NACIS 2016 Presentation Jeff Allen, University of Toronto Steven Farber, University of Toronto Scarborough Isochrones are often used for visual analysis of mobility and accessibility in urban areas. We will discuss an alternative method to conventional isochrones; using computed travel times to classify network segments rather than generating isolines or polygons. We will outline the data, tools, and geoprocessing steps required to make these kind of maps as well as discuss visualization considerations for different scales, subject matter, and for static and interactive maps. Further discussion will include their advantages and disadvantages when compared to conventional isochrones, particularly in terms of classification options and mapping in conjunction with other data. Finally, we will comment on how this method results in potential benefits for subsequent spatial analysis and how it can be scaled for multiple origin points, travel modes, departure times, and transit scenarios.

1. Using network segments in the
spatial representation of travel
time isochrones

2. Isochrones
Iso = Equal Chrone = Time

3. https://upload.wikimedia.org/wikipedia/commons/8/86/Isochronic_Passage_Chart_Francis_Galton_1881.jpg

4. https://archive.org/details/atlasofcommercia00bart

5. https://en.wikipedia.org/wiki/File:Map_of_Melbourne_and_environs_minimum_railway_or_tramway_time_zones.jpg

6. https://en.wikipedia.org/wiki/File:Map_of_Melbourne_and_environs_minimum_railway_or_tramway_time_zones.jpg

7. Existing Tools:
ArcGIS Network Analysis
PostGIS + pgRouting
OpenTripPlanner
Dozens of Web Applications
etc.
General Steps
1 - Create a Network Graph
2 - Compute travel time from a
point to network vertices
3 - Generate shapes or surface
for specific travel times
4 - Visualize output
Output:
Isolines, polygons, vector
grids, or rasters that
represent the AREA that is
accessible from a point (or
points)

8. A structural alternative:
General Steps
1 - Create a network graph
2 - Compute travel times from a
point to network vertices
3 - Generate shapes at specific
travel times
3 - Join travel times to edges
4 - Classify / visualize output
Using network segments in the
spatial representation of
travel time isochrones.

9. Output Data Structure:

12. Questions
1 - How can this technique be applied?
2 - How can it lead to new insights about our data?
3 - When is it preferable over conventional isochrones?
or

13. 1 - Mapping Differences in Travel Times:
By Travel Mode
By Time of Day
For Different Transit Agencies

14. 1 - Differences in Travel Times

15. 1 - Differences in Travel Times

16. v 2 - Combining with Areal Data

17. 3 - Potential Path Areas

18. 4 - Transit Maps:

19. 4 - Transit Maps:

20. 4 - Transit Maps:

21. 5 - Travel Surveys:

22. 5 - Travel Surveys:

23. 5 - Travel Surveys:

27. Some code & maps are on my github page at jamaps.github.io
Thank You!