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Updated: Jan 20, 2026

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
Published on: October 16, 2018
Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and
Raúl R Poppiel1, Marilusa P C Lacerda1, José A M Demattê2
1Faculty of Agronomy and Veterinary Medicine, University of Brasília; ICC Sul, Darcy Ribeiro University Campus, Asa Norte, Postal Box 4508, Brasília 70910-960, Brazil.
Abstract:
Geospatial soil information is critical for agricultural policy formulation and decision making, land-use suitability analysis, sustainable soil management, environmental assessment, and other research topics that are of vital importance to agriculture and economy. Proximal and Remote sensing technologies enables us to collect, process, and analyze spectral data and to retrieve, synthesize, visualize valuable geospatial information for multidisciplinary uses. We obtained the soil class map provided in this article by processing and analyzing proximal and remote sensed data from soil samples collected in toposequences based on pedomorphogeological relashionships. The soils were classified up to the second categorical level (suborder) of the Brazilian Soil Classification System (SiBCS), as well as in the World Reference Base (WRB) and United States Soil Taxonomy (ST) systems. The raster map has 30 m resolution and its accuracy is 73% (Kappa coefficient of 0.73). The soil legend represents a soil class followed by its topsoil color.
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