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- W2266408608 abstract "The soil survey and the resultant soil maps are produced, in his majority, by conventional approaches. The mapping units delimitation in these maps, depends on the technical experience of the person that will be carrying out the task. Aiming to reduce the subjectivity in that task and integrate facts of different origins to define preliminary mapping units of soils, it was utilized the technics of artificial neural network (ANN). In the ANN here applied 12 environmental variables combined were utilized in different ways. The selected variables were: geology, slope, aspect, elevation, profile and plan of curvature, annual solar radiation, and some secundary topographic index: wetness, sediments transport capacity, the stream power index and the spectral indexes ndvi and iron oxide. The results are going to affirm that, to ANN enables the integration of different variables for the trial delineation of preliminary units in soils maps . In the maps obtained by the ANN, regarding the combination of the different selected sets, the largest values of index kappa and global accuracy present also, in the units of mapping, larger indices of accuracy of the viewpoint of the user. All the resultant maps from the classification by RNA present more spatial details than the conventional soil map." @default.
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- W2266408608 date "2013-01-01" @default.
- W2266408608 modified "2023-09-23" @default.
- W2266408608 title "PEDOMETRIA APOIADA EM ATRIBUTOS TOPOGRÁFICOS, ÍNDICES ESPECTRAIS E GEOLOGIA COM USO DE REDES NEURAIS ARTIFICIAIS" @default.
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