Local Population Mapping Using a Random Forest Model Based on Remote and Social Sensing Data: A Case Study in Zhengzhou, China
High-resolution gridded population data are important for understanding and responding to many socioeconomic and environmental problems.Local estimates of the population allow officials and researchers to make a better local planning (e.g., optimizing public services and facilities).This study used a random forest algorithm, on the basis of remote