Open legacy soil survey data in Brazil: geospatial data quality and how to improve it

Detalhes bibliográficos
Autor(a) principal: Samuel-Rosa, Alessandro
Data de Publicação: 2020
Outros Autores: Dalmolin, Ricardo Simão Diniz, Moura-Bueno, Jean Michel, Teixeira, Wenceslau Geraldes, Alba, José Maria Filippini
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/160727
Resumo: Spatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil observations, estimated using the web mapping service, were validated with the true coordinates measured in the field. Overall, inconsistencies of different types and magnitudes were found in half of the observations, causing mild to severe misplacements. The involuntary substitution of symbols and numeric characters with similar appearance when recording geospatial data was the most common typing mistake. Among the geospatial data sources, the web mapping service was the most useful, due to operational advantages and lower positional error (~6 m). However, the quality of the description of the observation location controls the accuracy of estimated coordinates. Thus, the error of coordinates estimated using the web mapping service ranged between 30 and 1000 m. This is equivalent to coordinates measured from arc-seconds to arc-minutes, respectively. Under this scenario, the feedback from soil survey experts is crucial to improving the quality of geospatial data.
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spelling Open legacy soil survey data in Brazil: geospatial data quality and how to improve itFree Brazilian Repository for Open Soil DataPronaSolosPedometricssoil data recoverydigital soil mappingSpatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil observations, estimated using the web mapping service, were validated with the true coordinates measured in the field. Overall, inconsistencies of different types and magnitudes were found in half of the observations, causing mild to severe misplacements. The involuntary substitution of symbols and numeric characters with similar appearance when recording geospatial data was the most common typing mistake. Among the geospatial data sources, the web mapping service was the most useful, due to operational advantages and lower positional error (~6 m). However, the quality of the description of the observation location controls the accuracy of estimated coordinates. Thus, the error of coordinates estimated using the web mapping service ranged between 30 and 1000 m. This is equivalent to coordinates measured from arc-seconds to arc-minutes, respectively. Under this scenario, the feedback from soil survey experts is crucial to improving the quality of geospatial data.Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2020-02-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/16072710.1590/1678-992x-2017-0430Scientia Agricola; v. 77 n. 1 (2020); e20170430Scientia Agricola; Vol. 77 Núm. 1 (2020); e20170430Scientia Agricola; Vol. 77 No. 1 (2020); e201704301678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/160727/154973Copyright (c) 2020 Scientia Agricolainfo:eu-repo/semantics/openAccessSamuel-Rosa, AlessandroDalmolin, Ricardo Simão DinizMoura-Bueno, Jean MichelTeixeira, Wenceslau GeraldesAlba, José Maria Filippini2019-08-05T18:27:37Zoai:revistas.usp.br:article/160727Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2019-08-05T18:27:37Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
title Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
spellingShingle Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
Samuel-Rosa, Alessandro
Free Brazilian Repository for Open Soil Data
PronaSolos
Pedometrics
soil data recovery
digital soil mapping
title_short Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
title_full Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
title_fullStr Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
title_full_unstemmed Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
title_sort Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
author Samuel-Rosa, Alessandro
author_facet Samuel-Rosa, Alessandro
Dalmolin, Ricardo Simão Diniz
Moura-Bueno, Jean Michel
Teixeira, Wenceslau Geraldes
Alba, José Maria Filippini
author_role author
author2 Dalmolin, Ricardo Simão Diniz
Moura-Bueno, Jean Michel
Teixeira, Wenceslau Geraldes
Alba, José Maria Filippini
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Samuel-Rosa, Alessandro
Dalmolin, Ricardo Simão Diniz
Moura-Bueno, Jean Michel
Teixeira, Wenceslau Geraldes
Alba, José Maria Filippini
dc.subject.por.fl_str_mv Free Brazilian Repository for Open Soil Data
PronaSolos
Pedometrics
soil data recovery
digital soil mapping
topic Free Brazilian Repository for Open Soil Data
PronaSolos
Pedometrics
soil data recovery
digital soil mapping
description Spatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil observations, estimated using the web mapping service, were validated with the true coordinates measured in the field. Overall, inconsistencies of different types and magnitudes were found in half of the observations, causing mild to severe misplacements. The involuntary substitution of symbols and numeric characters with similar appearance when recording geospatial data was the most common typing mistake. Among the geospatial data sources, the web mapping service was the most useful, due to operational advantages and lower positional error (~6 m). However, the quality of the description of the observation location controls the accuracy of estimated coordinates. Thus, the error of coordinates estimated using the web mapping service ranged between 30 and 1000 m. This is equivalent to coordinates measured from arc-seconds to arc-minutes, respectively. Under this scenario, the feedback from soil survey experts is crucial to improving the quality of geospatial data.
publishDate 2020
dc.date.none.fl_str_mv 2020-02-20
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/160727
10.1590/1678-992x-2017-0430
url https://www.revistas.usp.br/sa/article/view/160727
identifier_str_mv 10.1590/1678-992x-2017-0430
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/160727/154973
dc.rights.driver.fl_str_mv Copyright (c) 2020 Scientia Agricola
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Scientia Agricola
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 77 n. 1 (2020); e20170430
Scientia Agricola; Vol. 77 Núm. 1 (2020); e20170430
Scientia Agricola; Vol. 77 No. 1 (2020); e20170430
1678-992X
0103-9016
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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