|
For my project I want to find all streets that can be reached within a certain driving distance. A practical example would be a car that has 50km mileage left. Which streets can be reached? The long way of doing this would be to set up a Shortest Tree Path from the starting point and cut at the desired range from the starting point to get all way ids. I was wondering if there is maybe an easier way. For example if I find all outermost way ids that are reachable with x km mileage left. Is there a way to deduct all way ids that are within this outer circle of way ids, meaning closer to the starting point and therefore reachable? Is there a way id naming convention that helps with this? Basically what is important for my project is getting all way or even node ids that are reachable within a ceratain mileage from a starting point. Thanks a lot! |
NOTICE: help.openstreetmap.org is no longer in use from 1st March 2024. Please use the OpenStreetMap Community Forum
Follow this question
By Email:Once you sign in you will be able to subscribe for any updates here
By RSS:Markdown Basics
- *italic* or _italic_
- **bold** or __bold__
- link:[text](http://url.com/ "title")
- image?
- numbered list: 1. Foo 2. Bar
- to add a line break simply add two spaces to where you would like the new line to be.
- basic HTML tags are also supported
Question tags:
question asked: 04 Jun '18, 18:08
question was seen: 1,238 times
last updated: 06 Jun '18, 21:07
Related questions
NOTICE: help.openstreetmap.org is no longer in use from 1st March 2024. Please use the OpenStreetMap Community Forum
What data source you want to use for that? API / imported OSM database?
Right now I am planning to download map tiles from osm and then find all way_ids that are within a certain distance. Probably by defining an outer perimeter where a specific street is just within reach of x km from starting point. And in the second step find all way_id that are within this perimeter / GPS point within this geometry(polygon, circle, rectangle, whatever it might end up looking like)