A geothermal heat flow model of Africa based on random forest regression - Al-Aghbary, M.; Sobh , M.; Gerhards , C. (Frontiers in Earth Science, 2022)
We generate a geothermal heat flow model over Africa using random forest regression based on sixteen different geophysical and geological quantities (among them are Moho depth, Curie temperature depth, gravity anomalies, topography, and seismic wave velocities). The training of the random forest is based on direct heat flow measurements collected in the compilation of Lucazeau (2019). The final model reveals structures that are consistent with existing regional geothermal heat flow information. It is interpreted with respect to the tectonic setup of Africa, and the influence of the selection of training data and target observables is illustrated in the supplementary material.