This study develops entropy-based measurements to quantify the geographical distribution diversity of taxi trip origins and destinations in New York City (NYC). The origin-entropy for a taxi zone accounts for all the trips that originate from this zone and calculates the level of geographical distribution diversity of these trips' destinations. Likewise, the destination-entropy for a taxi zone considers all the trips that end in this zone and calculates the level of geographical distribution diversity of these trips' origins.
The key highlights and insights from the study are:
Entropy-based measurements effectively capture shifts in the diversity of trips' geographical origins and destinations, reflecting changes in travel decisions due to major events like the COVID-19 pandemic.
While traditional trip count metrics show an overall decrease in taxi usage during the pandemic, the entropy measurements reveal that the geographical distribution diversity of trip origins and destinations remained high or even increased in certain zones. This suggests that despite fewer trips, the remaining taxi travelers were still accessing a wide range of destinations from diverse origins.
The study identified distinct temporal patterns in origin count, destination count, origin-entropy, and destination-entropy for different taxi zones, providing nuanced insights into how human mobility behaviors varied across the city. For example, zones with major transportation hubs, recreational areas, and mixed-use neighborhoods exhibited unique changes in these metrics.
The interactive geovisualization tool developed in this study enables researchers and urban planners to explore the spatial and temporal dynamics of taxi trip patterns, empowering data-driven decision making for transportation management and urban development.
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arxiv.org
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by Yuqin Jiang,... ב- arxiv.org 04-18-2024
https://arxiv.org/pdf/2401.17467.pdfשאלות מעמיקות