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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 tech...

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Main Authors: Poppiel, Raúl R., Lacerda, Marilusa Pinto Coelho, Demattê, José A. M., Oliveira Jr., Manuel P., Gallo, Bruna C., Safanelli, José L.
Format: Artigo
Language: Inglês
Published: Elsevier Inc. 2020
Subjects:
Mapeamento digital do solo
Solos - manejo
Planejamento agrícola
Online Access: https://repositorio.unb.br/handle/10482/36174
https://doi.org/10.1016/j.dib.2019.104070
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spelling ir-10482-361742020-01-21T13:09:30Z 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 Pinto Coelho Demattê, José A. M. Oliveira Jr., Manuel P. Gallo, Bruna C. Safanelli, José L. Mapeamento digital do solo Solos - manejo Planejamento agrícola 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. 2020-01-21T13:09:01Z 2020-01-21T13:09:01Z 2019 Artigo POPPIEL, Raúl R. et al. 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, v. 25, 104070, 2019. DOI: https://doi.org/10.1016/j.dib.2019.104070. Disponível em: https://www.sciencedirect.com/science/article/pii/S235234091930424X. Acesso em: 21 jan. 2020. https://repositorio.unb.br/handle/10482/36174 https://doi.org/10.1016/j.dib.2019.104070 Inglês Acesso Aberto © 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/). application/pdf Elsevier Inc.
institution REPOSITORIO UNB
collection REPOSITORIO UNB
language Inglês
topic Mapeamento digital do solo
Solos - manejo
Planejamento agrícola
spellingShingle Mapeamento digital do solo
Solos - manejo
Planejamento agrícola
Poppiel, Raúl R.
Lacerda, Marilusa Pinto Coelho
Demattê, José A. M.
Oliveira Jr., 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
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 Artigo
author Poppiel, Raúl R.
Lacerda, Marilusa Pinto Coelho
Demattê, José A. M.
Oliveira Jr., Manuel P.
Gallo, Bruna C.
Safanelli, José L.
author_sort Poppiel, Raúl R.
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 Inc.
publishDate 2020
url https://repositorio.unb.br/handle/10482/36174
https://doi.org/10.1016/j.dib.2019.104070
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score 13.657419

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