Identification of Vegetation Areas Affected by Wildfires Using RGB Images Obtained by UAV: A Case Study in the Brazilian Cerrado
The Cerrado is Brazil’s second largest biome, covering continuous areas in several states. Covering approximately 23% of Brazil’s territory, the Cerrado biome connects with all the main biomes in South America, thus forming a major biological corridor. This biome is one of those that has suffered the most from the incidence of wildfires, leading to a progressive depletion of the region’s natural resources. The aim of this study was to evaluate the use of an Unmanned Aerial Vehicle (UAV) embedded with an RGB sensor to obtain high-resolution digital products that can be used to identify areas of the Brazilian Cerrado affected by wildfires. The study was carried out in a savannah biome area selecting a vegetation corridor with native vegetation free from anthropogenic influence. The following UAV surveys were carried out before and after a burning event. Once the orthomosaics of the area were available, the GLI, VARI, ExG and NGRDI vegetation indices were used to analyze the vegetation. The data indicate that the B band and the GLI and ExG indices are more suitable for environmental impact analysis in Cerrado areas affected by fires, providing a solid basis for environmental monitoring and management in scenarios of fire disturbance.
Authors
- Miguel Júlio Machado Guimarães (ORCID: https://orcid.org/0000-0002-5497-6442)
- Gian C. Carvalho
- Carlos Vitor Oliveira Alves (ORCID: https://orcid.org/0000-0001-8020-4385)
- Juliane Rafaele Alves Barros (ORCID: https://orcid.org/0000-0002-0408-0904)
- Marlon Gomes da Costa (ORCID: https://orcid.org/0000-0003-1419-1605)
- Anderson Santos da Silva (ORCID: https://orcid.org/0000-0002-2229-501X)
- Iug Lopes (ORCID: https://orcid.org/0000-0003-0592-4774)
- Inês Reis (ORCID: https://orcid.org/0000-0003-4570-7491)
- Denis Pereira Ribeiro (ORCID: https://orcid.org/0009-0003-0689-0753)
Institutions
- Universidade Estadual de Feira de Santana (BR)
- Instituto Federal de Educação, Ciência e Tecnologia Baiano (BR)
- Instituto Federal do Piauí (BR)
- Instituto Federal do Maranhão (BR)
Publication Details
- Journal
- Geomatics
- Published
- 2025-03-16
- DOI
- https://doi.org/10.3390/geomatics5010013
- Citations
- 3
- Primary Topic
- Remote Sensing and LiDAR Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.40