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Spatial Analysis to Identify Urban Areas with Higher Potential for Social Investment

Journal of Geographic Information System 2017年第5期9卷 591-603页

作者： marcos roberto martines Rogério Hartung Toppa Ricardo Vicente Ferreira Alexandre Cavagis Fernando Shinji Kawakubo Rúbia Gomes Morato Department of Geography Tourism and Humanities Federal University of S&#227 o Carlos (UFSCar) Sorocaba Brazil Department of Environmental Science Federal University of S&#227 o Carlos (UFSCar) Sorocaba Brazil Department of Geography Federal University of Tri&#226 ngulo Mineiro (UFTM) Uberaba Brazil Department of Physics Chemistry and Mathematics Federal University of S&#227 o Carlos (UFSCar) Sorocaba Brazil Department of Geography University of S&#227 o Paulo (USP) S&#227 o Paulo Brazil

There has been great interest on the part of public and private initiatives in knowing the location of urban areas with potential for investments in social resources. The aim of the present article is to propose a methodology to identify such areas, using the city of São Paulo (Brazil) as a case study. This approach, supported by The Geographic Information System (GIS), is based on multicriteria analysis and quantification of spatial data. The results, presented spatially in a synthesis map, made possible to identify promissory areas for social investment in São Paulo. The method allows us to analyze data at different spatial scales from the GIS base, enabling a systematization to find out areas with higher potential for investment in social equipment, services and facilities. Furthermore, it gives possibility of modeling several variables, thus being adaptable to different geographic areas.

关键词： Urban Social Investment Spatial Multicriteria Analysis Geographic Information System

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Separability Analysis of Atlantic Forest Patches by Comparing Parametric and Non-Parametric Image Classification Algorithms

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Journal of Geographic Information System 2019年第5期11卷 567-578页

作者： marcos roberto martines Mariana de Paula Garcia Lúcio Alexandre D. M. Cavagis Marcel Fantin Ricardo Vicente Ferreira Matheus Oliveira Alves Rogério Hartung Toppa Federal University of So Carlos UFSCar/NEEPC So Carlos So Paulo Brazil Federal University of So Carlos UFSCar/DFQM So Carlos So Paulo Brazil University of So Paulo USP So Carlos So Paulo Brazil Federal University of Triangulo Mineiro Minas Gerais Brazil Faculdades Associadas de Uberaba FAZU Minas Gerais Brazil.

The aim of this work was to differentiate Atlantic Forest patches, as well as their spatial distribution, from other tree covers that compose the landscape, by comparing three methods of digital images classification, using techniques of geoprocessing and remote sensing. The study area was a sub-basin of the Iperó River, tributary of the Iperó-Mirim stream, Sarapuí River basin, in Araçoiaba da Serra, State of São Paulo, Brazil. This research has been developed on a Geographic Information System environment platform, using medium resolution images from Sentinel-2 Satellite. Three image classification algorithms: Maximum Likelihood Classification (MLC), Support Vector Machines (SVM) and Random Tree (RT) were applied to verify the separability of forest patches, forestry and other uses. The results were analyzed by means of a confusion matrix, accuracy and kappa index, thus showing that the three algorithms were able to successfully differentiate the targets, with the higher efficiency attributed to MLC and the lowest to RT. Overall, the three classifiers presented errors, but specifically for the forest patches, the highest accuracy was obtained from SVM.

关键词： Atlantic Forest Land Cover Image Classification

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Geoprocessing Applied in the Estimate of Infiltration and Surface Runoff in HPP’s Contribution Watershed

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Journal of Geographic Information System 2021年第6期13卷 643-659页

作者： Elizon Dias Nunes Patrícia De Araújo Romão Maurício martines Sales Marta Pereira Da Luz Institute of Socio-Environmental Studies Federal University of Goiás Goiania Brazil School of Civil and Environmental Engineering Federal University of Goiás Goiania Brazil Eletrobras Furnas Aparecida de Goiania Brazil Polytechnic School Pontifical Catholic University of Goiás Goiania Brazil

The knowledge of the hydrological regime contributes to the prediction of periods of higher or lower water supply as a function of the frequency and volume of rainfall in relation to the pedological, land cover, and land use conditions. This work aims at evaluating the spatio-temporal variability of the infiltration and runoff potential of an area formed by 4 sub-basins tributary to the São marcos River in Cristalina (GO). The SCS/NRCS-USDA (2004) method was used, using geoprocessing resources, considering soils in dry, semi-humid and humid conditions. The estimates indicate that rainfall with an average of 6.83 mm, in the September-October transition, in the face of soils in the dry condition does not provide surface runoff. Thus, the variability of pedological characteristics associated with the various conditions of coverage and land use indicates that even the areas with lower infiltration potential begin to contribute effectively with their respective channels in the transition from October to November, when rainfall events are more frequent and significant, and the soils are already in conditions of greater humidity.

关键词： Rainfall Height Runoff Coefficient Hydrological Behavior

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