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Trajectory Data Analyses for Pedestrian Space-time Activity Study

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Computing travel time when the exact address is unknown: a comparison of point and polygon ZIP code approximation

Ethan M Berke¹, Xun Shi

¹Department of Geography, Dartmouth College, Hanover, New Hampshire, USA. Ethan.M.Berke@dartmouth.edu

International Journal of Health Geographics

|April 30, 2009

Summary

Estimating travel time to healthcare is crucial. Population-based methods, particularly using population centroids, offer superior accuracy over geometry-based approaches, especially in urban settings.

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Area of Science:

Geographic Information Systems (GIS)
Health Services Research
Spatial Analysis

Background:

Geographic access to healthcare is vital.
Estimating travel time is a key metric for assessing this access.
Accurate travel time estimation is challenging when only ZIP code data is available.

Purpose of the Study:

To compare different strategies for estimating travel times to healthcare facilities using only ZIP code data.
To evaluate the accuracy of geometry-based versus population-based methods.
To identify the most reliable method for travel time estimation in diverse geographic settings.

Main Methods:

Simulated data from New Hampshire and Arizona were used.
Four methods were compared: geometric centroid, population centroid, service area rings with uniform distribution assumption, and service area rings with population distribution assumption.
Travel times based on street addresses served as the ground truth for validation.

Main Results:

Population-based methods demonstrated significantly smaller estimation errors compared to geometry-based methods.
Within each category (geometry or population), centroid and service area methods yielded similar error levels.
Estimation errors were notably smaller in urban areas than in rural areas.

Conclusions:

Population-based methods are superior for estimating travel time to healthcare.
The population centroid method emerged as the optimal choice for accuracy.
Travel time estimates in rural areas are less reliable and require careful consideration.