Abstract
The aim of this study was to evaluate the environmental quality of the Atlantic coast restinga, in south Brazil, using red, green and blue (RGB) drone images obtained in September of 2020 and 2021. The generated orthoimage was classified into different vegetation classes like herbaceous, shrubs and arboreal as well as other classes such as degraded and constructed areas. Classification was performed using the Random Forest algorithm, available from the Dzetsaka plugin for Quantum GIS. Of the total assessed area of restinga (289.17 ha), in 2020, 61.54% were conserved and 36.72% were degraded. In 2021 there was a decrease in conserved areas to 59.56%, and an increase in degraded areas to 38.85%. Regarding the sectors (1–8) evaluated in the two different years, sector 6 had the smallest preserved area of restinga (5.40 and 8.14 ha in 2020 and 2021, respectively), and sector 2 had the largest preservation area, with 44.07 ha in 2020 and 43.55 ha in 2021. Sectors 1,2,4, and 5 showed a reduction in conserved restinga areas (on average, 6.75%). An increase in conserved areas was observed in sectors 6 and 7 (on average, 20.4%) and in sector 8 (2%). These results show the potential of using images obtained by drone, in multi-temporal analyses of fragile areas such as restingas, helping with protection and conservation measures for these ecosystems.
Keywords:
aerial monitoring; unmanned aerial vehicles; hotspots; conserving coastal vegetation
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