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Remote Sens. 2019, 11(3), 310;

Modeling Polycentric Urbanization Using Multisource Big Geospatial Data

School of Transportation Engineering, Shenyang Jianzhu University, Shenyang 110168, China
Urban Informatics & Spatial Computing Lab, Department of Informatics, New Jersey Institute of Technology, Newark, NJ 07102, USA
Department of Land, Environment, Agriculture and Forestry, University of Padova, 35020 Padova, Italy
Innovation Center for Technology, Beijing Tsinghua Tongheng Urban Planning & Design Institute, Beijing 100085, China
Beijing Key Laboratory of Megaregions Sustainable Development Modelling, Capital University of Economics and Business, Beijing 100070, China
Author to whom correspondence should be addressed.
Received: 4 December 2018 / Revised: 29 January 2019 / Accepted: 31 January 2019 / Published: 4 February 2019
(This article belongs to the Special Issue Advances in Remote Sensing with Nighttime Lights)
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Understanding the dynamics of polycentric urbanization is important for urban studies and management. This paper proposes an analytical model that uses multisource big geospatial data to characterize such dynamics to facilitate policy making. There are four main steps: (1) main centers and subcenters are identified using spatial cluster analysis and geographically weighted regression (GWR) based on Visible Infrared Imaging Radiometer Suite (VIIRS)/NPP and social media check-in data; (2) the built-up areas are extracted by using Defense Meteorological Satellite Program—Operational Linescan System (DMSP/OLS) gradient images; (3) the economic corridors that connect the main center and subcenters are constructed using road network data from Open Street Map (OSM) with the least-cost distance method; and (4) the major urban development direction is identified by analyzing the changes in built-up areas within the economic corridors. The model is applied to three major cities in northeastern, central, and northwestern China (Shenyang, Wuhan, and Xi’an) from 1992 to 2012. View Full-Text
Keywords: polycentric urbanization; big geospatial data; nighttime light imagery; social media; economic corridors polycentric urbanization; big geospatial data; nighttime light imagery; social media; economic corridors

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Xie, Z.; Ye, X.; Zheng, Z.; Li, D.; Sun, L.; Li, R.; Benya, S. Modeling Polycentric Urbanization Using Multisource Big Geospatial Data. Remote Sens. 2019, 11, 310.

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