Agriculture and forest: A sustainable strategy in the Brazilian Amazon.

Large-scale agriculture is increasing in anthropogenically modified areas in the Amazon Basin. Crops such as soybean, maize, oil palm, and others are being introduced to supply the world demand for food and energy. However, the current challenge is to enhance the sustainability of these areas by increasing efficiency of production chains and to improve environmental services. The Amazon Basin has experienced a paradigm shift away from the traditional slash-and-burn agricultural practices, which offers decision makers the opportunity to make innovative interventions to enhance the productivity in previously degraded areas by using trees to ecological advantage. This study describes a successful experiment integrating the production of soybean and paricá (Glycine max L. and Schizolobium amazonicum) based on previous research that indicated potential topoclimatic zones for planting paricá in the Brazilian state of Pará. This paper shows that a no-tillage system reduces the effects of drought compared to conventional tillage still used by many farmers in the region. The integrated system was implemented during the 2014/2015 season in 234.6 ha in the high-potential zone in the municipality of Ulianópolis, Pará. Both soybean and paricá were planted simultaneously. Paricá was planted in 5 m x 2 m inter-tree spacing totaling 228x103 trees per hectare and soybean, in 4 m x 100 m spacing, distributed in nine rows with a 0.45 m inter-row distance, occupying 80% of the area. The harvested soybean production was 3.4 t ha-1, higher than other soybean monocultures in eastern Pará. Paricá benefited from soybean fertilization in the first year: It exhibited rapid development in height (3.26 m) and average diameter (3.85 cm). Trees and crop rotation over the following years is six years for forest species and one year for each crop. Our results confirm there are alternatives to the current production systems able to diminish negative impacts resulting from monoculture. In addition, the system provided environmental services such as reduced soil erosion and increased carbon stock by soil cover with no-tillage soybean cultivation. The soybean cover contributes to increased paricá thermal regulation and lower forestry costs. We concluded that innovative interventions are important to show local farmers that it is possible to adapt an agroforest system to large-scale production, thus changing the Amazon.

Detecting outliers and asserting consistency in agriculture ground truth information by using temporal VI data from modis.

Collecting ground truth data is an important step to be accomplished before performing a supervised classification. However, its quality depends on human, financial and time ressources. It is then important to apply a validation process to assess the reliability of the acquired data. In this study, agricultural infomation was collected in the Brazilian Amazonian State of Mato Grosso in order to map crop expansion based on MODIS EVI temporal profiles. The field work was carried out through interviews for the years 2005-2006 and 2006-2007. This work presents a methodology to validate the training data quality and determine the optimal sample to be used according to the classifier employed. The technique is based on the detection of outlier pixels for each class and is carried out by computing Mahalanobis distances for each pixel. The higher the distance, the further the pixel is from the class centre. Preliminary observations through variation coefficent validate the efficiency of the technique to detect outliers. Then, various subsamples are defined by applying different thresholds to exclude outlier pixels from the classification process. The classification results prove the robustness of the Maximum Likelihood and Spectral Angle Mapper classifiers. Indeed, those classifiers were insensitive to outlier exclusion. On the contrary, the decision tree classifier showed better results when deleting 7.5% of pixels in the training data. The technique managed to detect outliers for all classes. In this study, few outliers were present in the training data, so that the classification quality was not deeply affected by the outliers.

Energy balances in sugar cane, coffee and natural vegetation in the northeastern side of the São Paulo state, Brazil

Under land and climate change scenarios, agriculture has experienced water competitions among other sectors in the São Paulo state, Brazil. On the one hand, in several occasions, in the northeastern side of this state, nowadays sugar-cane is expanding, while coffee plantations are losing space. On the other hand, both crops have replaced the natural vegetation composed by Savannah and Atlantic Coastal Forest species. Under this dynamic situation, geosciences are valuable tools for evaluating the large-scale energy and mass exchanges between these diffe rent agro-ecosystems and the lower atmosphere. For quantification of the energy balance components in these mixed agro-ecosystems, the bands 1 and 2 from the MODIS product MOD13Q1 we re used throughout SA FER (Surface Algorithm for Evapotranspiration Retrieving) algorithm, which was applied together with a net of 12 automatic weather stations, during the year 2015 in the main sugar cane and coffee growing regions, located at the no rtheastern side of the state. The fraction of the global solar radiation (R G ) transformed into net radiation (Rn) was 52% for sugar cane and 53% for both, coffee and natural vegetation. The respective annual fractions of Rn used as λ E were 0.68, 0.87 and 0.77, while for the sensible heat (H) fluxes they were 0.27, 0.07 and 0.16. From April to July, heat advection raised λ E values above Rn promoting negative H, however these effects were much and less strong in coffee and sugar cane crop s, respectively. The smallest daily Rn fraction for all agro-ecosystems was for the soil heat flux (G), with averages of 5%, 6% and 7% in sugar cane, coffee and natural vegetation. From the energy balance analyses, we could conclude that, sugar-cane crop presented lower annual water consumption than that for coffee crop , what can be seen as an advantage in situations of water scarcity. However, the replacement of natural vegetation by su gar cane can contribute for warming th e environment, while when this occur with coffee crop there was noticed co oling conditions. The large scale modeling satisfactory results confirm the suitability of using MODIS products togeth er with weather stations to study the energy balance components in mixed agro-ecosystems under land-use and climate change conditions.