Fine-scale urban grid population data is obtained by fusing data from multiple sources,yet factors like sampling bias,spatial coverage,and temporality of input data often lead to population esti-mation errors.To address these issues,an urban population mapping method based on WiFi data is de-signed,with Zhengzhou city area as the study region.A population attraction indicator model is con-structed by integrating point of interest(POI)data with WiFi data sourced from ad tech ecosystems.Population mapping experiments are then conducted using two models:random forest and geographi-cally weighted regression,to produce 100 m resolution urban grid population data.The results indicate significant improvement in the accuracy of grid population data generated by using the proposed meth-odology,validating the effectiveness of the population attractiveness indicator.The study area exhibits a typical"core-edge"urban population distribution structure with decreasing circles.At the township/street level accuracy assessment,the method demonstrates numerically lower accuracy errors com-pared to publicly available datasets such as WorldPop and LandScan.
WiFi datapoint of interestpopulation mappingpopulation attraction indicatorspopu-lation distribution pattern
维普
万方数据
