Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils

Detalhes bibliográficos
Autor(a) principal: Alves,Marcelo Rodrigo
Data de Publicação: 2015
Outros Autores: Demattê,José A. M., Barros,Pedro Paulo Silva
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Ciência do Solo (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832015000501261
Resumo: ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).
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spelling Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soilssoil spectral behaviorterrain featuresremote sensingABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).Sociedade Brasileira de Ciência do Solo2015-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-06832015000501261Revista Brasileira de Ciência do Solo v.39 n.5 2015reponame:Revista Brasileira de Ciência do Solo (Online)instname:Sociedade Brasileira de Ciência do Solo (SBCS)instacron:SBCS10.1590/01000683rbcs20140410info:eu-repo/semantics/openAccessAlves,Marcelo RodrigoDemattê,José A. M.Barros,Pedro Paulo Silvaeng2015-12-04T00:00:00Zoai:scielo:S0100-06832015000501261Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=0100-0683&lng=es&nrm=isohttps://old.scielo.br/oai/scielo-oai.php||sbcs@ufv.br1806-96570100-0683opendoar:2015-12-04T00:00Revista Brasileira de Ciência do Solo (Online) - Sociedade Brasileira de Ciência do Solo (SBCS)false
dc.title.none.fl_str_mv Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils
title Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils
spellingShingle Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils
Alves,Marcelo Rodrigo
soil spectral behavior
terrain features
remote sensing
title_short Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils
title_full Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils
title_fullStr Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils
title_full_unstemmed Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils
title_sort Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils
author Alves,Marcelo Rodrigo
author_facet Alves,Marcelo Rodrigo
Demattê,José A. M.
Barros,Pedro Paulo Silva
author_role author
author2 Demattê,José A. M.
Barros,Pedro Paulo Silva
author2_role author
author
dc.contributor.author.fl_str_mv Alves,Marcelo Rodrigo
Demattê,José A. M.
Barros,Pedro Paulo Silva
dc.subject.por.fl_str_mv soil spectral behavior
terrain features
remote sensing
topic soil spectral behavior
terrain features
remote sensing
description ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).
publishDate 2015
dc.date.none.fl_str_mv 2015-10-01
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dc.language.iso.fl_str_mv eng
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dc.relation.none.fl_str_mv 10.1590/01000683rbcs20140410
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dc.publisher.none.fl_str_mv Sociedade Brasileira de Ciência do Solo
publisher.none.fl_str_mv Sociedade Brasileira de Ciência do Solo
dc.source.none.fl_str_mv Revista Brasileira de Ciência do Solo v.39 n.5 2015
reponame:Revista Brasileira de Ciência do Solo (Online)
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