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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.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
Work for Others (WFO)
OSTI Identifier:
1185543
DOE Contract Number:
AC05-00OR22725
Resource Type:
Conference
Resource Relation:
Conference: Winter Simulation Conference 2014, Savannah, GA, USA, 20141207, 20141210
Country of Publication:
United States
Language:
English
Subject:
LandScan; LandScan USA; Population; GIS

Citation Formats

Bhaduri, Budhendra L, Bright, Eddie A, Rose, Amy N, Liu, Cheng, Urban, Marie L, and Stewart, Robert N. Data Driven Approach for High Resolution Population Distribution and Dynamics Models. United States: N. p., 2014. Web.
Bhaduri, Budhendra L, Bright, Eddie A, Rose, Amy N, Liu, Cheng, Urban, Marie L, & Stewart, Robert N. Data Driven Approach for High Resolution Population Distribution and Dynamics Models. United States.
Bhaduri, Budhendra L, Bright, Eddie A, Rose, Amy N, Liu, Cheng, Urban, Marie L, and Stewart, Robert N. Wed . "Data Driven Approach for High Resolution Population Distribution and Dynamics Models". United States. doi:. https://www.osti.gov/servlets/purl/1185543.
@article{osti_1185543,
title = {Data Driven Approach for High Resolution Population Distribution and Dynamics Models},
author = {Bhaduri, Budhendra L and Bright, Eddie A and Rose, Amy N and Liu, Cheng and Urban, Marie L and Stewart, Robert N},
abstractNote = {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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Jan 01 00:00:00 EST 2014},
month = {Wed Jan 01 00:00:00 EST 2014}
}

Conference:
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