Inferência geográfica para delimitação de corredores ecológicos: um estudo de caso para a Mata Atlântica do município de Tibau do Sul/RN

The Atlantic Forest biome occupies much of the Atlantic coast of Brazil, in addition to portions of Paraguay and Argentina. Due mainly to its biodiversity which falls in the group of global hotspots, i.e., areas that have high priority for conservation. Although currently there are some available devices that assist in their protection in the course of the history of occupation and exploitation of the Brazilian territory, this biome has gone, and is still going through, an intense process of devastation, caused mainly by the pressure from economic activities, culminating in a significant reduction of its area and consequent fragmentation of the landscape, which brings with hosts a series of problems at various scales and aspects. As in most municipalities included in the reach area of the biome, the situation of forest fragmentation in Tibau do Sul / RN is quite critical, reflecting on a truly diverse landscape with broad typology of land uses. Among the alternatives aimed at the conservation of this biome include the creation of protected areas and the creation of ecological corridors, the latter being more efficient by connecting the remaining forests, increasing landscape connectivity, providing significant gains in relation to biodiversity. However, a major problem on implementation of Ecological Corridors projects is related to the selection of areas for this purpose, in this sense Geography can provide important contributions through the integrated study of landscape in the light of the geosystemic approach and the use of Geographical Information System (GIS) in order to permit assessment of reality having as a base the integration of ecological, biological and man-made aspects. Thus, this research aims to indicate potential areas and propose scenarios delimitation of Ecological Corridors in the municipality of Tibau do Sul / RN through Geographic Inference techniques in GIS platform. Therefore, the methodology adopted is based on the Geosystemic approach. From these elements were created 4 models to indicate potential areas for implementation of Ecological Corridors from the environmental perspective (potential erosion), socioeconomic (cover and land prices), legislative (areas protected by environmental legislation) and integrated (combination of environmental factors, socioeconomic and legislative), which in turn served as a basis for proposing scenarios aimed at this purpose. The results showed that all models can be quite useful in indicating potential areas for the establishment of ecological corridors, especially when based on an integrated approach between environmental and anthropogenic. The Corridors delimitation proposes shown may perform duties beyond the establishment of connectivity between fragments, since they also may have usefulness in controlling erosion and protecting fragile environments. Among the models developed, the integrated constituted itself as the best option because it enabled the interconnection of a larger number of fragments from a better use of the potentialities present in the landscape

Inferência fuzzy para o problema de corte de estoque com sobras aproveitáveis de material

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Abordagens freqüentista e bayesiana para avaliação genética de bovinos da raça Canchim para características de crescimento

This study aimed to: a) to compare the covariance components obtained by Restricted Maximum Likelihood (REML) and by bayesian inference (BI): b) to run genetic evaluations for weights of Canchim cattle measured at weaning (W240) and at eighteen months of age (W550), adjusted or not to 240 and 550 days of age, respectively, using the mixed model methodology with covariance components obtained by REML or by BI; and c) to compare selection decisions from genetic evaluations using observed or adjusted weights and by REML or BI. Covariance components, heritabilities and genetic correlation for W240 and W550 were estimated and the predicted breeding values were used to select 10% and 50% of the best bulls and cows, respectively. The covariance components obtained by REML were smaller than the a posteriori means obtained by Bl. Selected animals from both procedures were not the same, probably because the covariance components and genetic parameters were different. The inclusion of age of animal at weighing as a covariate in the statistical model fitted by BI did not change the selected bulls and cows.

Segmentação de dados de perfilamento a laser em áreas urbanas utilizando uma abordagem Bayesiana

In this paper is presented a region-based methodology for Digital Elevation Model segmentation obtained from laser scanning data. The methodology is based on two sequential techniques, i.e., a recursive splitting technique using the quad tree structure followed by a region merging technique using the Markov Random Field model. The recursive splitting technique starts splitting the Digital Elevation Model into homogeneous regions. However, due to slight height differences in the Digital Elevation Model, region fragmentation can be relatively high. In order to minimize the fragmentation, a region merging technique based on the Markov Random Field model is applied to the previously segmented data. The resulting regions are firstly structured by using the so-called Region Adjacency Graph. Each node of the Region Adjacency Graph represents a region of the Digital Elevation Model segmented and two nodes have connectivity between them if corresponding regions share a common boundary. Next it is assumed that the random variable related to each node, follows the Markov Random Field model. This hypothesis allows the derivation of the posteriori probability distribution function whose solution is obtained by the Maximum a Posteriori estimation. Regions presenting high probability of similarity are merged. Experiments carried out with laser scanning data showed that the methodology allows to separate the objects in the Digital Elevation Model with a low amount of fragmentation.

Modelos estocásticos com heterocedasticidade: Uma abordagem Bayesiana para os retornos do Ibovespa

Current research compares the Bayesian estimates obtained for the parameters of processes of ARCH family with normal and Student's t distributions for the conditional distribution of the return series. A non-informative prior distribution was adopted and a reparameterization of models under analysis was taken into account to map parameters' space into real space. The procedure adopts a normal prior distribution for the transformed parameters. The posterior summaries were obtained by Monte Carlo Markov Chain (MCMC) simulation methods. The methodology was evaluated by a series of Bovespa Index returns and the predictive ordinate criterion was employed to select the best adjustment model to the data. Results show that, as a rule, the proposed Bayesian approach provides satisfactory estimates and that the GARCH process with Student's t distribution adjusted better to the data.

Inferência espacial para mapeamento de macrófitas submersas: estudo de caso

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Classificação da curvatura de vertentes em perfil via Thin Plate Spline e Inferência Fuzzy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Inferência espacial de clorofila a por redes neurais artificiais aplicadas a imagens multiespectrais e medidas tomadas in situ

Pós-graduação em Ciências Cartográficas - FCT

Inferência espacial de cianobactérias a partir da fluorescência in vivo do pigmento ficocianina

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação de um sistema de Inferência Fuzzy de suporte à decisão para estimação de valores de ações cotadas na Bolsa de Valores de São Paulo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise Bayesiana para a distribuição Exponencial-Logarítmica

Pós-graduação em Matematica Aplicada e Computacional - FCT

Análise clássica e bayesiana do modelo Weibull modificado generalizado

Pós-graduação em Matematica Aplicada e Computacional - FCT

Una aproximación bayesiana a la medición de la vulnerabilidad poblacional a desastres naturales: estudio de caso para el Estado Plurinacional de Bolivia

En este artículo se explica el empleo de un enfoque bayesiano para medir la vulnerabilidad de una población a desastres naturales utilizando información climática, censal y administrativa. La aproximación bayesiana permite clasificar las regiones de acuerdo con su vulnerabilidad e identificar los factores físicos y socioeconómicos que hacen que una población sea más o menos vulnerable a una amenaza específica. Estos resultados son útiles para formular políticas de prevención de riesgos focalizadas en las regiones más vulnerables y en función de las características socioeconómicas más importantes de cada población. Se presenta un estudio de caso de la vulnerabilidad poblacional a sequías e inundaciones en el Estado Plurinacional de Bolivia.

Desenvolvimento de método para inferência de características físicas da água associadas às variações espectrais. Caso de Estudo: Reservatório de Itupararanga/SP

Pós-graduação em Ciências Cartográficas - FCT

Estimação da densidade de solos utilizando sistemas de inferência fuzzy

Pós-graduação em Agronomia (Energia na Agricultura) - FCA