|
|
Registros recuperados : 4 | |
1. | | CLUZEAU, D.; PÉRÈS, G.; MERCIER, V.; BISPO, A.; ARROUAYS, D.; WALTER, C.; CORTET, J.; VILLENAVE, C.; RUIZ, N.; RANJARD, L.; CHAUSSOD, R.; CANNAVACCIUOLO, M.; ROUGÉ, L.; JOLIVET, C.; FARGETTE, M.; MATEILLE, T.; LAVELLE, P.; LERMERCIER-FOUCAULT, B.; DUBS, F.; MARTIN-LAURENT, F.; VELASQUEZ, E.; BELLIDO, A.; GUERNION, M.; PONGE, J. F. Procedures and protocol for soil biodiversity monitoring: "RMQSBiodiv", a French Pilot area experience. In: INTERNATIONAL COLLOQUIUM ON SOIL ZOOLOGY, 15; INTERNATIONAL COLLOQUIUM ON APTERYGOTA, 12., 2008, Curitiba. Biodiversity, conservation and sustainabele management of soil animal: abstracts. Colombo: Embrapa Florestas. Editors: George Gardner Brown; Klaus Dieter Sautter; Renato Marques; Amarildo Pasini. 1 CD-ROM. Biblioteca(s): Embrapa Florestas. |
| |
2. | | CLUZEAU, D.; PÉRES, G.; CANNAVACCIUOLO, M.; BELLIDO, A.; GUERNION, M. RUIZ, N.; CORTET, J.; MATEILLE, T.; MARTIN-LAURENT, F.; VELASQUEZ, E.; MERCIER, V.; BISPO, A.; VILLENAVE, C.; RANJARD, L.; CHAUSSOD, R.; ROUGÉ, l.; JOLIVET, C.; LERMERCIER-FOUCAULT, B.; PONGE, J. F. How to manage and analyse a large biodiversity data set: the case of the regional "RMQS BioDiv" experience ? In: INTERNATIONAL COLLOQUIUM ON SOIL ZOOLOGY, 15; INTERNATIONAL COLLOQUIUM ON APTERYGOTA, 12., 2008, Curitiba. Biodiversity, conservation and sustainabele management of soil animal: abstracts. Colombo: Embrapa Florestas. Editors: George Gardner Brown; Klaus Dieter Sautter; Renato Marques; Amarildo Pasini. 1 CD-ROM. Biblioteca(s): Embrapa Florestas. |
| |
3. | | PÉRÈS, G.; CLUZEAU, D.; CHAUSSOD, R.; CORTET, J.; FARGETTE, M.; MATEILLE, T.; PONGE, J. F.; RANJARD, L.; RUIZ, N.; VILLENAVE, C.; MERCIER, C.; BISPO, A.; ARROUAYS, D.; WALTER, C.; CANNAVACIUOLO, M.; ROUGÉ, L.; JOLIVET, C.; LAVELLE, P.; LERMERCIER-FOUCAULT, B.; DUBS, F.; MARTIN-LAURENT, F.; VELASQUEZ, E.; BELLIDO, A.; GUERNION, M. Relevance of different soil fauna and microflora groups in the monitoring of soil biodiversity: RMQS-Biodiv, a french Pilote area experience. In: INTERNATIONAL COLLOQUIUM ON SOIL ZOOLOGY, 15; INTERNATIONAL COLLOQUIUM ON APTERYGOTA, 12., 2008, Curitiba. Biodiversity, conservation and sustainabele management of soil animal: abstracts. Colombo: Embrapa Florestas. Editors: George Gardner Brown; Klaus Dieter Sautter; Renato Marques; Amarildo Pasini. 1 CD-ROM. Biblioteca(s): Embrapa Florestas. |
| |
4. | | CANNAVACCIUOLO, M.; BELLIDO, A.; CLUZEAU, D.; ROUGÉ, L.; PÉRÈS, G.; JOLIVET, C.; FARGETTE, M.; MATEILLE, T.; LERMERCIER-FOUCAULT, B.; DUBS, F.; MERCIER, V.; ARROUAYS, D.; CORTET, J.; VILLENAVE, C.; RUIZ, N.; RANJARD, L.; CHAUSSOD, R.; MARTIN-LAURENT, F.; VELASQUEZ, E.; GUERNION, M.; PONGE, J. F. DONECOSOL: a software tool to manage biodiversity's data. In: INTERNATIONAL COLLOQUIUM ON SOIL ZOOLOGY, 15; INTERNATIONAL COLLOQUIUM ON APTERYGOTA, 12., 2008, Curitiba. Biodiversity, conservation and sustainabele management of soil animal: abstracts. Colombo: Embrapa Florestas. Editors: George Gardner Brown; Klaus Dieter Sautter; Renato Marques; Amarildo Pasini. 1 CD-ROM. Biblioteca(s): Embrapa Florestas. |
| |
Registros recuperados : 4 | |
|
|
| Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Solos. |
Data corrente: |
01/12/2017 |
Data da última atualização: |
10/11/2021 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
PINHEIRO, H. S. K.; OWENS, P. R.; ANJOS, L. H. C.; CARVALHO JUNIOR, W. de; CHAGAS, C. da S. |
Afiliação: |
H. S. K. PINHEIRO, UFRRJ; P. R. OWENS, USDA Dale Bumpers Small Farms Research Center; L. H. C. ANJOS, UFRRJ; WALDIR DE CARVALHO JUNIOR, CNPS; CESAR DA SILVA CHAGAS, CNPS. |
Título: |
Tree-based techniques to predict soil units. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
Soil Research, v. 55, n. 8, p. 788-798, 2017. |
DOI: |
https://doi.org/10.1071/SR16060 |
Idioma: |
Inglês |
Conteúdo: |
Quantitative soil-landscape models offer a method for conducting soil surveys that use statistical tools to predict natural patterns in the occurrence of particular map units across a landscape. The aim of the present study was to predict soil units in a watershed with wide variation in landscape conditions. The approach relied on a modelling of soil-forming factors in order to understand the variability of the landscape components in the region. Models were generated for landscape attributes related to pedogenesis, specifically elevation, slope, curvature, compound topographic index, Euclidean distance from stream networks, landforms map, clay minerals index, iron oxide index and normalised difference vegetation index, along with an existing geology map. The soil classification was adapted from the World Reference Base System for Soil Resources, and the predominant soil taxonomic orders observed were Ferrasols, Acrisols, Gleysols, Cambisols, Fluvisols and Regosols. The algorithms used to predict the soil units were based on decision tree (DT) and random forest (RF) methods. The criteria used to evaluate the models' performance were statistical indices, coherence between predicted units and the legacy map, as well as accuracy checks based on control samples. The best performing model was found to be the RF algorithm, with resulting statistical indices considered excellent (overall = 0.966, kappa = 0.962). The accuracy of the map as determined by control points was 67.89%, with a kappa value of 61.39%. MenosQuantitative soil-landscape models offer a method for conducting soil surveys that use statistical tools to predict natural patterns in the occurrence of particular map units across a landscape. The aim of the present study was to predict soil units in a watershed with wide variation in landscape conditions. The approach relied on a modelling of soil-forming factors in order to understand the variability of the landscape components in the region. Models were generated for landscape attributes related to pedogenesis, specifically elevation, slope, curvature, compound topographic index, Euclidean distance from stream networks, landforms map, clay minerals index, iron oxide index and normalised difference vegetation index, along with an existing geology map. The soil classification was adapted from the World Reference Base System for Soil Resources, and the predominant soil taxonomic orders observed were Ferrasols, Acrisols, Gleysols, Cambisols, Fluvisols and Regosols. The algorithms used to predict the soil units were based on decision tree (DT) and random forest (RF) methods. The criteria used to evaluate the models' performance were statistical indices, coherence between predicted units and the legacy map, as well as accuracy checks based on control samples. The best performing model was found to be the RF algorithm, with resulting statistical indices considered excellent (overall = 0.966, kappa = 0.962). The accuracy of the map as determined by control points was 67.89%, wi... Mostrar Tudo |
Palavras-Chave: |
Mapeamento digital do solo. |
Thesagro: |
Classificação do Solo; Pedologia. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 02162naa a2200217 a 4500 001 2081200 005 2021-11-10 008 2017 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1071/SR16060$2DOI 100 1 $aPINHEIRO, H. S. K. 245 $aTree-based techniques to predict soil units.$h[electronic resource] 260 $c2017 520 $aQuantitative soil-landscape models offer a method for conducting soil surveys that use statistical tools to predict natural patterns in the occurrence of particular map units across a landscape. The aim of the present study was to predict soil units in a watershed with wide variation in landscape conditions. The approach relied on a modelling of soil-forming factors in order to understand the variability of the landscape components in the region. Models were generated for landscape attributes related to pedogenesis, specifically elevation, slope, curvature, compound topographic index, Euclidean distance from stream networks, landforms map, clay minerals index, iron oxide index and normalised difference vegetation index, along with an existing geology map. The soil classification was adapted from the World Reference Base System for Soil Resources, and the predominant soil taxonomic orders observed were Ferrasols, Acrisols, Gleysols, Cambisols, Fluvisols and Regosols. The algorithms used to predict the soil units were based on decision tree (DT) and random forest (RF) methods. The criteria used to evaluate the models' performance were statistical indices, coherence between predicted units and the legacy map, as well as accuracy checks based on control samples. The best performing model was found to be the RF algorithm, with resulting statistical indices considered excellent (overall = 0.966, kappa = 0.962). The accuracy of the map as determined by control points was 67.89%, with a kappa value of 61.39%. 650 $aClassificação do Solo 650 $aPedologia 653 $aMapeamento digital do solo 700 1 $aOWENS, P. R. 700 1 $aANJOS, L. H. C. 700 1 $aCARVALHO JUNIOR, W. de 700 1 $aCHAGAS, C. da S. 773 $tSoil Research$gv. 55, n. 8, p. 788-798, 2017.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Solos (CNPS) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Nenhum registro encontrado para a expressão de busca informada. |
|
|