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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Infer?ncia fuzzy para predi??o de classes de solo em ?reas de assentamentos na microrregi?o da Mata Alagoana / Fuzzy inference to predict soil classes in areas of the microregion of Mata Alagoana / Inferencia fuzzy para la predici?n de clases de suelo en ?reas de asentamientos en la Microrregi?n de la Mata Alagoana

CARVALHO, Claudia Csek? Nolasco de 27 May 2015 (has links)
Submitted by Jorge Silva (jorgelmsilva@ufrrj.br) on 2018-08-29T20:27:02Z No. of bitstreams: 1 2015 - Claudia Cseko Nolasco de Carvalho.pdf: 7996736 bytes, checksum: 4342b7f850b677568441806a801d9047 (MD5) / Made available in DSpace on 2018-08-29T20:27:02Z (GMT). No. of bitstreams: 1 2015 - Claudia Cseko Nolasco de Carvalho.pdf: 7996736 bytes, checksum: 4342b7f850b677568441806a801d9047 (MD5) Previous issue date: 2015-05-27 / Sustainable development requires more detailed soil maps with representative information of local reality, helping to conciliate increasing agriculture production and environmental impacts reduction. It is a hard task to achieve considering the Brazil territorial extension and the absence of governmental programs and resources. The Digital Soil Mapping (DSM), through methodologies implementation, has been consolidated as support technique for conventional mapping. Using DSM techniques, we aimed to evaluate a methodological procedure to generate soil maps with refined scale by fuzzy inference, and to map simpler units, which means more adequate areas for the rural settlement development plans. We carried out the study on an area at the microregion of Mata of Alagoas State and the following attributes were integrated by pedologist knowledge: elevation, slope, curvature and profile, topographic wetness index ? derived from a Digital Elevation Model (built by aerophotogrammetric restitution at scale 1:8 000), and geological data at scale 1:50 000. In a first moment, we integrate the thematic layers of 5m resolution pixel related to the attributes. Possibility maps of predefined classes were generate based on rules established by pedological expertise using fuzzy inference. Then, we integrate the evidence maps of classes by weighted mean inference to produce the soils digital map. The predicted digital soil map was opposed to a map elaborated traditionally, and validated by field observation of transects and pre-existent profiles. The comparison between the digital soil map and the conventional indicated a accuracy of 81.2% between the predicted classes of the digital map and the ones on the conventional map units (described on the legend, however not spatialized). Confronting the predicted classes of the digital soil map and the ones identified on field, the observed accuracy was of 74.65%. The Kappa index found was very good, with 0.696 values for the comparison between the digital map and the conventional map and 0.705 between the digital map and field observations. The results demonstrate that legacy maps data may, through the pedologists knowledge and more detailed attribute data, aggregate information and produce more detailed soil maps. Considering the concepts of minimum mappable area, the definitions of pixel sizes suggested for the digital cartographic scale, and the rules for soil survey, the applied methodology allowed, on the used cartographic base, the amplification of the mapping scale from 1:25 000 to 1:15 000. / O desenvolvimento sustent?vel requer mapas de solo mais detalhados com informa??es representativas da realidade local que permitem conciliar aumento da produ??o agropecu?ria com minimiza??o de impactos ambientais. Essa ? uma tarefa dif?cil considerando a extens?o territorial do Brasil e a falta de programas e recursos governamentais. O Mapeamento Digital de Solos-MDS, atrav?s da implementa??o de metodologias, vem se consolidando como t?cnica de apoio ao mapeamento convencional. Usando t?cnicas de MDS, esse trabalho objetivou avaliar um procedimento metodol?gico para gerar mapa de solos com refinamento de escala usando infer?ncia fuzzy para mapear unidades mais simples, portanto mais adequadas aos planos de desenvolvimento dos assentamentos rurais. A ?rea escolhida para teste est? localizada na microrregi?o da Mata do Estado de Alagoas. Para execu??o do trabalho os atributos do terreno eleva??o, declividade, curvatura em perfil, plano de curvatura e ?ndice de umidade topogr?fica derivados de Modelo Digital de Eleva??o-MDE (gerado por restitui??o aerofotogram?trica na escala 1:8.000) e dados geol?gicos em escala 1:50:000, foram integrados atrav?s do conhecimento de ped?logos. Os planos de informa??es, com pixel de 5 m, a partir de regras estabelecidas pela expertise de ped?logos foram fuzzificados e integrados para gerar os mapas de possibilidades de ocorr?ncia para as classes de solo predefinidas. O mapa digital de solos foi produzido pela integra??o dos mapas de possibilidades das classes por infer?ncia m?dia ponderada. O mapa digital de solos predito foi confrontado com mapa elaborado por m?todo tradicional e validado por observa??es em campo ao longo de transectos e por perfis preexistentes. A an?lise comparativa entre o mapa digital de solos e o convencional obteve acur?cia de 81,2 % entre as classes preditas no mapa digital e as contidas nas unidades do mapa convencional (descritas na legenda, por?m n?o espacializadas). Confrontando as classes preditas no mapa digital e as identificadas no campo a acur?cia encontrada foi de 74,65%. A aferi??o das classes pelo ?ndice de Kappa foi considerada muito boa com valores de 0,696 para a compara??o entre o mapa digital versos mapa convencional e 0,705 entre o mapa digital e as observa??es de campo. A pesquisa mostrou que dados contidos em mapas legados de solo podem atrav?s do conhecimento de ped?logos e de dados detalhados de atributos do terreno agregar informa??es e produzir mapa digital de solo com amplia??o da escala e que neste trabalho ? compat?vel com a de levantamentos detalhados (1:15.000).

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