Articles | Volume 14, issue 3
Model evaluation paper
16 Mar 2021
Model evaluation paper |  | 16 Mar 2021

Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China

Batunacun, Ralf Wieland, Tobia Lakes, and Claas Nendel


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Katja Gänger on behalf of the Authors (28 Oct 2020)  Author's response
ED: Publish subject to technical corrections (10 Nov 2020) by David Topping
AR by Batunacun Ba on behalf of the Authors (18 Nov 2020)  Author's response    Manuscript
Short summary
Extreme gradient boosting (XGBoost) can provide alternative insights that conventional land-use models are unable to generate. Shapley additive explanations (SHAP) can interpret the results of the purely data-driven approach. XGBoost achieved similar and robust simulation results. SHAP values were useful for analysing the complex relationship between the different drivers of grassland degradation.