Mineração de dados para inferência da relação solo ... - IAC

CRIVELENTI, Rafael Castro. Data mining about to inference from relation soil -landscape in digital mapping soil. Dissertação (Mestrado em Gestão de RecursosAgroambientais) – Pós-Graduação – IAC.ABSTRACTDigital soil mapping can be a feasible option for less expensive and less timeconsumingsoil surveys. This research aims to develop a digital soil mapping techniqueusing relief descriptors as well as geologic mapping units in order to produce digital soilmaps of two topographic sheets to the scale of 1:50.000, Sao Pedro (SF-23-Y-A-IV-1) eDois Corregos (SF-22-Z-B-III-3). A digital database was built with topographic,geological and soil survey sheets. A digital elevation model (DEM), constructed fromthe 1:50.000 topo sheets, was used to create the relief morphometrical parameters slopegradient, slope profile, contour profile, basin contribution area, and diagonal distance tothe drainage of the two study areas. These parameters together with the geological mapwere georeferred, rasterized, and spatially associated to the existing 1:100.000-scale soilmaps, what allowed building a matrix of landscape parameters and soil mapping units.These matrixes were used in the Weka machine-learning environment to generate aprediction model by means of decision trees. The rules developed by the models wereapplied in geographical information systems to produce digital soil maps. Geology wasthe element with the greatest ability to predict soil mapping units, followed by slopegradient, at the Sao Pedro sheet, and by diagonal distance to the drainage, at the DoisCorregos sheet. Decision trees performed well to produce the models, with a spatialaccuracy of 55 % for the Sao Pedro and 61 % for the Dois Corregos sheets. Balancingclasses for training the data increased precision of mapping units with the leastextensive occurrences, associated to little reduction in the precision of those that occurin greater extensions, what improved usefulness of the produced digital soil maps.XIII