Building-level Estimation of Workplace Population using Household Travel Survey Data

Abstract

Recently, individual-level analysis and demand for fine-scale spatial data have increased, but most of the currently accessible data is aggregated on the basis of administrative units. In order to overcome these difficulties associated with data procurement, this study proposes a method to generate fine-scale spatial data by integrating easily accessible open data. The building selection algorithm that estimates the destination of a trip by building unit is based on areal interpolation and dasymetric mapping. The weights for the building selection process are derived from various ancillary data. The results showed that the proposed algorithm is more accurate than the existing interpolation method. This study suggests a new population estimation model based on trip records and has a significance in that high-resolution data is generated by combining various easily accessible data.