The Sloping Mire Soil-Landscape of Southern Ecuador : Influence of Predictor Resolution and Model Tuning on Random Forest Predictions
Joint Authors
Hitziger, Martin
Ließ, Mareike
Huwe, Bernd
Source
Applied and Environmental Soil Science
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-05
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Earth Science , Water and Environment
Abstract EN
The sloping mire landscape of the investigation area, in the southern Andes of Ecuador, is dominated by stagnic soils with thick organic layers.
The recursive partitioning algorithm Random Forest was used to predict the spatial water stagnation pattern and the thickness of the organic layer from terrain attributes.
Terrain smoothing from 10 to 30 m raster resolution was applied in order to obtain the best possible model.
For the same purpose, several model tuning parameters were tested and a prepredictor selection with the R-package Boruta was applied.
Model versions were evaluated and compared by 100 repetitions of the calculation of the residual mean square error of a five-fold cross-validation.
Position specific density functions of the predicted soil parameters were then used to display prediction uncertainty.
Prepredictor selection and tuning of the Random Forest algorithm in some cases resulted in an improved model performance.
We therefore recommend testing prepredictor selection and tuning to make sure that the best possible model is chosen.
This needs particular emphasis in complex tropical mountain soil-landscapes which provide a real challenge to any soil mapping approach but where Random Forest has proven to be successful due to the testing of model tuning and prepredictor selection.
American Psychological Association (APA)
Ließ, Mareike& Hitziger, Martin& Huwe, Bernd. 2014. The Sloping Mire Soil-Landscape of Southern Ecuador : Influence of Predictor Resolution and Model Tuning on Random Forest Predictions. Applied and Environmental Soil Science،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-484261
Modern Language Association (MLA)
Ließ, Mareike…[et al.]. The Sloping Mire Soil-Landscape of Southern Ecuador : Influence of Predictor Resolution and Model Tuning on Random Forest Predictions. Applied and Environmental Soil Science No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-484261
American Medical Association (AMA)
Ließ, Mareike& Hitziger, Martin& Huwe, Bernd. The Sloping Mire Soil-Landscape of Southern Ecuador : Influence of Predictor Resolution and Model Tuning on Random Forest Predictions. Applied and Environmental Soil Science. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-484261
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-484261