[PROJECT] How much of Hamburg is dedicated to cars?

[jlstro]

Pitch

Summary

The project will try to answer the question given in the title: How much of the surface area of my hometown Hamburg is dedicated to cars? The basic idea is to come up with a percentage and/or total of all the surface area of the city that is constructed for automotive transportation, e.g. streets & car parking areas, gas stations, highways, bridges... If possible, I'll try calculate the corresponding figure for bikes and trains/metro as well as a comparison. If all goes well, I will also compare different areas of the city: Rich/poor neighbourhoods, industrial/resident, touristy/non-touristy, etc.

I took inspiration from this and this article.

Details

Possible headline(s): N percent of Hamburg's surface is dedicated to cars, only x to bikes Every car uses up N square meter in Hamburg Cars use up a lot of space: Here's how much exactly Data set(s): I will work with data from OpenStreetmap. I'll have to figure out how exactly I measure the area. Code repository: will provide link later Possible problems/fears/questions: I think the biggest problem is to measure the area of streets correctly, so identify which non-street parts of a city are dedicated to cars

Work so far

Nothing to show, sorry

Checklist

This checklist must be completed before you submit your draft.

• [ ] I have already spent time with my data set, opening it, exploring it, etc
• [ ] I have created a "DIARY.md" file to save links and list all of the terrible, no good problems I come across
• [ ] My issue links to my data set(s)
• [ ] My issue links to my code repository
• [x] My issue explains what I'd like to explore in the data set
• [ ] My issue includes images - either inspiration or what I've done so far

[sarahslo]

hmm. interesting. can you tell us, how much is living space and how much is park space too?

[jlstro]

Update

Your project content: images/words/etc

I loaded Hamburg's street grid into qgis, so here's a screenshot This is not actually part of the project but it looks cool. So far, everything happened inside a notebook. There are no cool graphics yet.

Any changes in direction or topic?

I think I will compare the Hamburg districts with each other in the end, so the individual data sets are a bit smaller / easier to handle. There are 30.000 plus street segments in Hamburg, I thought it was much less.

Problems/Questions

Despite all prejudice, German streets are not all the same size/width. That makes it a bit complicated to figure out the actual area - so far, all I have is length.

Checklist

• [ ] I have included my visuals
• [ ] I have filled out the sections above
• [ ] I have been updating my DIARY.md with details about my process
• [ ] I have uploaded/updated any Jupyter Notebooks or other datasets into my code repository

[jlstro]

@sarahslo Yes, I will try to divide the remaining (non-car) areas into resident, recreation, etc. That should be fairly easy with the data I have I hope.

[jessimckenzi]

Really interesting! Are you planning on doing a map, or something that hacks up the info and makes it into something else, like an area chart of some kind? (Like a waffle chart, but you could make the space dedicated to cars pictures of cars, dedicated to bikes pictures of bikes, dedicated biz pic of a shop, dedicated residential pic of a house, etc.) Lots of possibilities! Excited to see what comes next.

[jlstro]

~ 1/15 of Hamburg is road/parking surface!

Unfortunately, I won't be able to finish this project in due time. I will come back after Lede and make it nice. Here's a map of what I did so far: red is car-stuff (parking, roads), light orange is public transportation. Light grey are buildings, green / blue is parks and water and dark grey is "other" - mostly industrial areas and some agriculture. The streets width is not to scale!

Here's what I did so far:

The project diary

=================

• Download Hamburg OSM data from here. Could've done it in QGIS with the QuickOSM plugin but the performance really sucks
• Download district boundaries of Hamburg from here
• install osmctools with apt
• convert file downloaded in step 1 to .osm and filter with the following options to only keep streets: osmfilter hamburg-latest.osm --keep="highway=residential =primary =secondary =tertiary =unclassified" --drop="public_transport=stop_position public_transport=platform public_transport man_made boundary leisure amenity highway=traffic_signals =motorway_junction =bus_stop railway building entrance=yes barrier=gate barrier shop" > temp.osm
• creat geojson from osm file for easier use in python with this cli tool
• load geojson into jupyter notebook
• clean data, put into df
• read about haversine formula for hours, understand nothing, get confused, read more
• eventually calculate length in meter from lat/long points
• measure 4 randomly chosen streets of each highway type (residential, secondary, primary, etc...) and take mean of width for each type
• multiply length by width and number of lanes to get street area - I double checked with this document, that says that inner city street lanes are around 3,8m - very roughly corresponds with my measurements
• calculate area of each district in Hamburg. I did this in QGIS with the field calculator and exported it to csv and load it into my notebook.
• Alright - around 5 per cent of all surface area are streets!
• add district to street info. I should've done this before: Use QGIS to find out which street is in which disctrict, clean up a bit (some are in multiple districts), export info to csv, join on unique street id with existing df
• check for other object types with osmfilter: osmfilter hamburg-latest.osm --keep="building" --drop="building=parking" > all_buildings.osm && osmfilter hamburg-latest.osm --keep="natural leisure landuse=grass" --drop="natural=water" > parks_recreation.osm && osmfilter hamburg-latest.osm --keep="natural=water" > water_areas.osm && osmfilter hamburg-latest.osm --keep="amenity=parking =parking_space =fuel =car_sharing =taxi building=parking" > parking_buildings.osm && osmfilter hamburg-latest.osm --keep="amenity=bus_station public_transport railway" --drop="tunnel=yes" > public_transport.osm
• import it all into the map

to-do

• spatial-join info of each district to all other objects (to distinguish which district an object is in) and calculate total/relative area for each type of surface use for each district
• make it all look nice
• ...profit?