Investigation on Small-area Population Estimation Based on Building Extraction
基于建筑物提取的精细尺度人口估算研究

In order to estimate the population of small area,a new population estimation method based on residential building attributes is presented.Firstly,buildings are extracted combining LiDAR data with high-resolution remote sensing images,using Dempster-Shafer theory of evidence.Then,all the non-residential buildings are excluded from extraction results according to land use classification map,and the population estimation model is generated by optimization choice of geometric attributes of residential buildings,such as building counts,building areas,and building volumes,based on linear regression method.The results demonstrated that proposed model yielded good small\|area population estimation results,and the proposed method improved the precision and automatic of population estimation.