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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...

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Autores principales: Poppiel, Raúl R., Lacerda, Marilusa P.C., Demattê, José A.M., Oliveira, Manuel P., Gallo, Bruna C., Safanelli, José L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580115/
https://www.ncbi.nlm.nih.gov/pubmed/31431909
http://dx.doi.org/10.1016/j.dib.2019.104070
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author Poppiel, Raúl R.
Lacerda, Marilusa P.C.
Demattê, José A.M.
Oliveira, Manuel P.
Gallo, Bruna C.
Safanelli, José L.
author_facet Poppiel, Raúl R.
Lacerda, Marilusa P.C.
Demattê, José A.M.
Oliveira, Manuel P.
Gallo, Bruna C.
Safanelli, José L.
author_sort Poppiel, Raúl R.
collection PubMed
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.
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spelling pubmed-65801152019-08-20 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 Poppiel, Raúl R. Lacerda, Marilusa P.C. Demattê, José A.M. Oliveira, Manuel P. Gallo, Bruna C. Safanelli, José L. Data Brief Agricultural and Biological Science 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. Elsevier 2019-05-30 /pmc/articles/PMC6580115/ /pubmed/31431909 http://dx.doi.org/10.1016/j.dib.2019.104070 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Agricultural and Biological Science
Poppiel, Raúl R.
Lacerda, Marilusa P.C.
Demattê, José A.M.
Oliveira, Manuel P.
Gallo, Bruna C.
Safanelli, José L.
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 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_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_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
topic Agricultural and Biological Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580115/
https://www.ncbi.nlm.nih.gov/pubmed/31431909
http://dx.doi.org/10.1016/j.dib.2019.104070
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