8 resultados para thematic mapping

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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In this work, we show the experience of continuing teacher education in Cartography in the period from 03/11/2009 to 03/11/2010, it was held by the Center for Continuing Education in Mathematics Education, Science and Environment (CECEMCA) - UNESP - Rio Claro, in DL (Distance Learning). This experience was through the extension course set in TelEduc platform. The course was titled Introduction to Cartography and aimed primarily: Present concepts of systematic and thematic mapping and its potential application in teaching practices, increase knowledge in the areas of Geography, Cartography and Environment; Offer alternatives for implementing content mapping in the classroom.

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Land cover mappings represent important tools for the regional planning. However, the current mappings are related to very specific purposes and, consequently, they are limited in their capacity to define the wide variety of existing types of land cover. In that context, this paper aims at developing a wide and including hierarchical classification system for land cover mapping in regional scale, which should contribute for a future standardization of classes. Besides, it is intended to test that system for a study case that contemplates the use of a classification method based on fuzzy approach, which has shown to be more appropriate than conventional approaches. Therefore, it was proposed a hierarchical classification system with three detailing levels and a study case was defined with the specification of the test area and of the classification project. Then, the georreferencing of a TM/Landsat-5 image that comprises the test area was carried out. Later, it was applied a fuzzy classification approach in the TM/Landsat-5 image, starting from images of probability for the mapped classes and an uncertainty image were generated. Finally, it was produced a conventional output that represents the thematic mapping of the test area.

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The great diversity of materials that characterizes the urban environment determines a structure of mixed classes in a classification of multiespectral images. In that sense, it is important to define an appropriate classification system using a non parametric classifier, that allows incorporating non spectral (such as texture) data to the process. They also allow analyzing the uncertainty associated to each class from the output alues of the network calculated in relation to each class. Considering these properties, an experiment was carried out. This experiment consisted in the application of an Artificial Neural Network aiming at the classification of the urban land cover of Presidente Prudente and the analysis of the uncertainty in the representation of the mapped thematic classes. The results showed that it is possible to discriminate the variations in the urban land cover through the application of an Artificial Neural Network. It was also possible to visualize the spatial variation of the uncertainty in the attribution of classes of urban land cover from the generated representations. The class characterized by a defined pattern as intermediary related to the impermeability of the urban soil presented larger ambiguity degree and, therefore, larger mixture.

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This research is based on the physical characterization of the environment to support definition of the best land use for the county of Colorado D'Oeste, in State of Rondônia, Brazil. Remote sensing and geoprocessing techniques were applied to support the preparation of a Geoenvironmental Zoning, which was used to define strategies of territorial and environmental management in that county. Digital and analogical remote sensing products, acquired by satellites, and additional cartographic and thematic maps allowed a morphostructural analysis to define low and high structural associated study site tectonic. Subsequently, this information was used to support analysis of the physiographic compartmentation of the study area. Based on this study information, it is possible to define geoenvironmental subzones and local hidrological regime, soils, mineral components, texture, color, and sedimentary materials. By integrating previous described information, a synthesis cartographic map generated. Accordingly, this Cartographic Sheet spatially defined the best land use over the study area, indicates zones for conservation, agricultural, and regeneration (areas that should be recovered). Finally, the results of this research can contribute and support governmental and non-governmental organization and local communities could improve land use and soil management, avoiding natural resource destruction and future land scarcity in the county of Colorado D'Oeste.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The landuse is usually an human phenomenon that occurs over the years, due to population increase. The territorial knowledge is needed, and is the first step for environmental planning to implement conservation practices on agricultural production system. This study aimed to develop thematic maps as: hydrography, soil, slope, land use, and subbasins to obtain the main geomorphic morphometric data (physical) of the Córrego Rico Watershed. The techniques of remote sensing and geographic information system were used to elaborate the maps and for calculating the geomorphological data, as area, altitude and length of the drainage net, which were submitted to multivariate statistics. The Córrego Rico Watershed has an area of 563 km2 . The predominant slopes were 3-8%, with 55.3% of the total area; and the main use was sugar cane. The soils that predominate in the area are Oxisols towards the Mogi-Guaçú river mouth and Ultisols at the upstream of the basin.