Spatial prediction of soil properties in two contrasting physiographic regions in Brazil
Michele Duarte de Menezes; Sérgio Henrique Godinho Silva; Carlos Rogério de Mello; Phillip Owens; Nilton Curi · 2016 · Scientia Agricola
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
This study compared the performance of ordinary kriging (OK) and regression kriging (RK) to predict soil physical-chemical properties in topsoil (0-15 cm). Mean prediction of error and root mean square of prediction error were used to assess the prediction methods. Two watersheds with contrasting soil-landscape features were studied, for which the prediction methods were performed differently. A multiple linear stepwise regression model was performed with RK using digital terrain models (DTMs) and remote sensing images in order to choose the best auxiliary covariates. Different pedogenic facto
Abstract by Michele Duarte de Menezes; Sérgio Henrique Godinho Silva; Carlos Rogério de Mello; Phillip Owens; Nilton Curi, Scientia Agricola (2016) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1590/0103-9016-2015-0071