Application of building occupancy probabilities for bottom up population modeling across a heterogeneous urban area

Keywords: building occupancy estimates, uncertainty, population models, building purpose
Session Type: Virtual Paper Abstract
Day: Sunday
Session Start / End Time: 2/27/2022 08:00 AM (Eastern Time (US & Canada)) - 2/27/2022 09:20 AM (Eastern Time (US & Canada))
Room: Virtual 6

Abstract

Developing a bottom-up population modeling approach that accounts for uncertainty is vital for areas of the world that lack censuses or surveys of populations for reporting reliable and current population estimates. In addition, reporting population uncertainty estimates that account for data integrity. continue to be a research challenge. One such population learning approach accounts for uncertainty at the data input level and propagated through the modeling process is the Population Density Tables (PDT). PDT models activity and reports people/1000 sqft at the regional, national and subnational scales for night and day for over 50 facility types (Residential, Commercial, Transportation, Public Service, Retail/Service Outlets, Recreation/Entertainment and Agriculture). These activity spaces capture the probability of occupancy of a facility within a bounded area such as a country or administrative unit while agnostically incorporating open-source data at any spatial scale. The open-source data consists of censuses or surveys, humanitarian data and reports, commercial websites, real estate databases, news articles, and more that account for the area of a facility and the population (whether workers, visitors, enrollment, etc.). Spatial application of the PDT occupancy probabilities was performed in Osaka, Japan where the building purpose, floors, and area are known. We validated our population estimates and quantified uncertainty against governmental census, tourist and business traveler reported estimates. The discussion will include the results of the population estimates and uncertainty, validation, visualization of the results, and next steps in this research.