Estimating work and home population using lidar-derived building volumes

Yun Zhao, Gustavo A. Ovando-Montejo, Amy E. Frazier, Adam J. Mathews, K. Colton Flynn, Emily A. Ellis

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

As urban populations rapidly rise worldwide, it is increasingly necessary to determine the accurate distribution and configuration of the population in order to appropriate resources and services. Census-based methods for obtaining population counts are time consuming, labour intensive, and costly. Researchers have turned to remote sensing to estimate population from aerial and satellite datasets including lidar, which allows measures of building volume to be incorporated into population estimates. However, studies using lidar-derived building volumes have noted inconsistencies between population and building volume estimates in certain areas. In this article, we investigate this issue by incorporating both static and ambient population data into models using the US Census Bureau’s Longitudinal Employer-Household Dynamics (LEHD) database. To do this, we first develop a normalized home–work index to classify census blocks as primarily work-oriented, home-oriented, or mixed-use based on the LEHD data. We then employ ordinary least squares and geographically weighted regression (GWR) to explore the relationships between the different population groups (work, home, and mixed) and lidar-derived building volumes. We test these relationships across four diverse cities in Texas: Austin, Dallas, Houston, and San Antonio. Results suggest non-stationarity in the relationship between building volume and population with stronger, positive relationships in home-oriented and mixed-use blocks where the amount of building volume per person may be more consistent compared to work-oriented blocks. GWR models yielded high R 2 values (0.9), particularly in mixed-use areas, indicating the potential for predictive relationships.

Original languageEnglish (US)
Pages (from-to)1180-1196
Number of pages17
JournalInternational Journal of Remote Sensing
Volume38
Issue number4
DOIs
StatePublished - Feb 16 2017
Externally publishedYes

Fingerprint

lidar
census
urban population
labor
remote sensing
resource
household

Keywords

  • building volume
  • city-wide
  • Diurnal population
  • lidar
  • urban

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Cite this

Estimating work and home population using lidar-derived building volumes. / Zhao, Yun; Ovando-Montejo, Gustavo A.; Frazier, Amy E.; Mathews, Adam J.; Flynn, K. Colton; Ellis, Emily A.

In: International Journal of Remote Sensing, Vol. 38, No. 4, 16.02.2017, p. 1180-1196.

Research output: Contribution to journalArticle

Zhao, Yun ; Ovando-Montejo, Gustavo A. ; Frazier, Amy E. ; Mathews, Adam J. ; Flynn, K. Colton ; Ellis, Emily A. / Estimating work and home population using lidar-derived building volumes. In: International Journal of Remote Sensing. 2017 ; Vol. 38, No. 4. pp. 1180-1196.
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