Open legacy soil survey data in Brazil: geospatial data quality and how to improve it
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Scientia Agrícola (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101401 |
Resumo: | ABSTRACT: 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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Scientia Agrícola (Online) |
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Open legacy soil survey data in Brazil: geospatial data quality and how to improve itFree Brazilian Repository for Open Soil DataPronaSolosPedometricssoil data recoverydigital soil mappingABSTRACT: 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.Escola Superior de Agricultura "Luiz de Queiroz"2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101401Scientia Agricola v.77 n.1 2020reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USP10.1590/1678-992x-2017-0430info:eu-repo/semantics/openAccessSamuel-Rosa,AlessandroDalmolin,Ricardo Simão DinizMoura-Bueno,Jean MichelTeixeira,Wenceslau GeraldesAlba,José Maria Filippinieng2019-06-28T00:00:00Zoai:scielo:S0103-90162020000101401Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2019-06-28T00:00Scientia 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 |
ABSTRACT: 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 |
2020-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101401 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000101401 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-992x-2017-0430 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
publisher.none.fl_str_mv |
Escola Superior de Agricultura "Luiz de Queiroz" |
dc.source.none.fl_str_mv |
Scientia Agricola v.77 n.1 2020 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 |
_version_ |
1748936465198350336 |