Modelling effective soil depth at field scale from soil sensors and geomorphometric indices

The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent...

Full description

Autores:
Castro Franco, Mauricio
Domenech, Marisa
Costa, José Luis
Aparicio, Virginia Carolina
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/61087
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/61087
http://bdigital.unal.edu.co/59895/
Palabra clave:
55 Ciencias de la tierra / Earth sciences and geology
63 Agricultura y tecnologías relacionadas / Agriculture
Feature selection
Petrocalcic horizon
Random Forest
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
id UNACIONAL2_4c5656d2c559d3340ada3c5f72110416
oai_identifier_str oai:repositorio.unal.edu.co:unal/61087
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Castro Franco, Mauricio5cf9e3f2-e214-4b11-99a2-61eac489e148300Domenech, Marisa508b8404-1a19-4b5a-9c07-2fb271109d54300Costa, José Luis01ba83ec-1aa4-44bc-a276-80846fc447a0300Aparicio, Virginia Carolina95269684-6f5e-4a4c-93f8-2fbd0a0978dc3002019-07-02T19:53:30Z2019-07-02T19:53:30Z2017-04-01ISSN: 2323-0118https://repositorio.unal.edu.co/handle/unal/61087http://bdigital.unal.edu.co/59895/The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results.application/pdfspaUniversidad Nacional de Colombia - Sede Palmirahttps://revistas.unal.edu.co/index.php/acta_agronomica/article/view/53282Universidad Nacional de Colombia Revistas electrónicas UN Acta AgronómicaActa AgronómicaCastro Franco, Mauricio and Domenech, Marisa and Costa, José Luis and Aparicio, Virginia Carolina (2017) Modelling effective soil depth at field scale from soil sensors and geomorphometric indices. Acta Agronómica, 66 (2). 228 - 234. ISSN 2323-011855 Ciencias de la tierra / Earth sciences and geology63 Agricultura y tecnologías relacionadas / AgricultureFeature selectionPetrocalcic horizonRandom ForestModelling effective soil depth at field scale from soil sensors and geomorphometric indicesArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL53282-311471-4-PB.pdfapplication/pdf10405624https://repositorio.unal.edu.co/bitstream/unal/61087/1/53282-311471-4-PB.pdf86692b098c06a467b9b273fcc3c61ac7MD51THUMBNAIL53282-311471-4-PB.pdf.jpg53282-311471-4-PB.pdf.jpgGenerated Thumbnailimage/jpeg7646https://repositorio.unal.edu.co/bitstream/unal/61087/2/53282-311471-4-PB.pdf.jpg2124998d1feb5c37925edc01df348098MD52unal/61087oai:repositorio.unal.edu.co:unal/610872023-04-10 23:05:23.171Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co
dc.title.spa.fl_str_mv Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
spellingShingle Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
55 Ciencias de la tierra / Earth sciences and geology
63 Agricultura y tecnologías relacionadas / Agriculture
Feature selection
Petrocalcic horizon
Random Forest
title_short Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title_full Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title_fullStr Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title_full_unstemmed Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
title_sort Modelling effective soil depth at field scale from soil sensors and geomorphometric indices
dc.creator.fl_str_mv Castro Franco, Mauricio
Domenech, Marisa
Costa, José Luis
Aparicio, Virginia Carolina
dc.contributor.author.spa.fl_str_mv Castro Franco, Mauricio
Domenech, Marisa
Costa, José Luis
Aparicio, Virginia Carolina
dc.subject.ddc.spa.fl_str_mv 55 Ciencias de la tierra / Earth sciences and geology
63 Agricultura y tecnologías relacionadas / Agriculture
topic 55 Ciencias de la tierra / Earth sciences and geology
63 Agricultura y tecnologías relacionadas / Agriculture
Feature selection
Petrocalcic horizon
Random Forest
dc.subject.proposal.spa.fl_str_mv Feature selection
Petrocalcic horizon
Random Forest
description The effective soil depth (ESD) affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30) and 0-90 (ECa_90) and geomorphometric indices. To do this, a Random Forest (RF) analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror) were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results.
publishDate 2017
dc.date.issued.spa.fl_str_mv 2017-04-01
dc.date.accessioned.spa.fl_str_mv 2019-07-02T19:53:30Z
dc.date.available.spa.fl_str_mv 2019-07-02T19:53:30Z
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.coarversion.spa.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/ART
format http://purl.org/coar/resource_type/c_6501
status_str publishedVersion
dc.identifier.issn.spa.fl_str_mv ISSN: 2323-0118
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/61087
dc.identifier.eprints.spa.fl_str_mv http://bdigital.unal.edu.co/59895/
identifier_str_mv ISSN: 2323-0118
url https://repositorio.unal.edu.co/handle/unal/61087
http://bdigital.unal.edu.co/59895/
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.spa.fl_str_mv https://revistas.unal.edu.co/index.php/acta_agronomica/article/view/53282
dc.relation.ispartof.spa.fl_str_mv Universidad Nacional de Colombia Revistas electrónicas UN Acta Agronómica
Acta Agronómica
dc.relation.references.spa.fl_str_mv Castro Franco, Mauricio and Domenech, Marisa and Costa, José Luis and Aparicio, Virginia Carolina (2017) Modelling effective soil depth at field scale from soil sensors and geomorphometric indices. Acta Agronómica, 66 (2). 228 - 234. ISSN 2323-0118
dc.rights.spa.fl_str_mv Derechos reservados - Universidad Nacional de Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
Derechos reservados - Universidad Nacional de Colombia
http://creativecommons.org/licenses/by-nc/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia - Sede Palmira
institution Universidad Nacional de Colombia
bitstream.url.fl_str_mv https://repositorio.unal.edu.co/bitstream/unal/61087/1/53282-311471-4-PB.pdf
https://repositorio.unal.edu.co/bitstream/unal/61087/2/53282-311471-4-PB.pdf.jpg
bitstream.checksum.fl_str_mv 86692b098c06a467b9b273fcc3c61ac7
2124998d1feb5c37925edc01df348098
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
repository.mail.fl_str_mv repositorio_nal@unal.edu.co
_version_ 1814090006601400320