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Forest fuel quantification in a typical Cerrado area is difficult due to the high costs and long field times associated with collecting data. In search of alternatives that facilitate data collection, indirect estimation has been studied, resulting in local equations for predicting the load based on easily obtainable variables. In this context, we sought to develop local equations to estimate the load of forest fuel, in a Cerrado area, in the Cantão Park State - Tocantins. As a function of variables measured in the field and digital variables from the processing of RGB digital images (Red, Green and Blue) acquired through aerial surveys. With the processing of digital images, the following variables were extracted: mean height in the digital model (hMDA) and point density in the threedimensional model (DPM). After the aerial survey, field sampling was carried out, collecting the following variables: mean height in the field (hc), number of individuals (Qti) and Total Fuel Material (MCT). Subsequently, equations were fitted, adopting the entire sample set. The model selection criterion was based on R²aj, Syx% and residual graph, in which adjusted coefficient of determination (R²aj) from 0.12 to 0.83 and residual standard error (Syx%) of 19.4 were obtained at 44%. It was observed that the use of control points performed by the MDA reduces the occurrence of errors, the correlations between the analyzed variables indicate the importance of considering multiple factors when performing analyzes and predictions in the study areas. [ABSTRACT FROM AUTHOR]

The quantification of fuel material in the Cerrado area is limited by the difficulty in obtaining data, the high costs and the high time spent in the field. In search of alternatives that facilitate the data acquisition, the use of RGB sensors stands out being able to be a useful and effective tool in quantifying the combustible material. In this context, the objective of this work was to evaluate the feasibility of using images from an airborne RGB sensor by a multirotor to estimate the combustible material by means of regression analysis. The fuel material was sampled from the area that was weighed in the field and dried in an oven. With the digital images processing, the height (htMDA) and the vegetation index (NGRDI) of the pixels covering the sample units were obtained, followed by a correlation analysis between the digital processing data and the combustible material. Subsequently, three regression models were adjusted, in which adjusted coefficient of determination (R2aj) was obtained from 0.39 to 0.80. The use of RGB sensors has potential for estimation of combustible material. When the htMDA and NGRDI variables are combined, values closer to the mid-range are obtained. [ABSTRACT FROM AUTHOR]