Perfil dos bolsistas PQ da área de Química baseado na Plataforma Lattes

The Lattes Platform, an information system maintained by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), is the main source of information on Brazilian researchers. This paper presents a scientific output profile of the CNPq Productivity Research Fellows in the Chemistry area based on the information extracted automatically from Lattes curricula in the 2002-2011 period using the language "LattesMiner". This paper also provides a comparison with the results of Santos et al. (2010). The findings confirmed that the majority of the researchers are male (67.9%), classified as category 2 (63.2%) and working in the Southeast region (60.7%).

Análise espacial e quimiométrica da distribuição de espécies metálicas em solos alagáveis e não alagáveis da Bacia do Médio Rio Negro, Amazônia

This study used chemometric tools and a Geographic Information System (GIS) to determine the influence of organic matter and anthropogenic activity on the distribution of metal species between two major communities of the Middle Negro River Basin-AM. Higher concentrations of metal species were determined in flooded regions. The chemometric analysis showed the affinity of organic matter for potentially toxic metals, indicating its selectivity. GIS spatial analysis has shown that proximity to urban areas is a variable that is likely to influence the pattern of concentration of organic matter, and consequently the distribution of metal species between flooded and non-flooded areas.

An analysis of the risk of cocoa moniliasis occurrence in Brazil as the result of climate change

The aim of this study was to evaluate the potential risk of moniliasis occurrence and the impacts of climate change on this disease in the coming decades, should this pathogen be introduced in Brazil. To this end, climate favorability maps were devised for the occurrence of moniliasis, both for the present and future time. The future scenarios (A2 and B2) focused on the decades of 2020, 2050 and 2080. These scenarios were obtained from six global climate models (GCMs) made available by the third assessment report of Intergovernmental Panel on Climate Change (IPCC). Currently, there are large areas with favorable climate conditions for moniliasis in Brazil, especially in regions at high risk of introduction of that pathogen. Considering the global warming scenarios provided by the IPCC, the potential risk of moniliasis occurrence in Brazil will be reduced. This decrease is predicted for both future scenarios, but will occur more sharply in scenario A2. However, there will still be areas with favorable climate conditions for the development of the disease, particularly in Brazil's main producing regions. Moreover, pathogen and host alike may undergo alterations due to climate change, which will affect the extent of their impacts on this pathosystem.

METHODOLOGY FOR AUTOMATICALLY DELIMITING PERMANENT PRESERVATION AREAS ALONG WATER COURSES - THE USE OF GIS IN THE HYDROLOGICAL BASIN OF THE SERGIPE RIVER, BRAZIL

ABSTRACT Permanent Preservation Areas (PPAs) along watercourses have been the focus of numerous studies, not only because of the fragility and ecological relevance of riverine vegetation, but also because of the inefficiency demonstrated in conforming to the legislation protecting it. One of the major difficulties encountered in terms of guaranteeing the effective conservation of these riverside areas is the absence of methodologies that can be used to define them rapidly and accurately without manually determining the widths of the rivers or assigning only uniform linear values for the entire watercourse. The present work sought to develop a spatial analysis methodology capable of automatically defining permanent preservation areas along watercourses using geographic information system (GIS) software. The present study was undertaken in the Sergipe River basin, "considering the river itself and its principal affluents. We used the database of the Digital Atlas of Hydrological Resources (SEMARH/SE), and the delimitations of the PPAs were performed using ArcGIS 10.1 and the XToolPro 9.0 extension. A total of 5,003.82 hectares of Permanent Preservation Areas were delimited along the margins of the rivers analyzed, with a margin of error of <1% in delimiting the widths of the rivers within the entire area considered. The methodology described here can be used to define PPAs efficiently, relatively rapidly, and with very small margins of error, thus representing a technological advance in terms of using GIS for land management.

Nova versão do sistema de avaliação de terras - SIAT

O SIAT é um sistema especialista para Avaliação de Terras derivado do MicroLEIS - Land Evaluation Information System desenvolvido na Espanha. Na primeira versão, as 12 variáveis foram adaptadas e ajustadas para condições tropicais, assim como a estrutura do programa e o banco de dados. Os testes de campo mostraram que os melhores resultados foram obtidos para escalas próximas de 1:100.000. Nesta segunda versão, os intervalos das variáveis foram redefinidos e uma interface de comunicação com o SIG IDRISI foi introduzida, permitindo a troca de dados entre os dois programas. Outra modificação importante foi a adoção de uma equação para calcular a erosividade no lugar de mapa apresentado no Manual do Usuário. Os testes de campo mostraram que o uso do SIAT é agora mais funcional, com melhor resolução, permitindo trabalhar com escalas em torno de 1:50.000, além de ser adaptável para todo o território brasileiro. A versão do SIAT pode ser obtida pelo endereço www.rc.unesp.br/igce/ceapla/biblioteca/softwares/siat.html.

Design and development of the architecture of an agricultural mobile robot

Parameters such as tolerance, scale and agility utilized in data sampling for using in Precision Agriculture required an expressive number of researches and development of techniques and instruments for automation. It is highlighted the employment of methodologies in remote sensing used in coupled to a Geographic Information System (GIS), adapted or developed for agricultural use. Aiming this, the application of Agricultural Mobile Robots is a strong tendency, mainly in the European Union, the USA and Japan. In Brazil, researches are necessary for the development of robotics platforms, serving as a basis for semi-autonomous and autonomous navigation systems. The aim of this work is to describe the project of an experimental platform for data acquisition in field for the study of the spatial variability and development of agricultural robotics technologies to operate in agricultural environments. The proposal is based on a systematization of scientific work to choose the design parameters utilized for the construction of the model. The kinematic study of the mechanical structure was made by the virtual prototyping process, based on modeling and simulating of the tension applied in frame, using the.

Cadastral maps of irrigated areas by center pivots in the State of Minas Gerais, using CBERS-2B/CCD satellite imaging

Medium-resolution satellite images have been widely used for the identification and quantification of irrigated areas by center pivot. These areas, which present predominantly circular forms, can be easily identified by visual analyses of these images. In addition to identifying and quantifying areas irrigated by center pivot, other information that is associated to these areas is fundamental for producing cadastral maps. The goal of this work was to generate cadastral mapping of areas irrigated by center pivots in the State of Minas Gerais, Brazil, with the purpose of supplying information on irrigated agriculture. Using the satellite CBERS2B/CCD, images were used to identify and quantify irrigated areas and then associate these areas with a database containing information about: irrigated area, perimeter, municipality, path row, basin in which the pivot is located, and the date of image acquisition.3,781 center pivots systems were identified. The smallest area irrigated was 4.6 hectares and the largest one was 192.6 hectares. The total estimated value of irrigated area was 254,875 hectares. The largest number of center pivots appeared in the municipalities of Unaí and Paracatu, with 495 and 459 systems, respectively. Cadastral mapping is a very useful tool to assist and enhance information on irrigated agriculture in the State of Minas Gerais.

Rainfall erosivity for the State of Rio de Janeiro estimated by artificial neural network

The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.

Comparison between hydrographically conditioned digital elevation models in the morphometric charaterization of watersheds

The aim of this study was to compare the hydrographically conditioned digital elevation models (HCDEMs) generated from data of VNIR (Visible Near Infrared) sensor of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), of SRTM (Shuttle Radar Topography Mission) and topographical maps from IBGE in a scale of 1:50,000, processed in the Geographical Information System (GIS), aiming the morphometric characterization of watersheds. It was taken as basis the Sub-basin of São Bartolomeu River, obtaining morphometric characteristics from HCDEMs. Root Mean Square Error (RMSE) and cross validation were the statistics indexes used to evaluate the quality of HCDEMs. The percentage differences in the morphometric parameters obtained from these three different data sets were less than 10%, except for the mean slope (21%). In general, it was observed a good agreement between HCDEMs generated from remote sensing data and IBGE maps. The result of HCDEM ASTER was slightly higher than that from HCDEM SRTM. The HCDEM ASTER was more accurate than the HCDEM SRTM in basins with high altitudes and rugged terrain, by presenting frequency altimetry nearest to HCDEM IBGE, considered standard in this study.

Analysis of land use and occupancy in permanent preservation areas according to the hydrography of Ribeirão Água Fria - Bofete, SP - Brazil

The use conflicts are determined by the inadequate occupations of the soil, as it is the case of soil occupation inside of permanent preservation areas. This study aimed to determine the classes of the soil use and if there are conflicts inside of permanent preservation areas along the drainage network of the Água Fria Stream watershed, located in Bofete city - São Paulo, Brazil. It locates geographically between the coordinates: 48°09'30" to 48°18'30" longitude WGr., 22°58'30" to 23°04'30" latitude S, with an area of 15242.84 ha. The map of soil use was elaborated through the interpretation directly in the computer screen of satellite digital image. In the orbital data, the study area is inserted in the quadrant A, of image TM/Landsat - 5, orbit 220, point 76, passage 9/8th/2007. The Geographical Information System used was CartaLinx. The conflict areas of the watershed were obtained from the crossing between the maps of soil use and of PPAs. The results allowed the conclusion that more than half of the area (51.09%) is occupied by pastures, reflex of sandy soils and low fertility. It was also verified that although almost half of the watershed is covered with some type of vegetation (48.78% of natural forest /reforestation), it has approximately a third of permanent preservation areas used inappropriately by pastures (88.15%), reforestation (10.42%) and exposed soil (1.43%), totaling 343.07ha of conflicting areas, in a total of 993.26 ha of PPAs.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Methodology for spatialization of intense rainfall equation parameters

The aim of this study was to generate maps of intense rainfall equation parameters using interpolated maximum intense rainfall data. The study area comprised Espírito Santo State, Brazil. A total of 59 intense rainfall equations were used to interpolate maximum intense rainfall, with a 1 x 1 km spatial resolution. Maximum intense rainfall was interpolated considering recurrence of 2; 5; 10; 20; 50 and 100 years, and duration of 10; 20; 30; 40; 50; 60; 120; 240; 360; 420; 660; 720; 900; 1,140; 1,380 and 1,440 minutes, resulting in 96 maps of maximum intense rainfall. The used interpolators were inverse distance weighting and ordinary kriging, for which significance level (p-value) and coefficient of determination (R²) were evaluated for the cross-validation data, choosing the method that presented better R² to generate maps. Finally, maps of maximum intense precipitation were used to estimate, cell by cell, the intense rainfall equation parameters. In comparison with literature data, the mean percentage error of estimated intense rainfall equations was 13.8%. Maps of spatialized parameters, obtained in this study, are of simple use; once they are georeferenced, they may be imported into any geographic information system to be used for a specific area of interest.

Identification, assessment and ordering of concepts for agro-energy planning and possibilities of spatial analysis

ABSTRACT The present study aims to present the main concepts of the sugarcane straw to energy planning. Throughout the study, the subject is contextualized highlighting broader aspects of sustainability, which is considered the main driver towards agro-energy modernization. Concerning sugarcane straw, we first evaluated its availability regarding technical and economic aspects, and then it summarized the straw production chain for energy supply purposes. As a proposal to support agro-energy planning, it is presented some spatial tools that have been barely used in the Brazilian energy planning context so far. Therefore, working on straw to electricity associated with supply chain basis, we developed a conceptual model to spatially assess this bioenergy system. Using the model proposed, it is described the whole supply chain at state level, which accounted the potential of a single mill to explore straw, as well as main costs associated with straw acquisition, investments on the straw recovery routes and electricity transmission. Bearing these concepts in mind, it is fully believed that spatial analysis can bring important information for agro-energy action plans.