A two-level random forest model for predicting the population distributions of urban functional zones: A case study in Changsha, China

•Two-level machine learning based on error compensation improves prediction accuracy.•Two-level random forest is better than the other two models.•Features related to interest points are more important in predicting distribution.•Variation of population density occurs in 203 single and 387 mixed functional zones.