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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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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. |
format | Online Article Text |
id | pubmed-6580115 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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