Livestock activity occupies ~67% of the global area used for agricultural activity, being directly related to important issues for humanity such as food security and the need to mitigate greenhouse gas emissions - GHG. In Brazil, the sixth largest emitter of GHG, land use and land cover activity is the main source of emissions. Considering that most of the pastures in Brazil present some level of degradation, in these areas there is a great opportunity to mitigate GHG emissions. In this study, three important aspects of this land use class are analyzed: The influence of climatic seasonality on biomass and on the spectral response of pasture areas at different spatial scales; The potential of the Normalized Difference Vegetation Index (NDVI), obtained by remote sensing for the mapping of pasture quality, and analysis of spatial patterns in national scale; And estimates of carbon stock in soil and aboveground biomass of pastures in the Cerrado biome, using models based on ecosystem processes. We observed that annual mean and variation of biomass stocks varied with spatial scale, and there were no significant differences in these stocks during the dry and rainy seasons due to grazing management strategies. The NDVI had low potential to predict the biomass stock of pastures in the evaluated areas, on the other hand, the potential as an pasture vigor indicator was high, showing a significant linear relation with the living/dead biomass ratio, especially in non-degraded pastures. The temporal pattern of the NDVI varied depending on the quality of the pasture and the spatial scale analyzed, indicating that it is not possible to establish single thresholds to map the condition of pastures in large areas like the Brazilian territory. From the mapping of pasture quality, it was possible to analyze their spatiotemporal dynamics. In this analysis, we identified an improvement in the brazilian pasture quality, with the area of gain quality being 2.7 times larger than the area of lost quality. The results correspond to the patterns observed in the literature and to the incentives for the recovery of pastures through programs such as the ABC Plan. The modeling of the dynamics and estimates of carbon stocks in the pasture areas of the Cerrado biome using the Century model, with the parameters adjusted to simulate the conventional pasture management in the biome, confirmed the versatility and robustness of the model, being effective in estimate carbon stocks in this areas, adequately reproducing the characteristic spatial patterns of seasonal influence in the Cerrado biome. In this sense, we believe that the results achieved through this study can contribute to a better characterization and understanding of pastures in Brazil.

Spectral information obtained by satellite imagery is well related to agronomic variables and can be used to monitor sugarcane growth and their responses to changes in environmental conditions of cultivation in large areas. This study is aimed to establish relationships between orbital data in the spectral ranges of the thermal and active photosynthetic radiation of Landsat-8 satellite with data observed with the leaf area index field (LAI), plant height, number of green leaves, and leaf temperature in plots planted with sugarcane, CTC-04 genotype, in a production cycle in sugarcane plant stage in Santo Antônio de Goiás-GO in the 2013/14 crop year. The first study aimed to calibrate a model to measure the temporal variation of the sugarcane LAI from the Normalized Difference Vegetation Index (NDVI) obtained from satellite Landsat 8’s surface reflectance images. It was conducted and the correlation between the LAI collected in the field and the NDVI with and without application of atmospheric correction. The corrected model showed the best relationship with field data. The application of the spectral model was efficient to monitor LAI over a sugarcane plant cycle. The results suggest that the NDVI-LAI relationship may vary during the production cycle of sugarcane due to variations in growth, development, and environmental conditions. Spectral variable NDVI with atmospheric correction was highly correlated (R² = 0,83) with LAI but the relationship proved to be affected by the NDVI saturation point at high values of LAI observed in the field. The second study aimed to evaluate the applicability of surface temperature (LST) obtained from the thermal bands of the Landsat-8 in correlation with the leaf temperature of sugarcane, to establish relationships able to detect water stress remotely through the images, in the occurrence period of drought throughout the year production in rain fed crop in the Cerrado region. The results showed that LST, despite having low direct association with the leaf temperature, has the potential of monitoring water stress in sugarcane within the Cerrado region, since the simulation of the difference between LST and the air temperature accompanies the spread between the leaf temperature and the air, the dynamics of soil water balance and changes in crop growth rates that occur in response to water stress.

The changes in land-cover and land-use are among the main causes of a series of environmental, social, and economic impacts. In particular, the formation of artificial reservoirs, due to the construction of hydroelectric plants (HPP), has been the subject of scientific studies in the country, mainly due to the changes they cause to the environment. Specifically, the construction of the Luís Eduardo Magalhães HPP in 2001 (along the Tocantins River), in a context of large-scale constructions in the state of Tocantins, resulted in a large flooded area (~ 630 km²), significant changes in the landscape, and relocation of rural and urban populations. In this sense, this work aimed to evaluate and quantify, through various satellite datasets and land-cover and land-use mapping of the area under the influence of the reservoir of the Luís Eduardo Magalhães HPP (in the period before and after its implementation), changes in the landscape and associated biophysical parameters. At the landscape scale, the following surface parameters, derived from Terra-MODIS images, were evaluated seasonally: temperature, vegetation index, evapotranspiration, and albedo. The analysis of these data, in the spatial - temporal domains, involved three experimental models: a) considering the area of influence of the reservoir as a whole (equidistance of 30 km); b) analysis considering the equidistance or proximity to the reservoir (through buffers, latitudinal transects, and areas of interest); c) comparisons between the MODIS sensor results and the biophysical parameters obtained from Landsat images (transformed by the SEBAL algorithm). The results of our research show the potential of using remote sensing images in the study of variations of biophysical parameters. The implementation of the Luís Eduardo Magalhães HPP reservoir boosted the occupation of areas around it, especially: the São João irrigation project (irrigation from lake water), the increase in real estate speculation through the creation of new land subdivisions and closed condominiums with direct access to the lake, occupation of other areas due to the relocation of families (as in the case of the district of Luzimangues-Porto Nacional), and the creation of condominiums near the reservoir. Between 2000 and 2014, there was a 111% decrease in the Cerrado native vegetation (forest formations, grassland formations, open and dense Cerrado Strict Sensu physiognomies) and an increase of 66% in urban areas and 947% in the agricultural areas. It was also observed that almost half of the entire study area (42%) suffered some kind of alteration in the land cover. The changes observed in the local biophysical parameters were a direct result of the reservoir implantation and the State's occupation and development policies (such as soybean financing), which influenced the spatial configuration of the various land-cover classes and existing land use in the study area. As a result, a number of negative environmental / climatic impacts are already perceived in the area. Therefore, it is suggested to implement public policies regarding the systematic monitoring of biophysical parameters in the area, with a view to minimizing and mitigating more severe long-term environmental impacts.

This study aimed to evaluate the performance of an Unmanned Aerial Vehicle (UAV) used to analysis of cultivated pasture areas. This evaluation was based on the comparison between the products of Vegetation Index calculated by orthomosaics from photos acquired by a UAV and the Percentage of Green collected in the ground level. The UAV Vegetation Index was the Modified Photochemical Reflectance Index (MPRI). It was held also a comparison between the Vegetation Indexes obtained with the UAV and an orbital platform being these the MPRI and the Normalized Difference Vegetation Index (NDVI) respectively. The data were collected monthly between July and December 2014. For comparison between the Percentage of Green and the MPRI was used 25 samples distributed along of transect established in ground level into the pasture area. For comparison between MPRI and NDVI other 15 samples were distributed along of the pasture area. The Percentage of Green relied on vertical photos acquired in the ground level. The MPRI resulted from aerial surveys done by UAV’s model “TIRIBA” that used the Canon PowerShot S100 camera coupled. The orthomosaics from aerial photos acquired on aerial surveys were generated in the Agisoft PhotoScan to calculate the MPRI after. The NDVI was calculated from surface reflectance images acquired by Landsat-8 satellite. Has been observed that Percentage of Green and MPRI are correlated and the same to be observed for MPRI and NDVI. There is also relationship in behavior of these products over time so was possible to conclude that both products could provide the necessary information for the characterization of the development of pasture between July and December 2014. Both products – Percentage of Green, MPRI and NDVI – feature advantages and limitations: the Percentage of Green is most sensitive for the changes into the pasture because of their detail high level (spatial resolution) but doesn’t have the income that the MPRI/UAV has and not provide the analysis of the whole area being necessary use to sampling; the MPRI/UAV has a higher sensitivity to record of the behavior of pasture when compared to NDVI/Landsat-8 bus the gain in the area imaged by orbital platform should not be disregarded. The correlation between Percentage of Green and MPRI and between MPRI and NDVI also suggests that these products can be used in conjunction to perform the monitoring of pasture areas.