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Article

Deciphering Mobility in “Strip Cities”: Multiscale Mechanisms and Spatial Fusion of Ride-Hailing Demand Under Topographical Constraints

1
School of Civil Engineering and Architecture, University of Jinan, Jinan 250022, China
2
Department of Civil and Environmental Engineering, University of Auckland, Auckland 1010, New Zealand
3
School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 518107, China
4
School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2026, 15(7), 286; https://doi.org/10.3390/ijgi15070286 (registering DOI)
Submission received: 7 April 2026 / Revised: 5 June 2026 / Accepted: 26 June 2026 / Published: 28 June 2026

Abstract

Understanding the spatial generation mechanisms of ride-hailing demand is crucial for sustainable urban mobility. However, existing literature largely assumes monocentric urban layouts and globally stationary spatial scales, often overlooking the severe topographical constraints inherent in “strip cities”. To bridge this gap, the present study proposes a novel dual-level analytical framework coupling the Spatially Embedded Laplacian Graph Partition (SE-LGP) algorithm with a Log-Gaussian Multiscale Geographically Weighted Regression (MGWR) model. Taking Jinan, China, as a quintessential strip city, we incorporate spatial penalties to decode its mobility dynamics. Macroscopically, we reveal that substantial topographic friction fragments the workday mobility network into a chain of 23 highly localized micro-circulations. This anisotropic friction results in a notable 41.70% intra-community retention rate, demonstrating that flexible mobility operates within confined functional basins rather than a unified citywide market. Microscopically, the MGWR uncovers significant multiscale spatial heterogeneity: the jobs–housing mismatch is strongly associated with demand at a global macro scale (bandwidth = 1335), whereas public transit integration operates predominantly at a localized micro scale (bandwidth = 44). Crucially, the interaction between topographical friction and infrastructure capacity unveils a highly localized pressure-valve effect (bandwidth = 46), indicating that physical road networks mitigate natural barriers strictly at a micro scale. Comparative analysis quantifies a “spatial fusion effect” during weekends; the relaxation of rigid tidal commuting reveals a structural invariance in built-environment scales (bandwidth = 1335), while the impact intensity of natural topographical friction undergoes a marked spatial inversion. This behavioral elasticity merges fragmented micro-circulations into larger regional communities (k=20). The findings indicate that flexible transit is strongly associated with scale-dependent and temporally elastic mechanisms. It provides insights for planners to transition from uniform city-wide fleet dispatching toward region-customized, temporally dynamic mobility management in topographically constrained metropolises.
Keywords: ride-hailing demand; strip-city morphology; spatial community detection; Multiscale Geographically Weighted Regression (MGWR); spatial fusion effect; topographical constraints ride-hailing demand; strip-city morphology; spatial community detection; Multiscale Geographically Weighted Regression (MGWR); spatial fusion effect; topographical constraints

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MDPI and ACS Style

Wang, D.; Jin, S.; Lin, L. Deciphering Mobility in “Strip Cities”: Multiscale Mechanisms and Spatial Fusion of Ride-Hailing Demand Under Topographical Constraints. ISPRS Int. J. Geo-Inf. 2026, 15, 286. https://doi.org/10.3390/ijgi15070286

AMA Style

Wang D, Jin S, Lin L. Deciphering Mobility in “Strip Cities”: Multiscale Mechanisms and Spatial Fusion of Ride-Hailing Demand Under Topographical Constraints. ISPRS International Journal of Geo-Information. 2026; 15(7):286. https://doi.org/10.3390/ijgi15070286

Chicago/Turabian Style

Wang, Di, Shuxin Jin, and Lin Lin. 2026. "Deciphering Mobility in “Strip Cities”: Multiscale Mechanisms and Spatial Fusion of Ride-Hailing Demand Under Topographical Constraints" ISPRS International Journal of Geo-Information 15, no. 7: 286. https://doi.org/10.3390/ijgi15070286

APA Style

Wang, D., Jin, S., & Lin, L. (2026). Deciphering Mobility in “Strip Cities”: Multiscale Mechanisms and Spatial Fusion of Ride-Hailing Demand Under Topographical Constraints. ISPRS International Journal of Geo-Information, 15(7), 286. https://doi.org/10.3390/ijgi15070286

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