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  • Prediction of total imperviousness from population density and land use data for urban areas (Case study: South East Queensland, Australia)

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    Author(s)
    Ramezani, MR
    Yu, B
    Che, Y
    Griffith University Author(s)
    Yu, Bofu
    Year published
    2021
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    Abstract
    Total imperviousness (residential and non-residential) increases with population growth in many regions around the world. Population density has been used to predict the total imperviousness in large areas, although population size was only closely related to residential imperviousness. In this study, population density together with land use data for 154 suburbs in Southeast Queensland (SEQ) of Australia were used to develop a new model for total imperviousness estimation. Total imperviousness was extracted through linear spectral mixing analysis (LSMA) using Landsat 8 OLI/TIRS, and then separated into residential and ...
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    Total imperviousness (residential and non-residential) increases with population growth in many regions around the world. Population density has been used to predict the total imperviousness in large areas, although population size was only closely related to residential imperviousness. In this study, population density together with land use data for 154 suburbs in Southeast Queensland (SEQ) of Australia were used to develop a new model for total imperviousness estimation. Total imperviousness was extracted through linear spectral mixing analysis (LSMA) using Landsat 8 OLI/TIRS, and then separated into residential and non-residential areas based on land use data for each suburb. Regression models were developed between population density and total imperviousness, and population density and residential imperviousness. Results show that (1) LSMA approach could retrieve imperviousness accurately (RMSE < 10%), (2) linear regression models could be used to estimate both total imperviousness and residential imperviousness better than nonlinear regression models, and (3) correlation between population density and residential imperviousness was higher (R2 = 0.77) than that between population density and total imperviousness (R2 = 0.52); (4) the new model was used to predict the total imperiousness based on population density projections to 2057 for three potential urban development areas in SEQ. This research allows accurate prediction of the total impervious area from population density and service area per capital for other regions in the world.
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    Journal Title
    Applied Sciences
    Volume
    11
    Issue
    21
    DOI
    https://doi.org/10.3390/app112110044
    Copyright Statement
    © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Human geography
    Urban and regional planning
    Publication URI
    http://hdl.handle.net/10072/409938
    Collection
    • Journal articles

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