Proximal soil sensing platform for effective mapping of soil attributes in Brazil.
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1112779 |
Resumo: | Sustainable management of agricultural lands requires detailed information on soil properties. Although the literature has shown the potential of PSS data integration to predict spatial variations of soil properties, most of these studies were done in temperate soils considering up to three sensors. Study cases here introduced to contribute in applying PSS to: (i) assess the spatial variation of tropical soil chemical and physical attributes; (ii) understand processes controlling spatial soil variations; and (iii) compare spatial dependence and patterns among proximally-sensed and laboratory-measured soil attributes. In three preliminary study cases PSS was applied for digital soil mapping, soil salinity mapping, and within-field crop variations. Hand held and "on-the-go" sensors, respectively, for point-based and continuous monitoring readings, include apparent electrical conductivity and magnetic susceptibility meters; gamma ray, X-ray fluorescence and near infrared spectrometers; and mechanical resistance meters among others. Variables were significantly correlated (p < 0.05), and their spatial dependence structure (i.e: variogram analysis) and the spatial distribution patterns (i.e.: kriging) were all-similar. In addition, combined PSS datasets have shown improved predictions of soil properties (i.e.: R2adj. from 0.21 to 0.94). Results have indicated the potential of PSS to assess the spatial variation of soil attributes that are more difficult to collect and analyze, supporting detailed soil mapping for precision agriculture and related activities. |
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Proximal soil sensing platform for effective mapping of soil attributes in Brazil.Sensoriamento ProximalAtributos do SoloMapeamento Digital do SoloSensoriamento RemotoSolo TropicalMapaRemote sensingTropical soilsDigital imagesSoil mapSustainable management of agricultural lands requires detailed information on soil properties. Although the literature has shown the potential of PSS data integration to predict spatial variations of soil properties, most of these studies were done in temperate soils considering up to three sensors. Study cases here introduced to contribute in applying PSS to: (i) assess the spatial variation of tropical soil chemical and physical attributes; (ii) understand processes controlling spatial soil variations; and (iii) compare spatial dependence and patterns among proximally-sensed and laboratory-measured soil attributes. In three preliminary study cases PSS was applied for digital soil mapping, soil salinity mapping, and within-field crop variations. Hand held and "on-the-go" sensors, respectively, for point-based and continuous monitoring readings, include apparent electrical conductivity and magnetic susceptibility meters; gamma ray, X-ray fluorescence and near infrared spectrometers; and mechanical resistance meters among others. Variables were significantly correlated (p < 0.05), and their spatial dependence structure (i.e: variogram analysis) and the spatial distribution patterns (i.e.: kriging) were all-similar. In addition, combined PSS datasets have shown improved predictions of soil properties (i.e.: R2adj. from 0.21 to 0.94). Results have indicated the potential of PSS to assess the spatial variation of soil attributes that are more difficult to collect and analyze, supporting detailed soil mapping for precision agriculture and related activities.RONALDO PEREIRA DE OLIVEIRA, CNPS; HUGO M. RODRIGUES, UFRRJ; GUSTAVO DE MATTOS VASQUES, CNPS; SILVIO ROBERTO DE LUCENA TAVARES, CNPS; LUIS CARLOS HERNANI, CNPS; JESUS FERNANDO MANSILLA BACA, CNPS; MAURICIO RIZZATO COELHO, CNPS.OLIVEIRA, R. P. deRODRIGUES, H. M.VASQUES, G. de M.TAVARES, S. R. de L.HERNANI, L. C.BACA, J. F. M.COELHO, M. R.2019-10-04T18:06:28Z2019-10-04T18:06:28Z2019-10-0420192019-10-04T18:06:28ZArtigo em anais e proceedingsinfo:eu-repo/semantics/publishedVersionIn: GLOBAL WORKSHOP ON PROXIMAL SOIL SENSING, 5., 2019, Columbia, MO. Program and proceedings. Columbia, MO: University of Missouri, 2019. p. 273-278.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1112779enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2019-10-04T18:06:35Zoai:www.alice.cnptia.embrapa.br:doc/1112779Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542019-10-04T18:06:35Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. |
title |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. |
spellingShingle |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. OLIVEIRA, R. P. de Sensoriamento Proximal Atributos do Solo Mapeamento Digital do Solo Sensoriamento Remoto Solo Tropical Mapa Remote sensing Tropical soils Digital images Soil map |
title_short |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. |
title_full |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. |
title_fullStr |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. |
title_full_unstemmed |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. |
title_sort |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. |
author |
OLIVEIRA, R. P. de |
author_facet |
OLIVEIRA, R. P. de RODRIGUES, H. M. VASQUES, G. de M. TAVARES, S. R. de L. HERNANI, L. C. BACA, J. F. M. COELHO, M. R. |
author_role |
author |
author2 |
RODRIGUES, H. M. VASQUES, G. de M. TAVARES, S. R. de L. HERNANI, L. C. BACA, J. F. M. COELHO, M. R. |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
RONALDO PEREIRA DE OLIVEIRA, CNPS; HUGO M. RODRIGUES, UFRRJ; GUSTAVO DE MATTOS VASQUES, CNPS; SILVIO ROBERTO DE LUCENA TAVARES, CNPS; LUIS CARLOS HERNANI, CNPS; JESUS FERNANDO MANSILLA BACA, CNPS; MAURICIO RIZZATO COELHO, CNPS. |
dc.contributor.author.fl_str_mv |
OLIVEIRA, R. P. de RODRIGUES, H. M. VASQUES, G. de M. TAVARES, S. R. de L. HERNANI, L. C. BACA, J. F. M. COELHO, M. R. |
dc.subject.por.fl_str_mv |
Sensoriamento Proximal Atributos do Solo Mapeamento Digital do Solo Sensoriamento Remoto Solo Tropical Mapa Remote sensing Tropical soils Digital images Soil map |
topic |
Sensoriamento Proximal Atributos do Solo Mapeamento Digital do Solo Sensoriamento Remoto Solo Tropical Mapa Remote sensing Tropical soils Digital images Soil map |
description |
Sustainable management of agricultural lands requires detailed information on soil properties. Although the literature has shown the potential of PSS data integration to predict spatial variations of soil properties, most of these studies were done in temperate soils considering up to three sensors. Study cases here introduced to contribute in applying PSS to: (i) assess the spatial variation of tropical soil chemical and physical attributes; (ii) understand processes controlling spatial soil variations; and (iii) compare spatial dependence and patterns among proximally-sensed and laboratory-measured soil attributes. In three preliminary study cases PSS was applied for digital soil mapping, soil salinity mapping, and within-field crop variations. Hand held and "on-the-go" sensors, respectively, for point-based and continuous monitoring readings, include apparent electrical conductivity and magnetic susceptibility meters; gamma ray, X-ray fluorescence and near infrared spectrometers; and mechanical resistance meters among others. Variables were significantly correlated (p < 0.05), and their spatial dependence structure (i.e: variogram analysis) and the spatial distribution patterns (i.e.: kriging) were all-similar. In addition, combined PSS datasets have shown improved predictions of soil properties (i.e.: R2adj. from 0.21 to 0.94). Results have indicated the potential of PSS to assess the spatial variation of soil attributes that are more difficult to collect and analyze, supporting detailed soil mapping for precision agriculture and related activities. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10-04T18:06:28Z 2019-10-04T18:06:28Z 2019-10-04 2019 2019-10-04T18:06:28Z |
dc.type.driver.fl_str_mv |
Artigo em anais e proceedings |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
In: GLOBAL WORKSHOP ON PROXIMAL SOIL SENSING, 5., 2019, Columbia, MO. Program and proceedings. Columbia, MO: University of Missouri, 2019. p. 273-278. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1112779 |
identifier_str_mv |
In: GLOBAL WORKSHOP ON PROXIMAL SOIL SENSING, 5., 2019, Columbia, MO. Program and proceedings. Columbia, MO: University of Missouri, 2019. p. 273-278. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1112779 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1817695566182744064 |