Pedological mapping through integration of digital terrain models spectral sensing and photopedology
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista ciência agronômica (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902015000400669 |
Resumo: | ABSTRACTNew tools for soil mapping are needed to increase speed and accuracy of pedological mapping processes. This study integrated various technologies to map soils of the Piracicaba region in São Paulo State, Brazil. Each technology was expected to provide different information to design a detailed map. We carried out field survey and soil sampling for laboratory analysis. Initially, we conducted field visits to obtain soil patterns of a reference site. We applied the acquired patterns to an validation site, based solely on information obtained from remote sensing and cartographic databases, namely LANDSAT 7/ETM, digital elevation models (DEM) and aerial photographs. We integrated the information from each product to generate the map of the validation site, which was validated by field inspection. Textural classification using satellite imaging ranged from 21-51% of accuracy. Band 5 in the sensor showed the best performance to discriminate between clayey and sandy soils. Aerial photographs provided the best information because, besides their own inherent characteristics, they operate on a larger scale and result in a map with up to 50 polygons, while DEM reached a maximum of 30 polygons. The digital mapping technology generated 45 mapping units. Finally, the mapping efficiently separated the Latosols from the other classes; however, in some cases there was confusion in the identification of Cambisols and litholic Neosols. |
id |
UFC-2_1ead4e5ac01ad572461ba7f9426ea451 |
---|---|
oai_identifier_str |
oai:scielo:S1806-66902015000400669 |
network_acronym_str |
UFC-2 |
network_name_str |
Revista ciência agronômica (Online) |
repository_id_str |
|
spelling |
Pedological mapping through integration of digital terrain models spectral sensing and photopedologyAerial photographsDigital terrain modelsSatellite imagesDigital soil mappingABSTRACTNew tools for soil mapping are needed to increase speed and accuracy of pedological mapping processes. This study integrated various technologies to map soils of the Piracicaba region in São Paulo State, Brazil. Each technology was expected to provide different information to design a detailed map. We carried out field survey and soil sampling for laboratory analysis. Initially, we conducted field visits to obtain soil patterns of a reference site. We applied the acquired patterns to an validation site, based solely on information obtained from remote sensing and cartographic databases, namely LANDSAT 7/ETM, digital elevation models (DEM) and aerial photographs. We integrated the information from each product to generate the map of the validation site, which was validated by field inspection. Textural classification using satellite imaging ranged from 21-51% of accuracy. Band 5 in the sensor showed the best performance to discriminate between clayey and sandy soils. Aerial photographs provided the best information because, besides their own inherent characteristics, they operate on a larger scale and result in a map with up to 50 polygons, while DEM reached a maximum of 30 polygons. The digital mapping technology generated 45 mapping units. Finally, the mapping efficiently separated the Latosols from the other classes; however, in some cases there was confusion in the identification of Cambisols and litholic Neosols.Universidade Federal do Ceará2015-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902015000400669Revista Ciência Agronômica v.46 n.4 2015reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFC10.5935/1806-6690.20150053info:eu-repo/semantics/openAccessDemattê,José A. M.Rizzo,RodneiBotteon,Victor Wilsoneng2015-09-30T00:00:00Zoai:scielo:S1806-66902015000400669Revistahttp://www.ccarevista.ufc.br/PUBhttps://old.scielo.br/oai/scielo-oai.php||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2015-09-30T00:00Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)false |
dc.title.none.fl_str_mv |
Pedological mapping through integration of digital terrain models spectral sensing and photopedology |
title |
Pedological mapping through integration of digital terrain models spectral sensing and photopedology |
spellingShingle |
Pedological mapping through integration of digital terrain models spectral sensing and photopedology Demattê,José A. M. Aerial photographs Digital terrain models Satellite images Digital soil mapping |
title_short |
Pedological mapping through integration of digital terrain models spectral sensing and photopedology |
title_full |
Pedological mapping through integration of digital terrain models spectral sensing and photopedology |
title_fullStr |
Pedological mapping through integration of digital terrain models spectral sensing and photopedology |
title_full_unstemmed |
Pedological mapping through integration of digital terrain models spectral sensing and photopedology |
title_sort |
Pedological mapping through integration of digital terrain models spectral sensing and photopedology |
author |
Demattê,José A. M. |
author_facet |
Demattê,José A. M. Rizzo,Rodnei Botteon,Victor Wilson |
author_role |
author |
author2 |
Rizzo,Rodnei Botteon,Victor Wilson |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Demattê,José A. M. Rizzo,Rodnei Botteon,Victor Wilson |
dc.subject.por.fl_str_mv |
Aerial photographs Digital terrain models Satellite images Digital soil mapping |
topic |
Aerial photographs Digital terrain models Satellite images Digital soil mapping |
description |
ABSTRACTNew tools for soil mapping are needed to increase speed and accuracy of pedological mapping processes. This study integrated various technologies to map soils of the Piracicaba region in São Paulo State, Brazil. Each technology was expected to provide different information to design a detailed map. We carried out field survey and soil sampling for laboratory analysis. Initially, we conducted field visits to obtain soil patterns of a reference site. We applied the acquired patterns to an validation site, based solely on information obtained from remote sensing and cartographic databases, namely LANDSAT 7/ETM, digital elevation models (DEM) and aerial photographs. We integrated the information from each product to generate the map of the validation site, which was validated by field inspection. Textural classification using satellite imaging ranged from 21-51% of accuracy. Band 5 in the sensor showed the best performance to discriminate between clayey and sandy soils. Aerial photographs provided the best information because, besides their own inherent characteristics, they operate on a larger scale and result in a map with up to 50 polygons, while DEM reached a maximum of 30 polygons. The digital mapping technology generated 45 mapping units. Finally, the mapping efficiently separated the Latosols from the other classes; however, in some cases there was confusion in the identification of Cambisols and litholic Neosols. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-12-01 |
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=S1806-66902015000400669 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902015000400669 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.5935/1806-6690.20150053 |
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 |
Universidade Federal do Ceará |
publisher.none.fl_str_mv |
Universidade Federal do Ceará |
dc.source.none.fl_str_mv |
Revista Ciência Agronômica v.46 n.4 2015 reponame:Revista ciência agronômica (Online) instname:Universidade Federal do Ceará (UFC) instacron:UFC |
instname_str |
Universidade Federal do Ceará (UFC) |
instacron_str |
UFC |
institution |
UFC |
reponame_str |
Revista ciência agronômica (Online) |
collection |
Revista ciência agronômica (Online) |
repository.name.fl_str_mv |
Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC) |
repository.mail.fl_str_mv |
||alekdutra@ufc.br|| ccarev@ufc.br |
_version_ |
1750297487978004480 |