The objective of this work was to identify the spectral bands, vegetation indices, and periods of the canola crop season in which the correlation between spectral data and biophysical indicators (total shoot dry matter and grain yield) is most significant. The experiment was carried out during the 2013 and 2014 crop seasons at Embrapa Trigo, in the state of Rio Grande do Sul, Brazil. A randomized complete block design was used, with four replicates, and the treatments consisted of five doses of nitrogen topdressing. Plant dry matter, grain yield, and phenology were measured. The canola spectral response was evaluated by measuring the canola canopy reflectance using a spectroradiometer, and, with this data, the SR, NDVI, EVI, SAVI, and GNDVI vegetation indices were determined. Pearson’s correlations between the spectral and biophysical variables of canola showed that the red (620 to 670 nm) and near-infrared (841 to 876 nm) bands were the best to estimate the dry matter. The vegetative period is the most indicated to obtain the most significant correlations for canola. All the used vegetation indices are adequate for estimating the dry matter and grain yield of canola.

The objective of this study was to characterize the variability of spectral reflectance and temporal profiles of vegetation indices associated with nitrogen fertilization, crop cycle periods, and weather conditions of the growing season in canola canopies in southern Brazil. An experiment was carried out during the 2013 and 2014 canola growing seasons at EMBRAPA Trigo, Passo Fundo, state of Rio Grande do Sul, Brazil. The experiment was conducted in a randomized block design with four replications. Five doses of nitrogen top dressing were used as treatments: 10, 20, 40, 80, and 160kg ha^-1. Measurements were obtained with the spectroradiometer positioned above the canopy, to construct spectral reflectance curves for canola and establish temporal profiles for several vegetation indices (SR, NDVI, EVI, SAVI, and GNDVI). In addition, data on shoot dry matter were obtained and phenological stages were determined. The spectral reflectance curves of canola were reported to change with canopy growth and development. Temporal profiles of vegetation indices showed two maximum peaks, one before flowering and other after flowering. The indices SR, NDVI, EVI, SAVI, and GNDVI were able to characterize changes in the canola canopy over time, as a function of phenological phases, weather conditions, and nitrogen fertilization, throughout the development cycle. Plant growth and development, variations in crop management, and environmental conditions affect the spectral response of canola.

The extension of the area occupied by the inter tussock stratum and tussock stratum in natural pastures is essential for the productive performance of grazing animals. Images obtained from unmanned remote sensors can provide useful information, especially because they have a high spatial resolution. Thus, this study evaluated the performance of the supervised adaptive classification applied to aerial images obtained from an onboard drone camera to map the area covered by tussocks in a natural pasture of the Pampa biome. The study was carried out in a natural pasture area managed since 1986 under different forage allowances, considering treatments of 8, 12, and 16 kg of dry matter per 100 kg live weight (% LW). An aerial image from September 2017, obtained with a Canon S100 camera onboard a drone at an altitude of 120 m, with a spatial resolution of 5 cm, was used. The random forest and support vector machine classifiers were tested associated with specific classification rules. False-color images showed considerable visual similarity in the large patterns of the vegetation distribution and the validation performed with independent samples when compared to the classified images. The tested classifiers were able to measure the area covered by the tussock stratum, which could be an indicator of the quality vegetation in a natural grassland of the Pampa biome.