Monitoring the brazilian pasturelands: A new mapping approach based on the landsat 8 spectral and temporal domains

In a world marked by a rapid population expansion and an unprecedented increase in per capita income and consumption, sustainable food production is certainly the most pressing issue affecting mankind. Within this context, the brazilian pasturelands, the main land-use form in the country, constitute a particularly important asset as a land reserve, which, through improved land-use strategies and intensification, can meet food security goals and contribute to the mitigation of greenhouse gas emissions. In this study, we utilized the entire set of Landsat 8 images available for Brazil in 2015, from which dozens of seasonal metrics were derived, to produce, through objective criteria and automated classification strategies, a new pasture map for the country. Based on the Random Forest algorithm, individually modelled and applied to each one of the 380 Landsat scenes covering the Brazilian territory, our map showed an overall accuracy of 87%. Another result of this study was the thorough spatial and temporal assessment of Landsat 8 data availability in Brazil, which indicated that about 80% of the country had 12 or fewer observations free of clouds or cloud shadows in 2015.