Using Landsat 8 image time series for crop mapping in a region of Cerrado, Brazil.

Abstract: The objective of this research is to classify agricultural land use in a region of the Cerrado (Brazilian Savanna) biome using a time series of Enhanced Vegetation Index (EVI) from Landsat 8 OLI. Phenological metrics extracted from EVI time series, a Random Forest algorithm and data mining techniques are used in the process of classification. The area of study is a region in the Cerrado in a region of the municipality of Casa Branca, São Paulo state, Brazil. The results are encouraging and demonstrate the potential of phenological parameters obtained from time series of OLI vegetation indices for agricultural land use classification

Identification of gaps in sugarcane plantations using UAV images.

The objective of this study is to present a methodology for the detection and quantification of gaps formed during planting or growing of sugarcane crops. The use of UAV images for precision agriculture is relevant because it brings new possibilities for improving crop's productivity by feeding the producer with highly accurate data about the crop status