Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method

Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method

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 techno...

Full description

Bibliographic Details
Main Authors: Raúl R. Poppiel, Marilusa P.C. Lacerda, José A.M. Demattê, Manuel P. Oliveira, Jr., Bruna C. Gallo, José L. Safanelli
Format: Article
Language:English
Published: Elsevier 2019-08-01
Series:Data in Brief
Online Access:http://www.sciencedirect.com/science/article/pii/S235234091930424X
id doaj-0545c9ba5d1e42188203c03d1f58ec63
record_format Article
spelling doaj-0545c9ba5d1e42188203c03d1f58ec632020-11-25T02:16:07ZengElsevierData in Brief2352-34092019-08-0125Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA methodRaúl R. Poppiel0Marilusa P.C. Lacerda1José A.M. Demattê2Manuel P. Oliveira, Jr.3Bruna C. Gallo4José L. Safanelli5Faculty of Agronomy and Veterinary Medicine, University of Brasília; ICC Sul, Darcy Ribeiro University Campus, Asa Norte, Postal Box 4508, Brasília 70910-960, Brazil; Corresponding author.Faculty of Agronomy and Veterinary Medicine, University of Brasília; ICC Sul, Darcy Ribeiro University Campus, Asa Norte, Postal Box 4508, Brasília 70910-960, BrazilDepartment of Soil Science, College of Agriculture Luiz de Queiroz, University of São Paulo; Pádua Dias Av., 11, Piracicaba, Postal Box 09, São Paulo 13416-900, BrazilFaculty of Agronomy and Veterinary Medicine, University of Brasília; ICC Sul, Darcy Ribeiro University Campus, Asa Norte, Postal Box 4508, Brasília 70910-960, BrazilDepartment of Soil Science, College of Agriculture Luiz de Queiroz, University of São Paulo; Pádua Dias Av., 11, Piracicaba, Postal Box 09, São Paulo 13416-900, BrazilDepartment of Soil Science, College of Agriculture Luiz de Queiroz, University of São Paulo; Pádua Dias Av., 11, Piracicaba, Postal Box 09, São Paulo 13416-900, BrazilGeospatial 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. Keywords: Digital soil mapping, Soil management, Agricultural planning, Soil classification system, Landsathttp://www.sciencedirect.com/science/article/pii/S235234091930424X
collection DOAJ
language English
format Article
sources DOAJ
author Raúl R. Poppiel
Marilusa P.C. Lacerda
José A.M. Demattê
Manuel P. Oliveira, Jr.
Bruna C. Gallo
José L. Safanelli
spellingShingle Raúl R. Poppiel
Marilusa P.C. Lacerda
José A.M. Demattê
Manuel P. Oliveira, Jr.
Bruna C. Gallo
José L. Safanelli
Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method
Data in Brief
author_facet Raúl R. Poppiel
Marilusa P.C. Lacerda
José A.M. Demattê
Manuel P. Oliveira, Jr.
Bruna C. Gallo
José L. Safanelli
author_sort Raúl R. Poppiel
title Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method
title_short Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method
title_full Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method
title_fullStr Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method
title_full_unstemmed Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method
title_sort soil class map of the rio jardim watershed in central brazil at 30 meter spatial resolution based on proximal and remote sensed data and mesma method
publisher Elsevier
series Data in Brief
issn 2352-3409
publishDate 2019-08-01
description 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. Keywords: Digital soil mapping, Soil management, Agricultural planning, Soil classification system, Landsat
url http://www.sciencedirect.com/science/article/pii/S235234091930424X
work_keys_str_mv AT raulrpoppiel soilclassmapoftheriojardimwatershedincentralbrazilat30meterspatialresolutionbasedonproximalandremotesenseddataandmesmamethod
AT marilusapclacerda soilclassmapoftheriojardimwatershedincentralbrazilat30meterspatialresolutionbasedonproximalandremotesenseddataandmesmamethod
AT joseamdematte soilclassmapoftheriojardimwatershedincentralbrazilat30meterspatialresolutionbasedonproximalandremotesenseddataandmesmamethod
AT manuelpoliveirajr soilclassmapoftheriojardimwatershedincentralbrazilat30meterspatialresolutionbasedonproximalandremotesenseddataandmesmamethod
AT brunacgallo soilclassmapoftheriojardimwatershedincentralbrazilat30meterspatialresolutionbasedonproximalandremotesenseddataandmesmamethod
AT joselsafanelli soilclassmapoftheriojardimwatershedincentralbrazilat30meterspatialresolutionbasedonproximalandremotesenseddataandmesmamethod
_version_ 1724892741278629888

Similar Items