Data driven approach for high resolution population distribution and dynamics models

Budhendra L. Bhaduri; Edward A. Bright; Amy N. Rose; Cheng Liu; Marie L. Urban; Robert N. Stewart

doi:10.1109/WSC.2014.7019945

Data driven approach for high resolution population distribution and dynamics models

Budhendra L. Bhaduri, Edward A. Bright, Amy N. Rose, Cheng Liu, Marie L. Urban, Robert N. Stewart

Geoinformatics Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

High resolution population distribution data are vital for successfully addressing critical issues ranging from energy and socio-environmental research to public health to human security. Commonly available population data from Census is constrained both in space and time and does not capture population dynamics as functions of space and time. This imposes a significant limitation on the fidelity of event-based simulation models with sensitive space-time resolution. This paper describes ongoing development of high-resolution population distribution and dynamics models, at Oak Ridge National Laboratory, through spatial data integration and modeling with behavioral or activity-based mobility datasets for representing temporal dynamics of population. The model is resolved at 1 km resolution globally and describes the U.S. population for nighttime and daytime at 90m. Integration of such population data provides the opportunity to develop simulations and applications in critical infrastructure management from local to global scales.

Original language	English
Title of host publication	Proceedings of the 2014 Winter Simulation Conference, WSC 2014
Editors	Andreas Tolk, Levent Yilmaz, Saikou Y. Diallo, Ilya O. Ryzhov
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	842-850
Number of pages	9
ISBN (Electronic)	9781479974863
DOIs	https://doi.org/10.1109/WSC.2014.7019945
State	Published - Jan 23 2015
Event	2014 Winter Simulation Conference, WSC 2014 - Savannah, United States Duration: Dec 7 2014 → Dec 10 2014

Publication series

Name	Proceedings - Winter Simulation Conference
Volume	2015-January
ISSN (Print)	0891-7736

Conference

Conference	2014 Winter Simulation Conference, WSC 2014
Country/Territory	United States
City	Savannah
Period	12/7/14 → 12/10/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/WSC.2014.7019945

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Bhaduri, B. L., Bright, E. A., Rose, A. N., Liu, C., Urban, M. L., & Stewart, R. N. (2015). Data driven approach for high resolution population distribution and dynamics models. In A. Tolk, L. Yilmaz, S. Y. Diallo, & I. O. Ryzhov (Eds.), Proceedings of the 2014 Winter Simulation Conference, WSC 2014 (pp. 842-850). Article 7019945 (Proceedings - Winter Simulation Conference; Vol. 2015-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2014.7019945

Bhaduri, Budhendra L. ; Bright, Edward A. ; Rose, Amy N. et al. / Data driven approach for high resolution population distribution and dynamics models. Proceedings of the 2014 Winter Simulation Conference, WSC 2014. editor / Andreas Tolk ; Levent Yilmaz ; Saikou Y. Diallo ; Ilya O. Ryzhov. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 842-850 (Proceedings - Winter Simulation Conference).

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title = "Data driven approach for high resolution population distribution and dynamics models",

abstract = "High resolution population distribution data are vital for successfully addressing critical issues ranging from energy and socio-environmental research to public health to human security. Commonly available population data from Census is constrained both in space and time and does not capture population dynamics as functions of space and time. This imposes a significant limitation on the fidelity of event-based simulation models with sensitive space-time resolution. This paper describes ongoing development of high-resolution population distribution and dynamics models, at Oak Ridge National Laboratory, through spatial data integration and modeling with behavioral or activity-based mobility datasets for representing temporal dynamics of population. The model is resolved at 1 km resolution globally and describes the U.S. population for nighttime and daytime at 90m. Integration of such population data provides the opportunity to develop simulations and applications in critical infrastructure management from local to global scales.",

author = "Bhaduri, {Budhendra L.} and Bright, {Edward A.} and Rose, {Amy N.} and Cheng Liu and Urban, {Marie L.} and Stewart, {Robert N.}",

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doi = "10.1109/WSC.2014.7019945",

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Bhaduri, BL, Bright, EA, Rose, AN, Liu, C, Urban, ML & Stewart, RN 2015, Data driven approach for high resolution population distribution and dynamics models. in A Tolk, L Yilmaz, SY Diallo & IO Ryzhov (eds), Proceedings of the 2014 Winter Simulation Conference, WSC 2014., 7019945, Proceedings - Winter Simulation Conference, vol. 2015-January, Institute of Electrical and Electronics Engineers Inc., pp. 842-850, 2014 Winter Simulation Conference, WSC 2014, Savannah, United States, 12/7/14. https://doi.org/10.1109/WSC.2014.7019945

Data driven approach for high resolution population distribution and dynamics models. / Bhaduri, Budhendra L.; Bright, Edward A.; Rose, Amy N. et al.
Proceedings of the 2014 Winter Simulation Conference, WSC 2014. ed. / Andreas Tolk; Levent Yilmaz; Saikou Y. Diallo; Ilya O. Ryzhov. Institute of Electrical and Electronics Engineers Inc., 2015. p. 842-850 7019945 (Proceedings - Winter Simulation Conference; Vol. 2015-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - High resolution population distribution data are vital for successfully addressing critical issues ranging from energy and socio-environmental research to public health to human security. Commonly available population data from Census is constrained both in space and time and does not capture population dynamics as functions of space and time. This imposes a significant limitation on the fidelity of event-based simulation models with sensitive space-time resolution. This paper describes ongoing development of high-resolution population distribution and dynamics models, at Oak Ridge National Laboratory, through spatial data integration and modeling with behavioral or activity-based mobility datasets for representing temporal dynamics of population. The model is resolved at 1 km resolution globally and describes the U.S. population for nighttime and daytime at 90m. Integration of such population data provides the opportunity to develop simulations and applications in critical infrastructure management from local to global scales.

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Bhaduri BL, Bright EA, Rose AN, Liu C, Urban ML, Stewart RN. Data driven approach for high resolution population distribution and dynamics models. In Tolk A, Yilmaz L, Diallo SY, Ryzhov IO, editors, Proceedings of the 2014 Winter Simulation Conference, WSC 2014. Institute of Electrical and Electronics Engineers Inc. 2015. p. 842-850. 7019945. (Proceedings - Winter Simulation Conference). doi: 10.1109/WSC.2014.7019945

Data driven approach for high resolution population distribution and dynamics models

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