Abstract
Abstract. Large-scale mapping of the Brazilian Savanna (Cerrado) vegetation using remote sensing images is still a challenge due to the high spatial variability and spectral similarity of the different characteristic vegetation types (physiognomies). In this paper, we report on semantic segmentation of the three major groups of physiognomies in the Cerrado biome (Grasslands, Savannas and Forests) using a fully convolutional neural network approach. The study area, which covers a Brazilian conservation unit, was divided into three regions to enable testing the approach in regions that were not used in the training phase. A WorldView-2 image was used in cross validation experiments, in which the average overall accuracy achieved with the pixel-wise classifications was 87.0%. The F-1 score values obtained with the approach for the classes Grassland, Savanna and Forest were of 0.81, 0.90 and 0.88, respectively. Visual assessment of the semantic segmentation outcomes was also performed and confirmed the quality of the results. It was observed that the confusion among classes occurs mainly in transition areas, where there are adjacent physiognomies if a scale of increasing density is considered, which agrees with previous studies on natural vegetation mapping for the Cerrado biome.
Highlights
The Brazilian Savanna, known as Cerrado, is the second largest Brazilian biome, covering an area of approximately two million km2, which amounts to 24% of the Brazilian territory
The average Overall Accuracy (OA), considering the semantic segmentation obtained in all test experiments, was 87.0%
Even though we are dealing with three classes for Savannas and Grasslands could be divided into several types of physiognomies in the Brasília National Park (BNP), according to the classification system proposed by Ribeiro and Walter (2008)
Summary
The Brazilian Savanna, known as Cerrado, is the second largest Brazilian biome, covering an area of approximately two million km, which amounts to 24% of the Brazilian territory. The water resources of this biome feed the three largest watersheds in South America: the Amazon, Prata and São Francisco watersheds. The Cerrado biome is considered one of the 35 global hotspots for biodiversity conservation (Mittermeier et al, 2011), with a flora containing more than 12,000 species, of which 40% are endemic. Only 8.6% of the Cerrado natural vegetation belongs to Conservation Units, i.e., specific regions established to protect biodiversity, water bodies and other environmental resources (MMA, 2010). Accurate mapping of Cerrado vegetation is essential for assessing biodiversity, improving Carbon stock estimation within the biome and guiding conservation policies
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