Doctoral Dissertation Research: Mapping and Estimating the Daily Space-Time Dynamics of Urban Population Distribution

University Of Georgia Research Foundation Inc, Athens GA

Investigators

Abstract

Population census data are collected on the de jure method in the U.S., which assigns persons according to their usual place of residence. This means that the census data do not necessarily reflect where people actually are during a day. In this doctoral dissertation research project, census population is referred to as nighttime population, which reflects where people live, to distinguish it from the daytime population, which more correctly reflects where people work, study, play, and shop. The doctoral candidate conducting this project will attempt to estimate and map the daily movements of daytime population using grid-based population density surface modeling and spatial interpolation with the aid of geographic information system (GIS) techniques for data integration. The student will employ areal interpolation, temporal interpolation, and dasymetric mapping theories to provide the underpinning for accurate population estimation at the hourly basis for the Atlanta metropolitan area in northern Georgia. In order to achieve these objectives, a large variety of data will be used, including data on journey to work from the Census Transportation Planning Package (CTPP), daily human activities from the survey results of the National Human Activity Survey (NHAPS), and firm-level employment data encoded by point locations. To map the daily dynamics of population distribution changes, the NHAPS data also will be used to produce collective diary for each of the distinctive population subgroups. The raster-based National Land Cover Data (NLCD) will be used in conjunction with the point-based business location data and daily commuting flow from the Census Transportation Planning Package (CTPP) data to locate the daily human activities and to produce a series of hour-based population density surfaces. The mapping and estimation produced will be verified by the field survey. This project will contribute to the production of a prototype real-time population estimation system that can be used to estimate the population in a particular part of the city at any specified time. Such information is particularly useful to local government agencies for emergency evacuation purposes and for transportation planning. The project will contribute to the use of GIS in the integration of space and time using areal interpolation, temporal interpolation and dasymetric mapping for mapping and estimating population mobility in a large metropolitan area. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.