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. 2022 Sep 29;12:16349. doi: 10.1038/s41598-022-20347-9

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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(Left panel) Shapley values for wildfire occurrence prediction. On the y-axis, the features are sorted by decreasing importance while the x-axis shows the SHAP value distribution and denotes whether a variable contributes to reduce or to increase the fire probability. Gradient colors indicate the original value for that variable. Each point represents a row from the original dataset. (Right panel) Fire Weather Index (FWI) Shapley values. For sake of readability, SHAP values exceeding the [− 0.2, 0.2] range were assigned the same colors of extreme points of the chosen interval. The map was produced by using the plot.raster function from "raster" R package.