Next Article in Journal
Study on Multi-Scale Window Determination for GLCM Texture Description in High-Resolution Remote Sensing Image Geo-Analysis Supported by GIS and Domain Knowledge
Previous Article in Journal
Stakeholder Specific Multi-Scale Spatial Representation of Urban Building-Stocks
Open AccessArticle

Population Synthesis Handling Three Geographical Resolutions

Department of Civil, Geo and Environmental Engineering, Technical University of Munich; Arcisstr. 21, 80333 Munich, Germany
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(5), 174; https://doi.org/10.3390/ijgi7050174
Received: 4 April 2018 / Revised: 26 April 2018 / Accepted: 30 April 2018 / Published: 4 May 2018
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. View Full-Text
Keywords: population synthesis; microscopic land use model; travel demand; agent based population synthesis; microscopic land use model; travel demand; agent based
Show Figures

Figure 1

MDPI and ACS Style

Moreno, A.T.; Moeckel, R. Population Synthesis Handling Three Geographical Resolutions. ISPRS Int. J. Geo-Inf. 2018, 7, 174.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop