Using Location-Based Services Data for Climate Resilience and Emergency Planning

Anonymized mobile Location-Based Services (LBS) data has gained its popularity in the realm of transportation planning for its availability at ever lower costs, spatial and temporal accuracy, and representativeness of movement and activity patterns among the population even at low levels of aggregation. Despite its capability in complementing regional travel surveys and providing more accurate portraits of typical travel patterns, there is a dearth of research on drawing insights about evacuation following disruptive, disastrous events for future planning from the mobile LBS data. This paper presents two case studies where the mobile LBS data are used in the context of climate resiliency and evacuation planning. The first case study is designed to analyze movement patterns of mobile devices before and after several large-scale natural disasters in Southern California in recent years. Baseline activities patterns are established using LBS records before the event, to be compared against activities during and after the event. The second case study focuses on the daily activity analysis in the Orlando region in Florida for the estimation and identification of population to be evacuated during an emergency. Metrics for evaluating the movement and activity patterns, including changes in device activity intensity, spatiotemporal distribution of device activities are examined to better understand transportation demand during and after a natural disaster or an emergency and guide efficient evacuation and infrastructure planning in response to climate change.


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures;
  • Pagination: 17p

Subject/Index Terms

Filing Info

  • Accession Number: 01763681
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-03823
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:08AM