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Identification of urban regions’ functions in Chengdu, China, based on vehicle trajectory data

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References

1988Thirteen Ways to Look at the Correlation Coefficient4,068 cited
2012Discovering regions of different functions in a city using human mobility and POIs1,136 cited
2006Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis865 cited
2017Extracting urban functional regions from points of interest and human activities on location‐based social networks470 cited
2012Urban land uses and traffic ‘source-sink areas’: Evidence from GPS-enabled taxi data in Shanghai423 cited
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n.d.Revealing travel patterns and city structure with taxi trip data246 cited
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2008Money Circulation, Trackable Items, and the Emergence of Universal Human Mobility Patterns67 cited
2015Understanding Urban Spatial Structure of Shanghai Central City Based on Mobile Phone Data53 cited

Cited by

2022Context-Aware Matrix Factorization for the Identification of Urban Functional Regions with POI and Taxi OD Data14 cited
2025How do built environment characteristics influence metro-bus transfer patterns across metro station types in Shanghai?

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12 cited

2023Multi-Scale Recursive Identification of Urban Functional Areas Based on Multi-Source Data8 cited

2024Adaptive weighted multi-view subspace clustering method for recognizing urban functions from multi-source social sensing data7 cited

2025Identifying dynamic functions of urban areas with a multi-temporal collaborative graph neural network model6 cited