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Sustainability 2018, 10(7), 2432; https://doi.org/10.3390/su10072432

Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method

1
Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China
2
Department of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China
*
Author to whom correspondence should be addressed.
Received: 22 May 2018 / Revised: 5 July 2018 / Accepted: 10 July 2018 / Published: 12 July 2018
(This article belongs to the Section Sustainable Urban and Rural Development)
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Abstract

Dasymetric mapping of high-resolution population facilitates the exploration of urban spatial feature. While most relevant studies are still challenged by weak spatial heterogeneity of ancillary data and quality of traditional census data, usually outdated, costly and inaccurate, this paper focuses on mobile phone data, which can be real-time and precise, and also strengthens spatial heterogeneity by its massive mobile phone base stations. However, user population recorded by mobile phone base stations have no fixed spatial boundary, and base stations often disperse in extremely uneven spatial distribution, this study defines a distance-decay supply–demand relation between mobile phone user population of gridded base station and its surrounding land patches, and outlines a dasymetric mapping method integrating two-step floating catchment area method (2SFCAe) and land use regression (LUR). The results indicate that LUR-2SFCAe method shows a high fitness of regression, provides population mapping at a finer scale and helps identify urban centrality and employment subcenters with detailed worktime and non-worktime populations. The work involving studies of dasymetric mapping based on LUR-2SFCAe method and mobile phone data proves to be encouraging, sheds light on the relationship between mobile phone users and nearby land use, brings about an integrated exploration of 2SFCAe in LUR with distance-decay effect and enhances spatial heterogeneity. View Full-Text
Keywords: dasymetric mapping; urban spatial feature; land use regression (LUR); two-step floating catchment area (2SFCA); mobile phone data; urban centrality dasymetric mapping; urban spatial feature; land use regression (LUR); two-step floating catchment area (2SFCA); mobile phone data; urban centrality
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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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Liu, L.; Peng, Z.; Wu, H.; Jiao, H.; Yu, Y. Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method. Sustainability 2018, 10, 2432.

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