A study of habitat fragmentation in Southeastern Brazil using remote sensing and geographic information systems (GIS)

The purpose of this work was to study fragmentation of forest formations (mesophytic forest, riparian woodland and savannah vegetation (cerrado)) in a 15,774-ha study area located in the Municipal District of Botucatu in Southeastern Brazil (São Paulo State). A land use and land cover map was made from a color composition of a Landsat-5 thematic mapper (TM) image. The edge effect caused by habitat fragmentation was assessed by overlaying, on a geographic information system (GIS), the land use and land cover data with the spectral ratio. The degree of habitat fragmentation was analyzed by deriving: 1. mean patch area and perimeter; 2. patch number and density; 3. perimeter-area ratio, fractal dimension (D), and shape diversity index (SI); and 4. distance between patches and dispersion index (R). In addition, the following relationships were modeled: 1. distribution of natural vegetation patch sizes; 2. perimeter-area relationship and the number and area of natural vegetation patches; 3. edge effect caused by habitat fragmentation, the values of R indicated that savannah patches (R = 0.86) were aggregated while patches of natural vegetation as a whole (R = 1.02) were randomly dispersed in the landscape. There was a high frequency of small patches in the landscape whereas large patches were rare. In the perimeter-area relationship, there was no sign of scale distinction in the patch shapes, In the patch number-landscape area relationship, D, though apparently scale-dependent, tends to be constant as area increases. This phenomenon was correlated with the tendency to reach a constant density as the working scale was increased, on the edge effect analysis, the edge-center distance was properly estimated by a model in which the edge-center distance was considered a function of the to;al patch area and the SI. (C) 1997 Elsevier B.V. B.V.

Spatial Distribution of Seropositive Dogs to Leptospira spp. and Evaluation of Leptospirosis Risk Factors Using a Decision Tree

Background: Leptospirosis is an important zoonotic disease associated with poor areas of urban settings of developing countries and early diagnosis and prompt treatment may prevent disease. Although rodents are reportedly considered the main reservoirs of leptospirosis, dogs may develop the disease, may become asymptomatic carriers and may be used as sentinels for disease epidemiology. The use of Geographical Information Systems (GIS) combined with spatial analysis techniques allows the mapping of the disease and the identification and assessment of health risk factors. Besides the use of GIS and spatial analysis, the technique of data mining, decision tree, can provide a great potential to find a pattern in the behavior of the variables that determine the occurrence of leptospirosis. The objective of the present study was to apply Geographical Information Systems and data prospection (decision tree) to evaluate the risk factors for canine leptospirosis in an area of Curitiba, PR.Materials, Methods & Results: The present study was performed on the Vila Pantanal, a urban poor community in the city of Curitiba. A total of 287 dog blood samples were randomly obtained house-by-house in a two-day sampling on January 2010. In addition, a questionnaire was applied to owners at the time of sampling. Geographical coordinates related to each household of tested dog were obtained using a Global Positioning System (GPS) for mapping the spatial distribution of reagent and non-reagent dogs to leptospirosis. For the decision tree, risk factors included results of microagglutination test (MAT) from the serum of dogs, previous disease on the household, contact with rats or other dogs, dog breed, outdoors access, feeding, trash around house or backyard, open sewer proximity and flooding. A total of 189 samples (about 2/3 of overall samples) were randomly selected for the training file and consequent decision rules. The remained 98 samples were used for the testing file. The seroprevalence showed a pattern of spatial distribution that involved all the Pantanal area, without agglomeration of reagent animals. In relation to data mining, from 189 samples used in decision tree, a total of 165 (87.3%) animal samples were correctly classified, generating a Kappa index of 0.413. A total of 154 out of 159 (96.8%) samples were considered non-reagent and were correctly classified and only 5/159 (3.2%) were wrongly identified. on the other hand, only 11 (36.7%) reagent samples were correctly classified, with 19 (63.3%) samples failing diagnosis.Discussion: The spatial distribution that involved all the Pantanal area showed that all the animals in the area are at risk of contamination by Leptospira spp. Although most samples had been classified correctly by the decision tree, a degree of difficulty of separability related to seropositive animals was observed, with only 36.7% of the samples classified correctly. This can occur due to the fact of seronegative animals number is superior to the number of seropositive ones, taking the differences in the pattern of variable behavior. The data mining helped to evaluate the most important risk factors for leptospirosis in an urban poor community of Curitiba. The variables selected by decision tree reflected the important factors about the existence of the disease (default of sewer, presence of rats and rubbish and dogs with free access to street). The analyses showed the multifactorial character of the epidemiology of canine leptospirosis.

Análise multicritérios na definição de áreas prioritárias à conectividade entre fragmentos florestais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparação entre dois sistemas de informação geográfica (ARCGIS e GVSIG) na elaboração de um mapa de potencialidade para a silvicultura baseado em elementos do meio físico: a bacia do Paraíba do Sul (Porção Paulista)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geoprocessamento aplicado na distribuição espacial da capacidade do uso na microbacia do Córrego dos Rochas, Avaré (SP)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Extração automática de contornos de telhados de edifícios em um modelo digital de elevação, utilizando inferência Bayesiana e campos aleatórios de Markov

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ecologia molecular de fungos patogênicos onygenales em animais silvestres do interior do estado de São Paulo

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Variabilidade do índice de vegetação por diferença normalizada (NDVI) em áreas reflorestamento: floresta estadual Edmundo Navarro de Andrade (FEENA)/Rio Claro (SP)

Pós-graduação em Geociências e Meio Ambiente - IGCE

Zoneamento ecológico econômico do município de Altinópolis, SP

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Integração de modelos de localização a sistemas de informações geográficas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A CASE tool for the modeling of methods and information systems

MODSI is a multi-models tool for information systems modeling. A modeling process in MODSI can be driven according to three different approaches: informal, semi-formal and formal. The MODSI tool is therefore based on the linked usage of these three modeling approaches. It can be employed at two different levels: the meta-modeling of a method and the modeling of an information system.In this paper we start presenting different types of modeling by making an analysis of their particular features. Then, we introduce the meta-model defined in our tool, as well as the tool functional architecture. Finally, we describe and illustrate the various usage levels of this tool.

Carta de Aptidão para a implantação de rodovias e avaliação de alternativas de traçado com uso de geotecnologias

This study discuss the use of the geotechnologies to aid the planners on the terrain aptness definition for highways implantation and on the different trace evaluation to the extention of the Governador Carvalho Pinto highway, between Taubaté-SP and Aparecida do Norte-SP. Fratures on the area were mapping using Landsat ETM+, band Pan. In order to elaborate the phisical aptness chart for highway implantation was used the Analitical Hierarchy Process (AHP) operation, in on geographical information system (GIS). Using GIS were realized a ponderate middle with the soils, rocks, relief, slope, fractures and land use/cover maps. Using this physical aptness chart and joinning it with urban and restrict areas (that was inserted by the Boolean operation), were obtained a viability chart for highway implantation. Based on it were proposed three aleatory traces for the Carvalho Pinto highway. This traces were evaluated with the cross tabulation operation. The integration of the restrict areas, land use and phisical aptness in digital media can offer for the planners the cartography of the viability for the highway implantation. The evaliation of these three traces, based on the viability chart, can subsidyse the decision by the planners.

Usage of enterprise modeling processes and information systems design to forecast demand

Managing the great complexity of enterprise system, due to entities numbers, decision and process varieties involved to be controlled results in a very hard task because deals with the integration of its operations and its information systems. Moreover, the enterprises find themselves in a constant changing process, reacting in a dynamic and competitive environment where their business processes are constantly altered. The transformation of business processes into models allows to analyze and redefine them. Through computing tools usage it is possible to minimize the cost and risks of an enterprise integration design. This article claims for the necessity of modeling the processes in order to define more precisely the enterprise business requirements and the adequate usage of the modeling methodologies. Following these patterns, the paper concerns the process modeling relative to the domain of demand forecasting as a practical example. The domain of demand forecasting was built based on a theoretical review. The resulting models considered as reference model are transformed into information systems and have the aim to introduce a generic solution and be start point of better practical forecasting. The proposal is to promote the adequacy of the information system to the real needs of an enterprise in order to enable it to obtain and accompany better results, minimizing design errors, time, money and effort. The enterprise processes modeling are obtained with the usage of CIMOSA language and to the support information system it was used the UML language.

Geoprocessamento aplicado na distribuição espacial da capacidade de uso de uma microbacia

The present study aimed to show the spatial distribution of the Rochas watershed (Avaré-SP, Brazil) soil use capacity using the Idrisi geographical information system in order to contribute to a better territorial organization and the planning of the appropriate soil occupation. The obtained results using this methodology showed that most of the Rocha watershed areas are from the following groups: dystrophic yellow-red latosol (36.64%), eutroferric and distroferric red latosol (30.30%) with sandy texture. There was a predominance of areas with slope classes of 0-12%, plain to wavy relief (61.37% of the watershed area) showing that these areas are appropriate for annual culture plantations with wide use of machinery. Most of these areas were classified as class IV (73.79%) as to use capacity. In the studied area the following subclasses of land use capacity were found: IIe, s; IIIe; IVe; IVs; IVe,s; VIe and VIIe. Capacity subclasses IVe; IVe,s; IVs and Vie were the most significant because they are areas that can be used for agriculture but subject to severe soil impoverishment if there are no special care mainly for annual cultures. The Idrisi geographical information system was efficient to determine soil use capacity of the Rocha's watershed showing that the use of geoprocessing tools makes data analysis easier and faster, allowing digital data storage for future analysis uses mainly for territorial planning and environmental studies.

The effects of soil pollution and its relation with morbidity in shoreline areas

Soil and subsoil pollution is not only significant in terms of environmental loss, but also a matter of environmental and public health. Solid, liquid and gaseous residues are the major soil contamination agents. They originate from urban conglomerates and industrial areas in which it is impossible to emphasize the chemical, petrochemical and textile industry; thermoelectric, mining, and ironmaster activities. The contamination process can thus be defined as a compound addition to soil, from what qualitative and or quantitative manners can modify soil's natural characteristics and use, producing baneful and deteriorative effects on human health. Studies have shown that human exposition to high concentration of some heavy metals found on soil can cause serious health problems, such as pulmonary or kidney complications, liver and nervous system harm, allergy, and the chronic exposition that leads to death. The present study searches for the correlation among soil contamination, done through a geochemical baseline survey of an industrial contamination area on the shoreline of Sao Paulo state. The study will be conducted by spatial analysis using Geographical Information Systems for mapping and regression analysis. The used data are 123 soil samples of percentage concentration of heavy metals. They were sampled and spatially distributed by geostatistics methods. To verify if there is a relation between heavy metals soil pollution and morbidity an executed correlation and regression analysis will be done using the pollution registers as the independent variables and morbidity as dependable variables. It is expected, by the end of the study, to identify the areas relation between heavy metals soil pollution and morbidity, moreover to be able to provide assistance in terms of new methodologies that could facilitate soil pollution control programs and public health planning. © 2010 WIT Press.