Population synthesis handling three geographical resolutions

Ana Tsui Moreno, Rolf Moeckel

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

In this paper, we develop a synthetic population as the first step in implementing an integrated land use/transport model. The model is agent-based, where every household, person, dwelling, and job is treated as an individual object. Therefore, detailed socioeconomic and demographic attributes are required to support the model. The Iterative Proportional Updating (IPU) procedure is selected for the optimization phase. The original IPU algorithm has been improved to handle three geographical resolutions simultaneously with very little computational time. For the allocation phase, we use Monte Carlo sampling. We applied our approach to the greater Munich metropolitan area. Based on the available data in the control totals and microdata, we selected 47 attributes at the municipality level, 13 attributes at the county level, and 14 additional attributes at the borough level for the city of Munich. Attributes are aggregated at the household, dwelling, and person level. The algorithm is able to synthesize 4.5 million persons in 2.1 million households in less than 1.5 h. Directions regarding how to handle multiple geographical resolutions and how to balance the amount and order of attributes to avoid overfitting are presented.

Original languageEnglish
Article number174
JournalISPRS International Journal of Geo-Information
Volume7
Issue number5
DOIs
StatePublished - May 2018

Keywords

  • Agent based
  • Microscopic land use model
  • Population synthesis
  • Travel demand

Fingerprint

Dive into the research topics of 'Population synthesis handling three geographical resolutions'. Together they form a unique fingerprint.

Cite this