Patterns of Nighttime Crowd Flows in Tourism Cities Based on Taxi Data—Take Haikou Prefecture as an Example
نویسندگان
چکیده
The study of patterns crowd flows represents an emerging and expanding research field. most straightforward efficient approach to investigate the is concentrate on traffic flow. However, assessments simple point-to-point movement frequently lack universal validity, little has been conducted regularity nighttime movement. Due suspension public transportation at night, taxi orders are critical in capturing features a tourism city. Using Haikou as example, this paper proposes mixed Geogrid Spatio-temporal model (MG-STM) for city order address challenges. Firstly, by collecting pick-up/drop-off/in-out flow crowds, uses DCNMF dimensionality reduction extract semi-supervised spatio-temporal variation K-Means clustering method determine cluster types flows’ changes each geogrid. Secondly, constructing mixed-evaluation based LJ1-01 light data, clusters, land use data geogrid-based regions, pattern urban areas successfully determined. results suggest that MG-STM can estimate number collective various regions effectively appropriately. Moreover, population density shows high positive correlation with lag flows. Each 5% increase 30-min delay peak will be extremely beneficial developing implementing systems criminal tracking pandemic prevention.
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ژورنال
عنوان ژورنال: Remote Sensing
سال: 2022
ISSN: ['2315-4632', '2315-4675']
DOI: https://doi.org/10.3390/rs14061413