Estimation of building-scale population density by using a dasymetric based interpolation method: A case study of Seoul metropolitan area

Keywords: Dasymetric mapping, population, COVID-19
Session Type: Virtual Paper Abstract
Day: Saturday
Session Start / End Time: 2/26/2022 08:00 AM (Eastern Time (US & Canada)) - 2/26/2022 09:20 AM (Eastern Time (US & Canada))
Room: Virtual 39

Abstract

COVID-19 is a respiratory disease that is transmitted through respiratory droplets and aerosols. Mostly, urban environment might be more susceptible to such disease because a number of buildings with large population are densely distributed. In particular, existing population in a building at a particular time is crucial for the quarantine. However, it is not easy to identify de facto population present in the building at a specific time. In this regard, this study attempts to estimate a detailed distribution of the living population in the buildings of the city using a dasymetric based interpolation method. Typically, a dasymetric based interpolation utilizes the ancillary data to estimate the spatial distribution of population at a finer scale. In this study, we take advantage of the integrated building information as new ancillary data for estimating the building-scale population density, particularly focusing on building usage. Specifically, regression approach is conducted to generate a set of weights for different usages of buildings by considering the total floor area. The empirical results present a more accurate estimation of population density at a finer scale, given the de facto population of the city.. The estimated living population at a building scale would be significantly used for the quarantine and effective responses from mass infected diseases like COVID19.