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| Souza,Eliana de; Fernandes Filho,Elpídio Inácio; Schaefer,Carlos Ernesto Gonçalves Reynaud; Batjes,Niels H.; Santos,Gerson Rodrigues dos; Pontes,Lucas Machado. |
| ABSTRACT Soil bulk density (ρb) data are needed for a wide range of environmental studies. However, ρb is rarely reported in soil surveys. An alternative to obtain ρb for data-scarce regions, such as the Rio Doce basin in southeastern Brazil, is indirect estimation from less costly covariates using pedotransfer functions (PTF). This study primarily aims to develop region-specific PTFs for ρb using multiple linear regressions (MLR) and random forests (RF). Secondly, it assessed the accuracy of PTFs for data grouped into soil horizons and soil classes. For that purpose, we compared the performance of PTFs compiled from the literature with those developed here. Two groups of data were evaluated as covariates: 1) readily available soil properties and 2) maps... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Multiple linear regressions; Random forests; Soil predictors; Spatial prediction. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162016000600525 |
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