Growth and survival of Sclerolobium paniculatum vogel and the relationship between rainfall and the increment in diameter at different planting spacings.

Sclerolobium paniculatum Vogel is a species that has good potential for reclamation of degraded soils. The aim of the investigation was to evaluate the growth and survival of the species and the influence of rainfall on growth in diameter as a function of different spacings (4 m x 2 m, 4 m x 3 m, and 4 m x 4 m). The results indicate that the temporal analysis (period from November 2007 to August 2013) detected significant differences (p ? 0.05) in height between the 4 m x 2 m and 4 m x 4 m spacings, while no significant difference in diameter was found between the 4 m x 2 m and 4 m x 3 m spacings. However, the statistical differences did not persist when the data was analyzed at seven and half years old. Regarding survival, a significant difference was observed only between the 4 m x 4 m spacing and the others, with superiority to the former. A strong correlation was found between rainfall and the increment in diameter of individuals in the broader spacings (R = 0.80 in the 4 m x 3 m spacing and R = 0.77 in the 4 m x 4 m spacing), while in the denser spacing the correlation was moderate (R = 0.56 in the 4 m x 2 m spacing). Since the spacings adopted did not influence tree growth by the end of the period, the choice will depend on other factors such as survival and costs of implementation and forestry management. Plantations in regions with larger rainfall amplitude may benefit the productivity of the species.

Energy balance model applied to pasture experimental areas in São Paulo State, Brazil.

The Simple Algorithm for Evapotranspiration Retrieving (SAFER) was used to estimate biophysical parameters and theenergy balance components in two different pasture experimental areas, in the São Paulo state, Brazil. The experimentalpastures consist in six rotational (RGS) and three continuous grazing systems (CGS) paddocks. Landsat-8 images from2013 and 2015 dry and rainy seasons were used, as these presented similar hydrological cycle, with 1,600 mm and 1,613mm of annual precipitation, resulting in 19 cloud-free images. Bands 1 to 7 and thermal bands 10 and 11 were used withweather data from a station located nearthe experimental area. NDVI, biomass, evapotranspiration and latent heat flux(λE) temporal values statistically differ CGS from RGS areas. Grazing systems influences the energy partition and theseresults indicate that RGS benefits biomass production, evapotranspiration and the microclimate, due higher LE values.SAFER is a feasible tool to estimate biophysical parameters and energy balance components in pasture and has potentialto discriminate continuous and rotation grazing systems in a temporal analysis.

Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data.

Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.