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are still challenged by weak spatial heterogeneity of ancillary data and quality of traditional census data, usually outdated, costly and inaccurate, this paper focuses on mobile phone data, which can be real-time and precise, and also strengthens spatial heterogeneity by its massive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.

Highlights

  • Population mapping at a finer scale and higher resolution can play an important role in understanding urban spatial features, especially in the measurement of urban centrality [1,2] and identification of employment centers [3,4,5,6,7]

  • These results suggest that land use regression (LUR)-2SFCAe is fit for dasymetric mapping with mobile phone data and to present land uses, wherein the distance decay setting of 2SFCAe tackles the problem of the undefined boundary of base station service area

  • The 1 km grid was applied in this study with a persuasive regression result, a balance of unevenness and heterogeneity remains to be explored for finer-grid mapping. These results provide substantial evidence for the assumption that the combination of LUR and 2SFCAe with two-step floating catchment area (2SFCA) can map population with mobile phone data and land use, which addresses the spatial heterogeneity in most dasymetric mapping, and tackles the problem for the undefined boundary of base stations in 2SFCA

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Summary

Introduction

Population mapping at a finer scale and higher resolution can play an important role in understanding urban spatial features, especially in the measurement of urban centrality [1,2] and identification of employment centers [3,4,5,6,7]. Most studies try to address spatial heterogeneity by fining geographic scale of ancillary data, ranging from Land use/land cover data (LULC) [14], soil sealing degree [15], nighttime lights, transportation network, elevation, and slope data extracted from satellite maps [16] to data with more classifications, such as cadastral information [17], tax parcel [18], buildings [19], Points of Interests (POIs) [20], and Volunteer Geographic Information (VGI) [21] Such methods have proven effective in improving the resolution of population mapping by enhancing spatial variance with increased amount of data categories, the accuracy of ancillary data still affects the results. The census data used in most studies usually lag behind in timeliness, and are costly and inaccurate, which could jeopardize the result of population distribution as well

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