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Title: Urban Scaling as Validation for Predictions of Imperviousness From Population

Abstract

Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land-Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process-based models of ecosystem composition under different climate scenarios.

Authors:
ORCiD logo [1]; ORCiD logo [2];  [3]; ORCiD logo [4]
  1. National Security Sciences Division Oak Ridge National Laboratory Oak Ridge TN USA
  2. Climate Change Science Institute and Environmental Sciences Division Oak Ridge National Laboratory Oak Ridge TN USA
  3. Math Thesis Program, Oak Ridge High School Oak Ridge TN USA
  4. Climate Change Science Institute and Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak Ridge TN USA
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1734796
Alternate Identifier(s):
OSTI ID: 1777773; OSTI ID: 1786644
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Published Article
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Name: Geophysical Research Letters Journal Volume: 47 Journal Issue: 23; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES

Citation Formats

Brelsford, Christa, Coon, Ethan T., Moran, V, Edward, and Allen‐Dumas, Melissa. Urban Scaling as Validation for Predictions of Imperviousness From Population. United States: N. p., 2020. Web. https://doi.org/10.1029/2020GL089742.
Brelsford, Christa, Coon, Ethan T., Moran, V, Edward, & Allen‐Dumas, Melissa. Urban Scaling as Validation for Predictions of Imperviousness From Population. United States. https://doi.org/10.1029/2020GL089742
Brelsford, Christa, Coon, Ethan T., Moran, V, Edward, and Allen‐Dumas, Melissa. Sat . "Urban Scaling as Validation for Predictions of Imperviousness From Population". United States. https://doi.org/10.1029/2020GL089742.
@article{osti_1734796,
title = {Urban Scaling as Validation for Predictions of Imperviousness From Population},
author = {Brelsford, Christa and Coon, Ethan T. and Moran, V, Edward and Allen‐Dumas, Melissa},
abstractNote = {Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land-Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process-based models of ecosystem composition under different climate scenarios.},
doi = {10.1029/2020GL089742},
journal = {Geophysical Research Letters},
number = 23,
volume = 47,
place = {United States},
year = {2020},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1029/2020GL089742

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