers, comprising the largest and most biodiverse tropical forest area on the planet. In years with extreme droughts, the Amazon has experienced intense forest fire events, such as in 1998, 2005, 2010, 2016, 2023, and 2024, causing significant biomass loss, reduced tree density, alterations in floristic structure, biodiversity decline, and contributing to global warming, among other factors. Gaps in knowledge about fire propagation in standing forests (undeforested forests) in tropical regions remain a challenge due to the difficulty in identifying fires and obtaining information in short periods of time for their assessment. Using data from the AcreQueimadas Project of the Laboratory of Geoprocessing Applied to the Environment (LabGAMA) at the Federal University of Acre, which performs remote sensing mapping distinguishing forest fires from agricultural burnings, it is possible to combine this data with satellite monitoring with lower temporal resolution, such as Sentinel-2 and Planet data (with imaging every 1 to 5 days), to understand the speed of fire propagation in the Amazon rainforest. This will extract important information to understand fire propagation in different forest types (fuel) and topography in the Southwestern Amazon. The expected results are the identification of patterns in fire behavior in terms of the speed of its propagation in different forest types and topography. If the objective is achieved, we will have important indicators for the construction of models and computational simulations that can assist in the development of strategies to combat and prevent forest fires in the Amazon.