Using Geotechnology to Estimate Annual Soil Loss Rate in the Brazilian Cerrado

Soil erosion is a serious environmental problem that has adversely affected the world’s food production through the reduction of land productivity and water availability. The present study estimated annual soil loss rate and its spatial distribution in the most important Brazil’s agricultural region, the Brazilian Cerrado, using Revised Soil Loss Equation (RUSLE) model into Geographic Information System (GIS) framework. For this purpose, the soil erosion annual rate was determined in function of RUSLE model factors: rainfall erosivity (R), soil erodibility (K), topography (LS), crop management (C) and supporting conservation practice (P). All factors were obtained from literature. They were processed and integrated into a GIS, resulting in a map of annual soil loss rate. The methodology applied showed acceptable precision and it was possible to identify the most susceptible areas to water erosion. The average estimated rate of soil loss for the entire Cerrado was 12.8 t∙ha−1∙yr−1. Large part of the Cerrado is under low soil loss zone corresponding to 79.91% of total surface area, while 15.70%, 3.74%, and 0.66% are under moderate, high, and very high, respectively. The average estimated rate of soil loss in areas used for silviculture was 52.1 t∙ha−1∙yr−1. In semi-perennial, perennial, and annual crops cultivation were 29.3, 23.9, and 9.8 t∙ha−1∙yr−1, respectively, while in the pasture was 13.3 t∙ha−1∙yr−1. Except for annual crops, all farm and silviculture areas showed average soil loss ranging from moderate to high rate. These results suggest that the implementation of more effective management techniques and conservation practices are necessary for the Cerrado to maintain and to improve land productivity by ensuring national and international food demands

Tracking the Connection between Brazilian Agricultural Diversity and Native Vegetation Change by a Machine Learning Approach.

ABSTRACT - In Brazil, agribusiness has a considerable role in the country?s GDP. Because of this, the State needs territorial planning to minimize the impacts on natural resources, especially in the Pantanal and Amazon biomes, where agribusiness has expanded. The lower the agricultural diversification, the lower the pattern of land use homogeneity, generally associated with agribusiness, especially when it occupies large areas with more technological productive units. This paper investigates the relationship between spatial diversification patterns and the dynamics of native vegetation in Brazil. We propose a feature engineering and clustering approach for 5570 Brazilian municipalities between 1999 and 2018. It was based on the unsupervised artificial neural network Self-Organizing Map (SOM) to divide the municipalities into homogeneous groups of agricultural products diversity trends. The results were compared with the change in vegetation area using data from the national land use-mapping project called Mapbiomas. The analysis allowed the identification of three different regimes of modification in native vegetation, particularly related to municipalities in Brazil?s Midwest and North regions, indicating substantial changes in the Cerrado and Amazon biomes

Classifying multiyear agricultural land use data from Mato Grosso using time-series MODIS vegetation index data.

MODIS 250-m NDVI and EVI datasets are now regularly used to classify regional-scale agricultural land-use practices in many different regions of the globe, especially in the state of Mato Grosso, Brazil, where rapid land-use change due to agricultural development has attracted considerable interest from researchers and policy makers. Variation exists in which MODIS datasets are used, how they are processed for analysis, and what ground reference data are used. Moreover, various and-use/land-cover classes are ultimately resolved, and as yet, crop-specific classifications (e.g. soy?corn vs. soy?cotton double crop) have not been reported in the literature, favoring instead generalized classes such as single vs. double crop. The objective of this study is to present a rigorous multiyear evaluation of the applicability of time-series MODIS 250-m VI data for crop classification in Mato Grosso, Brazil. This study shows progress toward more refined crop-specific classification, but some grouping of crop classes remains necessary. It employs a farm field polygon-based ground reference dataset that is unprecedented in spatial and temporal coverage for the state, consisting of 2003 annual field site samples representing 415 unique field sites and five crop years (2005-2009). This allows for creation of a dataset containing "best-case" or "pure" pixels, which we used to test class separability in a multiyear cross validation framework applied to boosted decision tree classifiers trained on MODIS data subjected to different pre-processing treatments. Reflecting the agricultural landscape of Mato Grosso as a whole, cropping practices represented in the ground reference dataset largely involved soybeans, and soy-based classes (primarily double crop "soy-commercial" and single crop "soy-cover") dominated the analysis along with cotton and pasture. With respect to the MODIS data treatments, the best results were obtained using date-ofacquisition interpolation of the 16-day composite VI time series and outlier point screening, for which five-year out-of-sample accuracies were consistently near or above 80% and Kappa values were above 0.60. It is evident that while much additional research is required to fully and reliably differentiate more specific crop classes, particular groupings of cropping strategies are separable and useful for a number of applications, including studies of agricultural intensification and extensification in this region of the world

Beyond protected areas:assessing the role of legal reserves and permanent preservation areas for conserving tropical forests in private properties in the eastern Brazilian Amazon

Native vegetation covers about 60% of the national territory of Brazil, with 40% under some form of public protected area (conservation units and indigenous lands) and the remaining 60% located in private areas or public lands with no clear designation. The protection of forests on private land is therefore a vital part of any overall conservation strategy. In Brazil, the conservation of forest on private lands is regulated by the Brazilian Environmental Law (Law N° 12.651, 25 March 2012), commonly known as the Forest Code, and focus on two main mechanisms: Legal Reserves (LR) and Permanent Preservation Areas (APP in Portuguese). The aim of this thesis is to advance our understanding of some of the key challenges and opportunities facing forest conservation and restoration in the Brazilian Amazon by assessing the LR and APPs on private lands. Focused on Pará, the thesis provides the first assessment of the total LR deficit (LR that have been illegally deforested in the past) for any of Brazil´s Amazonian states as well as a uniquely comprehensive assessment of legal compliance with the protection and restoration of APPs, and critically examines implications for different actors and public policy. In Chapter 2 we found no evidence that riparian forests had been more effectively protected than non-riparian forests in the flagship municipality of Paragominas. Instead, deforestation was found to be comparatively higher inside riparian permanent preservation areas as recently as 2010, indicating widespread failure of private property owners to comply with environmental legislation. Moreover there was no evidence for higher levels of regeneration in deforested riparian zones than non-riparian zones, although property owners are obliged by law to restore such areas. A number of challenges limit efforts to improve the protection and restoration of riparian forests. These include limited awareness of environmental compliance requirements, better cartographic products and limitations in the technical capacity of the state and municipality governments. Considering the whole state of Pará, Chapter 3 shows that the total LR surplus (12.6 Mha) – based on the revised Forest Code – is more than five times the total area of deficit (2.3 Mha). Yet, of this total surplus, only 11% can be legally deforested (is in properties with >80% forest cover) and the remaining 89% is already protected by law but can be used (sold or rented) to compensate for areas that are under deficit. This analysis identifies that the majority of municipalities (111 out of 144) in the state could compensate their total LR deficit with surplus areas of LR within the same municipality, indicating compensation can always take place close to the source of the deficit. Maximizing the environmental benefits of achieving Forest Code compliance requires measures that go beyond the existing legal framework, including interventions to avoid further deforestation in places where it is still legal, compensate in close proximity to areas with legal reserve deficit and promote local restoration on degraded lands. Finally, Chapter 4 finds that, despite riparian APPs being mostly covered by forest in the state of Pará (63%), the area required to be restored by law (1 Mha) accounts for only about one-third of the deforested area that does not need to be restored following the 2012 revision of the Forest Code. This suggests that some important catchments in Pará may not recover fully functioning hydrological and ecological services, as around 2.7 Mha of consolidated APP are likely to remain deforested. We also demonstrated how coarse-scale mapping data consistently underestimates the extent of different APP areas, and thus the scale of the challenge presented by the compliance requirements of the forest code. In improving our understanding of the requirements and potential for forest compensation and restoration, through the mechanisms of APP and LR, offers a key advance for achieving environmental compliance in Pará and elsewhere in the Brazilian Amazon and the wider tropics

Digital agriculture: research, development and innovation in production chains.

Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil

Digital agriculture: research, development and innovation in production chains.

Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil.Translated by Beverly Victoria Young and Karl Stephan Mokross