A COMPARATIVE STUDY OF METHODS FOR DRIVE TIME ESTIMATION ON GEOSPATIAL BIG DATA: A CASE STUDY IN USA

8 citations as recorded by crossref.

1. Pediatric out-of-hospital cardiac arrest outcomes by Child Opportunity Index, race and ethnicity J. Barreto et al. https://doi.org/10.1016/j.resuscitation.2026.110970
2. Advancing equity in electric vehicle infrastructure: Assessing charging accessibility under the National Electric Vehicle Infrastructure (NEVI) program J. Lou et al. https://doi.org/10.1016/j.erss.2026.104620
3. Travel time prediction from sparse open data G. Boeing & Y. Zhou https://doi.org/10.1080/13658816.2026.2628193
4. Patient Travel Patterns and Concordance With Geographic Market Boundaries S. Decker et al. https://doi.org/10.7326/ANNALS-24-00857
5. Source-Dependent Accessibility Discrepancies and Their Effects on Land-Value Models J. Kim et al. https://doi.org/10.3390/su18073259
6. ‘Mind the Gap’—The impact of discrepancies between Google Maps API and reported travel data in the Global South F. Bastarianto et al. https://doi.org/10.1016/j.cstp.2025.101508
7. Big data in modelling geographical accessibility to healthcare: a scoping review protocol A. Njogu et al. https://doi.org/10.1136/bmjopen-2025-101567
8. Efficient and representative door-to-door travel time estimation for planning and policy M. Miotti & S. Hellweg https://doi.org/10.1007/s11116-025-10705-7