Modeling population density using land cover data

This study investigates the correlation between land cover data and other factors that affect population distribution. The results show that land cover data contain sufficient information to infer population distribution and can be used independently to model the spatial pattern of population density in China. Chinaʹs population distribution model (CPDM) was developed based on land cover data to calculate population density in China at 1 km resolution. For cells in rural areas, population probability coefficients were calculated based on weighted linear models, the weights of land cover types being derived from multivariate regression models and on a qualitative order of land types in 12 agro-ecological zones. For cells in urban areas, a power exponential decay model based on city size and the distance from urban center was employed to calculate population probability coefficients. The models were validated in sampled cells using ancillary population data. The validation shows the mean relative error of estimated population to be 3.13 and 5.26% in rural and urban areas, respectively. Compared to existing models, the accuracy of CPDM is much higher at cell, county and province scales.