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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.06011 |
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| _version_ | 1866916782334279680 |
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| author | Li, Fangyuan Li, Yijing Rogerson, Luke Edward |
| author_facet | Li, Fangyuan Li, Yijing Rogerson, Luke Edward |
| contents | With rising demand for emergency services, the London Ambulance Service, LAS, and the London Fire Brigade, LFB, face growing challenges in resource coordination. This study investigates the temporal and spatial similarities in their service demands to assess potential for routine cross-agency collaboration. Time series analysis revealed aligned demand peaks in summer, on Fridays, during daytime hours, and were highly sensitive to high temperature weather conditions. Bivariate mapping and Moran I indicated significant spatial overlaps in central London and Hillingdon. Geographically Weighted Regression, GWR, examined the influence of socioeconomic factors, while Comap analysis uncovered spatiotemporal heterogeneity across fire service types. The findings highlight opportunities for targeted collaboration in high-overlap areas and peak periods, offering practical insights to enhance emergency service resilience and efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_06011 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | London Blue Light Collaboration Evaluation: A Comparative Analysis of Spatio temporal Patterns on Emergency Services by London Ambulance Service and London Fire Brigade Li, Fangyuan Li, Yijing Rogerson, Luke Edward Computers and Society With rising demand for emergency services, the London Ambulance Service, LAS, and the London Fire Brigade, LFB, face growing challenges in resource coordination. This study investigates the temporal and spatial similarities in their service demands to assess potential for routine cross-agency collaboration. Time series analysis revealed aligned demand peaks in summer, on Fridays, during daytime hours, and were highly sensitive to high temperature weather conditions. Bivariate mapping and Moran I indicated significant spatial overlaps in central London and Hillingdon. Geographically Weighted Regression, GWR, examined the influence of socioeconomic factors, while Comap analysis uncovered spatiotemporal heterogeneity across fire service types. The findings highlight opportunities for targeted collaboration in high-overlap areas and peak periods, offering practical insights to enhance emergency service resilience and efficiency. |
| title | London Blue Light Collaboration Evaluation: A Comparative Analysis of Spatio temporal Patterns on Emergency Services by London Ambulance Service and London Fire Brigade |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2506.06011 |