| Registro completo |
| Provedor de dados: |
PAB
|
| País: |
Brazil
|
| Título: |
Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density
|
| Autores: |
Sarmento,Eliana Casco
Giasson,Elvio
Weber,Eliseu
Flores,Carlos Alberto
Hasenack,Heinrich
|
| Data: |
2012-09-01
|
| Ano: |
2012
|
| Palavras-chave: |
Appellation of origin
Decision tree
Digital elevation model
Geographic information systems
Neural network
Soil mapping
|
| Resumo: |
The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.
|
| Tipo: |
Info:eu-repo/semantics/article
|
| Idioma: |
Inglês
|
| Identificador: |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2012000900025
|
| Editor: |
Embrapa Secretaria de Pesquisa e Desenvolvimento
Pesquisa Agropecuária Brasileira
|
| Relação: |
10.1590/S0100-204X2012000900025
|
| Formato: |
text/html
|
| Fonte: |
Pesquisa Agropecuária Brasileira v.47 n.9 2012
|
| Direitos: |
info:eu-repo/semantics/openAccess
|
|
