Preprints
https://doi.org/10.5194/egusphere-2024-138
https://doi.org/10.5194/egusphere-2024-138
24 Jan 2024
 | 24 Jan 2024

Random forests with spatial proxies for environmental modelling: opportunities and pitfalls

Carles Milà, Marvin Ludwig, Edzer Pebesma, Cathryn Tonne, and Hanna Meyer

Abstract. Spatial proxies such as coordinates and Euclidean distance fields are often added as predictors in random forest models; however, their suitability in different predictive conditions has not yet been thoroughly assessed. We investigated 1) the conditions under which spatial proxies are suitable, 2) the reasons for such adequacy, and 3) how proxy suitability can be assessed using cross-validation.

In a simulation and two case studies, we found that adding spatial proxies improved model performance when both residual spatial autocorrelation, and regularly or randomly-distributed training samples, were present. Otherwise, inclusion of proxies was neutral or counterproductive and resulted in feature extrapolation for clustered samples. Random k-fold cross-validation systematically favoured models with spatial proxies even when not appropriate.

As the benefits of spatial proxies are not universal, we recommend using spatial exploratory and validation analyses to determine their suitability, and considering alternative inherently spatial RF-GLS models.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Carles Milà, Marvin Ludwig, Edzer Pebesma, Cathryn Tonne, and Hanna Meyer

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-138', Anonymous Referee #1, 07 Feb 2024
  • RC2: 'Comment on egusphere-2024-138', Carsten F. Dormann, 07 Feb 2024
  • AC1: 'Comment on egusphere-2024-138', Carles Milà, 02 May 2024

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-138', Anonymous Referee #1, 07 Feb 2024
  • RC2: 'Comment on egusphere-2024-138', Carsten F. Dormann, 07 Feb 2024
  • AC1: 'Comment on egusphere-2024-138', Carles Milà, 02 May 2024
Carles Milà, Marvin Ludwig, Edzer Pebesma, Cathryn Tonne, and Hanna Meyer

Data sets

Code and data for "Random forests with spatial proxies for environmental modelling: opportunities and pitfalls" Carles Milà https://zenodo.org/records/10495235

Carles Milà, Marvin Ludwig, Edzer Pebesma, Cathryn Tonne, and Hanna Meyer

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Short summary
Spatial proxies such as coordinates and distances are often included as predictors in random forest models for predictive mapping. In a simulation and two case studies, we investigated under which conditions this is appropriate. We found that spatial proxies are not always beneficial and thus we conclude that they should not be used as default approach without careful consideration. We also give insights on the reasons behind their suitability, how to detect it, and potential alternatives.