Arantes, Tassia Borges

Belchior, Isabela Braga

de Carvalho, Luis Marcelo Tavares

Gomes, Samantha Ramos

Motta, Marcelo Souza

Pereira, Eveline Aparecida

English

Portal de Revistas do ICMBio (Instituto Chico Mendes de Conservação da Biodiversidade)

UAV use for prescribed after-burn 
Biodiversidade Brasileira, 10(1): 71, 2020 Instituto Chico Mendes de Conservação da Biodiversidade 
 
 
71 
 
UAV use for prescribed after-burn mapping in Itatiaia National 
Park 
 
 
Isabela Braga Belchior1*, Luis Marcelo Tavares de Carvalho1, Samantha Ramos Gomes1, 
Tassia Borges Arantes1, Eveline Aparecida Pereira1, Marcelo Souza Motta2 
 
 
1 Universidade Federal de Lavras (UFLA), Lavras, Brasil 
2Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio), Parque Nacional do Itatiaia, Brasil 
*e-mail: isabela_bbelchior@hotmail.com  
 
 
 
 
ABSTRACT – This research was conducted in the Campos de Altitude located in Itatiaia 
National Park (INP). The vegetation is composed of grass and shrub strata characteristic of 
this type of phytophysiognomy, with the presence of endemic species of the area. 
Historically, since it is an area with the highest concentration of major fires, as of 2017, the 
conservation unit performs management actions aimed at increasing the knowledge of the 
ecological role of fire in the Campos de Altitude. The aim of this study was to perform a 
detailed classification of the scar left in the soil after prescribed burning, evaluating the 
effectiveness of the burning. The images were obtained on March 31, 2017, after two days 
of the prescribed burn, using an RGB sensor coupled to an unmanned aerial vehicle (UAV). 
After processing and orthomosaic generation, an image of the entire area with 8 cm of 
spatial resolution was obtained. Orthomosaic classification was made by object-based 
analysis. The algorithm used for segmentation was edge-based segmentation, the defined 
parameters were scale and merge, with values of 60 and 80, respectively. The land cover 
classes used in the classification were: vegetation, burnt vegetation, rocky outcrops, and 
water. The classification algorithm used was the Support Vector Machine (SVM). 
Accuracy was assessed using a confusion matrix and Kappa index. The SVM algorithm 
was found to be effective in the classification of high-spatial-resolution images, with an 
overall accuracy of 94.5% and a Kappa index of 0.92. For the burnt vegetation class, the 
user’s and producer’s accuracy was 87.9% and 94%, respectively. The mapping indicated 
that the prescribed burning was effective, achieving its objectives (reduction of 
combustible material and fragmentation of it in the landscape, in an area susceptible to 
fire). It was also observed that because it is a fire characterized by low intensity, an area of 
arboreal vegetation and areas of swamps within the area were not affected by fire. 
 
Keywords: prescribed burning, Support Vector Machine, classification, INP 
 


UAV use for prescribed after-burn mapping in Itatiaia National Park

https://www.icmbio.gov.br/revistaeletronica/index.php/BioBR/article/download/1558/1069

UAV use for prescribed after-burn mapping in Itatiaia National Park

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