https://alexandrakapp.github.io/30daymapchallenge/
What is the 30dayMapChallenge?
My results
The idea is to make 30 maps from each day from 1st Nov to 30th Nov 2020. I hope to get about half done - so 15 maps.
I want to use this challenge to play around with different R packages for geospatial data and try out different ways of interactive visualizations.
Amount of cars in XHain mapped as points onto streets
There are 80.808 cars registered in Friedrichshain-Kreuzberg (2017).
If all cars would start driving at the same time - it'd get pretty crowded
The polygon of the streets are derived as a 'negative' from the official blocks provided by the Geoportal Berlin. Points to represent cars are sampled randomly within the polygon.
Data:
- Amount of cars via kleine Anfragen
- Polygon of streets derived from Geoportal Berlin 'Blockkarte 1:5000 (ISU5)'
Tools & Packages:
All domestic German flights 2019
About 10% of all flights from German airports are domestic flights - so starting in Germany and landing in Germany.
The amount of flights between German airports are mapped here:
Data:
Tools & Packages:
- geocode airports: tmaptools R package
- viz: flowmap.blue R package
The catchment area of boulder gyms in Berlin
Playing around with Voroni maps: "Voronoi polygons are created so that every location within a polygon is closer to the sample point in that polygon than any other sample point."
Here: All boulder gyms (that I know of) in Berlin. If everyone would go his or her closest gym (by beeline), this would be the catchment areas of each boulder gym.
Tools & Packages:
- geocode boulder gyms: tmaptools R package
- viz: mapview
Traffic accidents in Stuttgart
The 'Statistikportal' offers a great data set on (almost) all accidents in Germany as single points. The mapdeck package auto aggregates point data into hexagons - so no need for data pre-processing.
I chose to crop the data to the outline of Stuttgart - but any other region or city can easily be used with the code by setting a different outline.
Data:
Tools & Packages:
- get outline of Stuttgart: osmdata
- viz: mapview R package
Rotpunkt
Today is another one on climbing - it's less about the mapping tools.
In sport climbing, redpointing is free-climbing a route, while lead climbing, after having practiced the route beforehand. The English term "redpoint" is a loan translation of the German Rotpunkt coined by Kurt Albert in the mid-1970s at Frankenjura. He would paint a red X on a fixed pin so that he could avoid using it for a foot- or handhold. Once he was able to free-climb the entire route, he would put a red dot at the base of the route. In many ways, this was the origin of the free climbing movement that led to the development of sport climbing ten years later. Wikipedia
This map shows all notable ascents according to Wikipedia.
Data:
Self compiled data set using:
- Wikipedia
- Coordinates mostly collected from thecrag.com
Hours of sunshine in Germany 2019
Where in Germany was a lot of sunshine in 2019 - where was it rather grey?
Data:
Tools & Packages:
- reading ESRI ascii grid file format: sp R package
- viz of raster data: leaflet R package
- hover information for raster data: leafem R package
The life lines of Berlin
A fast way to find major streets within a city, without searching for any data on traffic amounts, street types or street width:
Take random start and end points within the city and run a routing to find routes connecting the start and end points.
Then aggregate the single street segments on how often they were used. You then get an image of the major city axes.
Big thanks to the stplanr package, which makes this easily done within a few lines of code!
Tools & Packages:
- routing and aggregating line segments: stplanr R package
- viz: leaflet R package
Which cuisine can you eat where in Berlin?
Tools & Packages:
- Data on restaurants: osmdata R package
- Viz: mapdeck R package
Data:
OpenStreetMap via osmdata package
Mapping the alpes in 3D
Playing around with the mapdeck::add_terrain() function. Not perfect yet, but works for a first try.
Data:
Elevation data with Mapbox Tiles:
Tools & Packages:
- Viz: mapdeck R package
Noise in Berlin
OpenGIS Web Services (OWS) define geospatial standards to provide geo data, like WFS (Web Feature Service) for vector data and WMS (Web Map Service) for raster data. Yet, these standards are not widely known with developers or data analysts who are used to working with ESRI-shape files, geojsons, etc.
Some spatial data infrastructure providers, as the Geodatenportal Berlin (FIS-Broker) only offer these services and no further file download.
There are some resources on how to use those services in R, e.g. here some general info and here more specific for the Berlin FIS-Broker.
Though, all example code was on retrieving vector data of WFS services. For todays challenge "raster" I wanted to try out, how easy it is to get raster data (WMS) straight into R.
It's not entirely straight forward, as you need to find some parameters (e.g. "layers") through the getCapabilities query first. Then you retrieve a PNG where you need to set a proper georeference again, with a bounding box and CRS. Therefore, I still find the easiest way for a one time download to use QGIS (I wrote a blog post on how to do that at the Technologiestiftung Berlin), as QGIS does all this setting the correct parameters already for you.
Data:
Tools & Packages:
- construct URL httr R package
- plot RGB raster layer leafem R package
Area of destroyed rain forest in 2019
In 2019 121.500 square km of rain forest had been destroyed. But how much is that? This map shows a polygon as large as the destroyed area that can be moved to any spot on the map to compare it to.
Data:
Tools & Packages:
- viz of raster data: leaflet R package
- map editing and drawing for leaflet: leafpm R package
Movement within Berlin ("Binnenwanderung")
Many people are moving to Berlin from other places - especially the center - "im Ring" - is popular for people comiing to the city. But once in Berlin - how do people move between the different districts ("Binnenwanderung")? More people move from the center districts to the outskirts. (Data from 2013)
Click on a district to see where the people are coming from that move to this district.
Click events on leaflet maps are possible with shiny observe events.
Data:
Tools & Packages:
- viz and clicking interaction: leaflet R package & shiny R package
U-Bahn trains moving through Berlin
All U-Bahn trains moving through the city on a regular Monday using the {mapdeck::add_trips()} function.
Data:
Tools & Packages:
- Viz: mapdeck R package
- read GTFS data: tidytransit R package
Flight departures by Airport in Germany
Today is not made with R, but with Datawrapper
Data:
Tools & Packages:
Create your own basemap with Mapbox Studio
Ever wanted pink rivers or lilac streets on your basemap? That can easily be done with Mapbox Studio.
Tools & Packages: