Bike Parking Lots in Vienna

Bike Parking Lots in Vienna
OpenGovernmentVienna
rstudy
Published

November 8, 2015

Another addition to the OpenGovernmentVienna repo by Christian Brandstaetter showing the density of bike parking lots in Vienna.

The script executes the following steps:

  1. Download Vienna map including district boundaries and bike parking lots from http://data.wien.gv.at.
  2. Plot two Vienna maps showing bike parking lots and density per district.
library(rgdal) 
library(rgeos) 
library(XML)
library(RCurl)
library(ggplot2) 
library(plotrix) 
library(maptools)

download.vienna.shape <- function(shapename, outdir = "data") {
    baseurl <- "http://data.wien.gv.at/daten/geo?service=WFS&request=GetFeature&version=1.1.0&typeName=ogdwien:"
    urlparam <- "&srsName=EPSG:4326&outputFormat=shape-zip" 
    url <- sprintf("%s%s%s", baseurl, shapename, urlparam)
    
    dir.create(outdir, showWarnings = FALSE)
    destfile = file.path(outdir, sprintf("%s.zip", shapename))
    download.file(url, destfile = destfile)
    unzip(destfile, exdir = file.path(outdir, shapename))
    invisible(file.remove(destfile))
}

Retrieve Data

## Read District Boundaries
download.vienna.shape("BEZIRKSGRENZEOGD")
wmap <- readOGR("data/BEZIRKSGRENZEOGD", layer="BEZIRKSGRENZEOGDPolygon") 
## OGR data source with driver: ESRI Shapefile 
## Source: "data/BEZIRKSGRENZEOGD", layer: "BEZIRKSGRENZEOGDPolygon"
## with 23 features
## It has 15 fields
## Read Streets
download.vienna.shape("STRASSENGRAPHOGD")
smap <- readOGR("data/STRASSENGRAPHOGD", layer="STRASSENGRAPHOGD") 
## OGR data source with driver: ESRI Shapefile 
## Source: "data/STRASSENGRAPHOGD", layer: "STRASSENGRAPHOGD"
## with 28293 features
## It has 18 fields
## Read bike parking lots
download.vienna.shape("FAHRRADABSTELLANLAGEOGD")
bmap <- readOGR("data/FAHRRADABSTELLANLAGEOGD", layer="FAHRRADABSTELLANLAGEOGDPoint") 
## OGR data source with driver: ESRI Shapefile 
## Source: "data/FAHRRADABSTELLANLAGEOGD", layer: "FAHRRADABSTELLANLAGEOGDPoint"
## with 4061 features
## It has 5 fields
## Download Size of Each district
distsize <- download.vienna.bydistrict("lebensraum/tabellen/nutzungsklassen-bez", skip.row = 2)
distsizekm2 <- distsize[, 1] / 100

Calculate stuff

## Number of bike parking lots per district
bikelotsperdistrict <- table(bmap$BEZIRK)
lotdensity <- bikelotsperdistrict / distsizekm2

## Normalization of Colour Scaling
normdichte <- round(lotdensity/max(lotdensity)*50,digits=0) 
colfunc <- colorRampPalette(c("lightblue", "darkgreen")) 
colfunc100 <- colfunc(100) 
bezirksfarben <- colfunc100[normdichte]

# Transformations  111.1 
# km to degree (einfache Umrechnung) 
hundm <- (1/111.1)/10 
# 100 m for Radius of Punkte  
centroids <- gCentroid(wmap, byid=TRUE) # Mittelpunkt/Bezirk

Plots

Plot 1 - Vienna Map with Bike Parking Lots (Discrete Density)

layout(1:2, heights=c(5,1)) 
par(mar=c(0.5,0.5,1,0.5), oma=rep(3, 4), las=1) 
plot(wmap, main="Bike Parking Lots in Vienna", col=bezirksfarben[wmap$BEZNR]) 

# add bike parking lots
plot(smap, add=TRUE, col = "grey")
draw.circle(coordinates(bmap)[,1], coordinates(bmap)[,2],hundm,border=rgb(255,255,0,maxColorValue=255),col=rgb(255,255,0,maxColorValue=255))
text(as.character(wmap$BEZ_RZ), x = centroids@coords[,1], y = centroids@coords[,2], col="orangered",cex=0.8,font=2)

# Legend
par(mar=c(1,0.5,3,0.5)) 
colseq <- seq(range(lotdensity)[1],range(lotdensity)[2],20) 
image(x=colseq,y=1,z=matrix(seq_along(colseq)), col=colfunc(10), main=expression(paste("Bike parking lot density per district km"^-2)),axes=F) 
axis(1)

Null

Plot 2 - Vienna Map with Bike Parking Lots (Continous Density)

# Transformation of bike parking lots shape to data.frame for ggplot2
RK <- data.frame(coordinates(bmap)) 
colnames(RK) <- c("long","lat") 
ws2 <- fortify(smap,region="OBJECTID")  
wmap2 <- wmap 
# assign ID
wmap2@data$id <- rownames(wmap2@data) 
# transform to data.frame  
test1 <- fortify(wmap2, region="id")   
# This may take a while...
ggplot(data=test1) + 
  aes(x=long,y=lat) + 
  geom_polygon(aes(group=group),col="black",fill=NA) + 
  geom_point(data=RK,aes(x=long,y=lat)) + 
  geom_line(data=ws2,aes(group=group))+ xlab("longitude")+ylab("latitude") + 
  stat_density2d(data=RK,aes(fill = ..level..),size=1,bins=200,alpha=0.1, geom="polygon",n=100) +  
  ggtitle("Bike Parking Lots in Vienna 2015")+ scale_fill_continuous(name = "Kernel Density") + 
  theme_bw()

Null

Comments/Pull Requests welcome!

Authors: Christian Brandstaetter with minor modifications by Mario Annau