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Optimization of Modelling Population Density Estimation Based on Impervious Surfaces

Author

Listed:
  • Jinyu Zang

    (School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Ting Zhang

    (School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Longqian Chen

    (School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Long Li

    (School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China
    Department of Geography, Earth System Sciences, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium)

  • Weiqiang Liu

    (School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Lina Yuan

    (Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China)

  • Yu Zhang

    (Department of Land Resource Management, School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, China)

  • Ruiyang Liu

    (School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Zhiqiang Wang

    (School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Ziqi Yu

    (School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Jia Wang

    (School of Public Policy and Management, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

Abstract

Population data are key indicators of policymaking, public health, and land use in urban and ecological systems; however, traditional censuses are time-consuming, expensive, and laborious. This study proposes a method of modelling population density estimations based on remote sensing data in Hefei. Four models with impervious surface (IS), night light (NTL), and point of interest (POI) data as independent variables are constructed at the township scale, and the optimal model was applied to pixels to obtain a finer population density distribution. The results show that: (1) impervious surface (IS) data can be effectively extracted by the linear spectral mixture analysis (LSMA) method; (2) there is a high potential of the multi-variable model to estimate the population density, with an adjusted R 2 of 0.832, and mean absolute error (MAE) of 0.420 from 10-fold cross validation recorded; (3) downscaling the predicted population density from the township scale to pixels using the multi-variable stepwise regression model achieves a more refined population density distribution. This study provides a promising method for the rapid and effective prediction of population data in interval years, and data support for urban planning and population management.

Suggested Citation

  • Jinyu Zang & Ting Zhang & Longqian Chen & Long Li & Weiqiang Liu & Lina Yuan & Yu Zhang & Ruiyang Liu & Zhiqiang Wang & Ziqi Yu & Jia Wang, 2021. "Optimization of Modelling Population Density Estimation Based on Impervious Surfaces," Land, MDPI, vol. 10(8), pages 1-17, July.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:8:p:791-:d:603334
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    References listed on IDEAS

    as
    1. Mariateresa Ciommi & Gianluca Egidi & Rosanna Salvia & Sirio Cividino & Kostas Rontos & Luca Salvati, 2020. "Population Dynamics and Agglomeration Factors: A Non-Linear Threshold Estimation of Density Effects," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    2. Han Li & Long Li & Longqian Chen & Xisheng Zhou & Yifan Cui & Yunqiang Liu & Weiqiang Liu, 2019. "Mapping and Characterizing Spatiotemporal Dynamics of Impervious Surfaces Using Landsat Images: A Case Study of Xuzhou, East China from 1995 to 2018," Sustainability, MDPI, vol. 11(5), pages 1-22, February.
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    Cited by:

    1. Huan Xu & Jianjun Yang & Guozhu Xia & Tao Lin, 2022. "Spatio-temporal Differentiation of Coupling Coordination between Ecological Footprint and Ecosystem Service Functions in the Aksu Region, Xinjiang, China," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    2. Longgao Chen & Xiaoyan Yang & Long Li & Longqian Chen & Yu Zhang, 2021. "The Natural and Socioeconomic Influences on Land-Use Intensity: Evidence from China," Land, MDPI, vol. 10(11), pages 1-25, November.

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