Digital Mapping of Soil Classes in Rio de Janeiro State, Brazil: Data, Modelling and Prediction

Abstract

A soil database for Rio de Janeiro State was collated in Access, for a project on quantifying the magnitude, spatial distribution and organic carbon in the soils of Rio de Janeiro State (Projeto Carbono_RJ). The main activities were the search, selection, analysis and review of the data for each soil profile already described in the study area, the georeferencing of each soil profile (when spatial coordinates were not available) and the input of new soil profiles into a new interface. The Rio de Janeiro soil dataset now contains 731 soil profiles, 2744 soil horizons, and 48 soil attributes usually described at the soil survey process. From this soil dataset, only 431 soil profiles that were adequately geo-located have been used in this application. The dataset contains limited data for bulk density and hydraulic soil properties, among others. From this dataset, quantitative modelling and digital soil mapping have been completed experimentally at 90 m resolution, using soil data and predictor variables, such as satellite images, lithology, a prior soil map and a DEM and its derivates. This dataset, which is one of the more complete soil datasets in Brazil, is being used as a testbed for learning and teaching DSM, using a variety of methods based on the scorpan model (Embrapa, 2006). In the first instance, the soil dataset was used to predict soil classes at the Order level of the Brazilian Soil Classification System – SiBCS (Embrapa, 2006). Five models were built and their results were compared and mapped.