vignettes/gisfin_tutorial.md
In rOpenGov/gisfin: Finland GIS R Tools
gisfin - tutorial
This R package provides tools to access open spatial data in Finland
as part of the rOpenGov project.
For contact information and source code, see the
github page
Available data sources
Helsinki region district maps (Helsingin seudun
aluejakokartat)
- Aluejakokartat: kunta, pien-, suur-, tilastoalueet (Helsinki region district
maps)
- Äänestysaluejako: (Helsinki region election district maps)
- Source: Helsingin kaupungin Kiinteistövirasto (HKK)
Helsinki spatial data (Helsingin seudun avoimia
paikkatietoaineistoja)
- Seutukartta (Helsinki Region Maps)
- Helsingin piirijako (District Division of the City of Helsinki)
- Seudullinen osoiteluettelo (Regional Address List)
- Helsingin osoiteluettelo (Register of Addresses of the City of Helsinki)
- Rakennusrekisterin ote (Helsinki building registry)
- Source: Helsingin kaupungin Kiinteistövirasto (HKK)
National Land Survey data (Maanmittauslaitoksen avointa
dataa)
- Yleiskartat: kunta-, maakuntarajat (municipality and province borders)
- Source: Maanmittauslaitos (MML)
IP address geographic coordinates
Statistics Finland geospatial data (Tilastokeskuksen paikkatietoaineistoja)
- Väestöruutuaineisto (Population grid)
- Tuotanto- ja teollisuuslaitokset (Production and industrial facilities)
- Oppilaitokset (Educational institutions)
- Tieliikenneonnettomuudet (Road accidents)
- Source: Statistics Finland
Finnish postal code areas (Suomalaiset postinumero KML-muodossa)
- Source: Duukkis
Examples (Further usage examples)
List of potential data sources to be added to the package can be found
here.
Installation
Requirements
The gisfin package uses the
rgdal package, which
depends on GDAL (Geospatial Data Abstraction Library).
Some rgdal installation tips for various platforms are listed below. The
gisfin package has been tested with recent versions of the dependency packages
and libraries and it is recommended to use the recent releases. The older versions
are known to cause problems in some cases. If you encounter problems, please contact
us by email: louhos@googlegroups.com.
Windows
Install binaries from CRAN
OSX
Follow these instructions to install rgeos and rgdal on OSX. If these don't work, install the rgdal from KyngChaos Wiki.This is preferred over using the CRAN binaries.
Linux
Install the following packages through your distribution's package manager
Ubuntu/Debian
sudo apt-get -y install libgdal1-dev libproj-dev
Fedora
sudo yum -y install gdal-devel proj-devel
openSUSE
sudo zypper --non-interactive in libgdal-devel libproj-devel
Additional dependencies
These may be needed:
GDAL,
freeglut,
XML,
GEOS and
PROJ.4.
Installing the package
Development version for developers:
install.packages("devtools")
library("devtools")
install_github("ropengov/gisfin")
Load package.
library("gisfin")
Helsinki region district maps
Helsinki region district maps (Helsingin seudun aluejakokartat) from
Helsingin kaupungin Kiinteistövirasto (HKK).
List available maps with get_helsinki_aluejakokartat().
get_helsinki_aluejakokartat()
## [1] "kunta" "pienalue" "pienalue_piste"
## [4] "suuralue" "suuralue_piste" "tilastoalue"
## [7] "tilastoalue_piste" "aanestysalue"
Below the 'suuralue' districts is used for plotting examples with spplot() and
ggplot2. The other district types can be plotted
similarly.
Plot with spplot
Retrieve 'suuralue' spatial object with get_helsinki_aluejakokartat() and plot
with spplot().
sp.suuralue <- get_helsinki_aluejakokartat(map.specifier="suuralue")
spplot(sp.suuralue, zcol="Name")
Function generate_map_colours() allows nice region colouring separable
adjacent regions. This is used here with the rainbow() colour scale to plot
the regions with spplot().
sp.suuralue@data$COL <- factor(generate_map_colours(sp=sp.suuralue))
spplot(sp.suuralue, zcol="COL",
col.regions=rainbow(length(levels(sp.suuralue@data$COL))),
colorkey=FALSE)
Plot with ggplot2
Use the 'sp.suuralue' retrieved above, and retrieve also the center points of
the districts. Use sp2df() function to tranform the spatial objects into data
frames. Plot with ggplot2, using blank map theme with
get_theme_map().
# Retrieve center points
sp.suuralue.piste <- get_helsinki_aluejakokartat(map.specifier="suuralue_piste")
# Get data frames
df.suuralue <- sp2df(sp.suuralue)
df.suuralue.piste <- sp2df(sp.suuralue.piste)
# Set map theme
library(ggplot2)
theme_set(get_theme_map())
# Plot regions, add labels using the points data
ggplot(df.suuralue, aes(x=long, y=lat)) +
geom_polygon(aes(fill=COL, group=Name)) +
geom_text(data=df.suuralue.piste, aes(label=Name)) +
theme(legend.position="none")
Plot election districts
Retrieve and plot äänetysaluejako (election districts) with
get_helsinki_aluejakokartat() and spplot(), use colours to separate
municipalities.
sp.aanestys <- get_helsinki_aluejakokartat(map.specifier="aanestysalue")
spplot(sp.aanestys, zcol="KUNTA",
col.regions=rainbow(length(levels(sp.aanestys@data$KUNTA))),
colorkey=FALSE)
Helsinki spatial data
Other Helsinki region spatial data from
Helsingin Kaupungin Kiinteistövirasto (HKK).
List available spatial data with get_helsinki_spatial().
get_helsinki_spatial()
Retrieve municipality map for the larger Helsinki region with
get_helsinki_spatial() and transform coordinates with sp::spTransform().
sp.piiri <- get_helsinki_spatial(map.type="piirijako",
map.specifier="ALUEJAKO_PERUSPIIRI")
# Check current coordinates
sp.piiri@proj4string
# Transform coordinates to WGS84
sp.piiri <- sp::spTransform(sp.piiri, CRS("+proj=longlat +datum=WGS84"))
National Land Survey Finland
Spatial data from National Land Survey Finland
(Maanmittauslaitos, MML). These data are preprocessed into RData format, see
details here.
Retrieve regional borders for Finland with get_mml().
# Get a specific map
sp.mml <- get_mml(map.id="Yleiskartta-4500", data.id="HallintoAlue")
# Investigate available variables in this map
library(knitr)
kable(head(as.data.frame(sp.mml)))
| | Kohderyhma| Kohdeluokk| Enklaavi|AVI |Maakunta |Kunta |AVI_ni1 |AVI_ni2 |Maaku_ni1 |Maaku_ni2 |Kunta_ni1 |Kunta_ni2 |Kieli_ni1 |Kieli_ni2 |AVI.FI |Kieli.FI |Maakunta.FI |Kunta.FI |
|:---|----------:|----------:|--------:|:---|:--------|:-----|:-----------------------------------------|:--------------------------------------------------|:-----------------|:-------------------|:---------|:---------|:---------|:---------|:-----------------------------------------|:--------|:-----------------|:--------|
|005 | 71| 84200| 1|4 |14 |005 |Länsi- ja Sisä-Suomen aluehallintovirasto |Regionförvaltningsverket i Västra och Inre Finland |Etelä-Pohjanmaa |Södra Österbotten |Alajärvi |N_A |Suomi |N_A |Länsi- ja Sisä-Suomen aluehallintovirasto |Suomi |Etelä-Pohjanmaa |NA |
|009 | 71| 84200| 1|5 |17 |009 |Pohjois-Suomen aluehallintovirasto |Regionförvaltningsverket i Norra Finland |Pohjois-Pohjanmaa |Norra Österbotten |Alavieska |N_A |Suomi |N_A |Pohjois-Suomen aluehallintovirasto |Suomi |Pohjois-Pohjanmaa |NA |
|010 | 71| 84200| 1|4 |14 |010 |Länsi- ja Sisä-Suomen aluehallintovirasto |Regionförvaltningsverket i Västra och Inre Finland |Etelä-Pohjanmaa |Södra Österbotten |Alavus |N_A |Suomi |N_A |Länsi- ja Sisä-Suomen aluehallintovirasto |Suomi |Etelä-Pohjanmaa |NA |
|016 | 71| 84200| 1|1 |07 |016 |Etelä-Suomen aluehallintovirasto |Regionförvaltningsverket i Södra Finland |Päijät-Häme |Päijänne-Tavastland |Asikkala |N_A |Suomi |N_A |Etelä-Suomen aluehallintovirasto |Suomi |Päijät-Häme |NA |
|018 | 71| 84200| 1|1 |01 |018 |Etelä-Suomen aluehallintovirasto |Regionförvaltningsverket i Södra Finland |Uusimaa |Nyland |Askola |N_A |Suomi |N_A |Etelä-Suomen aluehallintovirasto |Suomi |Uusimaa |NA |
|019 | 71| 84200| 1|2 |02 |019 |Lounais-Suomen aluehallintovirasto |Regionförvaltningsverket i Sydvästra Finland |Varsinais-Suomi |Egentliga Finland |Aura |N_A |Suomi |N_A |Lounais-Suomen aluehallintovirasto |Suomi |Varsinais-Suomi |NA |
You can list other available data sets:
list_mml_datasets()
## $`2012`
## character(0)
##
## $`2016`
## character(0)
##
## $`Maastotietokanta-tiesto1`
## [1] "N61_v"
##
## $`Maastotietokanta-tiesto2`
## [1] "N62_p" "N62_s" "N62_t" "N62_v"
##
## $`Yleiskartta-1000`
## [1] "AmpumaRaja" "HallintoAlue"
## [3] "HallintoAlue_DataFrame" "HallintoalueRaja"
## [5] "KaasuJohto" "KarttanimiPiste500"
## [7] "KarttanimiPiste1000" "KorkeusAlue"
## [9] "KorkeusViiva500" "KorkeusViiva1000"
## [11] "LentokenttaPiste" "LiikenneAlue"
## [13] "MaaAlue" "Maasto1Reuna"
## [15] "Maasto2Alue" "MetsaRaja"
## [17] "PeltoAlue" "RautatieViiva"
## [19] "SahkoLinja" "SuojaAlue"
## [21] "SuojametsaRaja" "SuojeluAlue"
## [23] "TaajamaAlue" "TaajamaPiste"
## [25] "TieViiva" "VesiAlue"
## [27] "VesiViiva"
##
## $`Yleiskartta-4500`
## [1] "HallintoAlue" "HallintoalueRaja" "KarttanimiPiste2000"
## [4] "KarttanimiPiste4500" "KarttanimiPiste8000" "KorkeusAlue"
## [7] "KorkeusViiva" "Maasto1Reuna" "RautatieViiva"
## [10] "TaajamaPiste2000" "TaajamaPiste4500" "TaajamaPiste8000"
## [13] "TieViiva2000" "TieViiva4500" "TieViiva8000"
## [16] "VesiAlue" "VesiViiva2000" "VesiViiva4500"
## [19] "VesiViiva8000"
Further examples
Visualizing Finnish municipalities with your own data
Here we show examples with the standard shape tools. For interactive maps, see leaflet and rMaps. Examples to be added later.
First, retrieve population data (2013) for Finnish municipalities:
# Get municipality population data from Statistics Finland
# using the pxweb package
library(pxweb)
mydata <- get_pxweb_data(url = "http://pxwebapi2.stat.fi/PXWeb/api/v1/fi/Kuntien_talous_ja_toiminta/Kunnat/ktt14/080_ktt14_2013_fi.px",
dims = list(Alue = c('*'),
Tunnusluku = c('30'),
Vuosi = c('Arvo')),
clean = TRUE)
# Pick municipality ID from the text field
mydata$Kuntakoodi <- sapply(strsplit(as.character(mydata$Alue), " "), function (x) x[[1]])
mydata$Kunta <- sapply(strsplit(as.character(mydata$Alue), " "), function (x) x[[2]])
# Rename fields for clarity
mydata$Asukasluku <- mydata$values
# Pick only the necessary fields for clarity
mydata <- mydata[, c("Kunta", "Kuntakoodi", "Asukasluku")]
Visualize population with Land Survey Finland (MML) maps. See also blog post on this topic. Use a fast wrapper that generates ggplot2-object that can be further modified if necessary:
# Get the municipality map for visualization
sp <- get_municipality_map(data.source = "MML")
# Merge the Finnish map shape file and the population data based on
# the 'Kunta' field. The population data contains also some other
# regions besides municipalities. These will be ignored when merged
# with the municipality map:
sp2 <- sp::merge(sp, mydata, all.x = TRUE, by.x = "kuntakoodi", by.y="Kuntakoodi")
p <- region_plot(sp2, color = "Asukasluku", region = "kuntakoodi", by = 100000)
print(p)
Using GADM maps
Same with GADM maps. You can select the desired maps at the GADM service. Choose Finland and file format R. This will give the link to the Finnish municipality data file. GADM contains very useful maps but the Finnish municipality map data seems a bit outdated:
# Load municipality borders from GADM:
# sp <- get_municipality_map(data.source = "GADM") # also possible
gadm.url <- "http://biogeo.ucdavis.edu/data/gadm2/R/FIN_adm4.RData"
con <- url(gadm.url)
load(con); close(con)
# Convert NAME field into factor (needed for plots)
gadm$NAME_4 <- factor(gadm$NAME_4)
# Merge the Finnish map shape file and the population data based on
# the 'Kunta' field (see above)
gadm2 <- sp::merge(gadm, mydata, by.x = "NAME_4", by.y = "Kunta", all.x = TRUE)
# Plot the shape file, colour municipalities by population
# It turns out that not all municipality names can be matched.
# We are happy to add solutions here if you have any.
spplot(gadm2, zcol="Asukasluku", colorkey=TRUE, main = "Population in Finnish municipalities")
Geocoding
Get geocodes for given location (address etc.) using one of the available
services. Please read carefully the usage policies for the different services:
The function get_geocode() returns both latitude and longitude for the first
hit, and the raw output (varies depending on the service used).
Warning! The geocode results may vary between sources, use with care!
gc1 <- get_geocode("Mannerheimintie 100, Helsinki", service="okf")
unlist(gc1[1:2])
## lat lon
## 60.18856 24.91736
gc2 <- get_geocode("Mannerheimintie 100, Helsinki", service="openstreetmap")
unlist(gc2[1:2])
## lat lon
## 60.18864 24.91750
gc3 <- get_geocode("Mannerheimintie 100, Helsinki", service="google")
unlist(gc3[1:2])
## lat lon
## 60.18864 24.91753
Get geocode for a city (instead of street address; only implemented for OSM at the moment):
gc4 <- get_geocode("&city=Helsinki", service="openstreetmap", raw_query=T)
unlist(gc4[1:2])
## lat lon
## 60.16741 24.94257
IP Location
Geographic coordinates for a given IP-address from
Data Science Toolkit:
ip_location("137.224.252.10")
## [1] "51.9667015075684" "5.66669988632202"
Statistics Finland geospatial data
Geospatial data provided by
Statistics Finland.
Retrieve a list of the available data sets for population density. In case the
service is unreachable, character(0) is returned.
request <- gisfin::GeoStatFiWFSRequest$new()$getPopulationLayers()
client <- gisfin::GeoStatFiWFSClient$new(request)
layers <- client$listLayers()
if (length(layers) > 0) layers
## [1] "vaestoruutu:vaki2005_1km" "vaestoruutu:vaki2005_1km_kp"
## [3] "vaestoruutu:vaki2010_1km" "vaestoruutu:vaki2010_1km_kp"
## [5] "vaestoruutu:vaki2011_1km" "vaestoruutu:vaki2011_1km_kp"
## [7] "vaestoruutu:vaki2012_1km" "vaestoruutu:vaki2012_1km_kp"
## [9] "vaestoruutu:vaki2013_1km" "vaestoruutu:vaki2013_1km_kp"
## [11] "vaestoruutu:vaki2014_1km" "vaestoruutu:vaki2014_1km_kp"
## [13] "vaestoruutu:vaki2015_1km" "vaestoruutu:vaki2015_1km_kp"
## [15] "vaestoruutu:vaki2005_5km" "vaestoruutu:vaki2010_5km"
## [17] "vaestoruutu:vaki2011_5km" "vaestoruutu:vaki2012_5km"
## [19] "vaestoruutu:vaki2013_5km" "vaestoruutu:vaki2014_5km"
## [21] "vaestoruutu:vaki2015_5km"
## attr(,"driver")
## [1] "WFS"
## attr(,"nlayers")
## [1] 21
Get population density in year 2005 on a 5 km x 5 km grid, convert to
RasterStack object and plot on log scale.
library(raster)
request$getPopulation(layers[11])
client <- gisfin::GeoStatFiWFSClient$new(request)
population <- client$getLayer(layers[11])
if (length(population) > 0) {
x <- sp::SpatialPixelsDataFrame(coordinates(population), population@data, proj4string=population@proj4string)
population <- raster::stack(x)
plot(log(population[["vaesto"]]))
}
Finnish postal code areas
Spatial data provided by Duukkis.
Get the postal code areas and plot them for the Helsinki region.
pnro.sp <- get_postalcode_areas()
pnro.sp@data$COL <- factor(generate_map_colours(sp=pnro.sp))
pnro.pks.sp <- pnro.sp[substr(pnro.sp$pnro, 1, 2) %in% c("00", "01", "02"), ]
spplot(pnro.pks.sp, zcol="COL",
col.regions=rainbow(length(levels(pnro.pks.sp@data$COL))),
colorkey=FALSE)
Citation
Citing the data: See help() to get citation information for each data
source individually.
Citing the R package:
citation("gisfin")
Kindly cite the gisfin R package as follows:
(C) Joona Lehtomaki, Juuso Parkkinen, Leo Lahti, Jussi Jousimo
and Janne Aukia 2015-2016. gisfin R package
A BibTeX entry for LaTeX users is
@Misc{,
title = {gisfin R package},
author = {Joona Lehtomaki and Juuso Parkkinen and Leo Lahti and Jussi Jousimo and Janne Aukia},
year = {2015-2016},
}
Many thanks for all contributors! For more info, see:
https://github.com/rOpenGov/gisfin
Session info
This vignette was created with
sessionInfo()
## R version 3.3.1 (2016-06-21)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.1 LTS
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=de_BE.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=de_BE.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=de_BE.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=de_BE.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] raster_2.5-8 pxweb_0.6.3 ggplot2_2.1.0 maptools_0.8-39
## [5] rgeos_0.3-21 gisfin_0.9.27 R6_2.2.0 rgdal_1.1-10
## [9] sp_1.2-3 knitr_1.14
##
## loaded via a namespace (and not attached):
## [1] Rcpp_0.12.7 spdep_0.6-8 formatR_1.4 plyr_1.8.4
## [5] highr_0.6 bitops_1.0-6 LearnBayes_2.15 tools_3.3.1
## [9] boot_1.3-18 digest_0.6.10 jsonlite_1.1 evaluate_0.10
## [13] nlme_3.1-128 gtable_0.2.0 lattice_0.20-34 Matrix_1.2-7.1
## [17] curl_2.1 coda_0.18-1 httr_1.2.1 stringr_1.1.0
## [21] gtools_3.5.0 grid_3.3.1 data.table_1.9.6 XML_3.98-1.4
## [25] foreign_0.8-67 RJSONIO_1.3-0 gdata_2.17.0 deldir_0.1-12
## [29] magrittr_1.5 scales_0.4.0 MASS_7.3-45 splines_3.3.1
## [33] gmodels_2.16.2 colorspace_1.2-7 labeling_0.3 stringi_1.1.2
## [37] RCurl_1.95-4.8 munsell_0.4.3 chron_2.3-47 rjson_0.2.15
rOpenGov/gisfin documentation built on May 26, 2019, 8:48 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
gisfin - tutorial
This R package provides tools to access open spatial data in Finland as part of the rOpenGov project.
For contact information and source code, see the github page
Available data sources
Helsinki region district maps (Helsingin seudun aluejakokartat)
- Aluejakokartat: kunta, pien-, suur-, tilastoalueet (Helsinki region district maps)
- Äänestysaluejako: (Helsinki region election district maps)
- Source: Helsingin kaupungin Kiinteistövirasto (HKK)
Helsinki spatial data (Helsingin seudun avoimia paikkatietoaineistoja)
- Seutukartta (Helsinki Region Maps)
- Helsingin piirijako (District Division of the City of Helsinki)
- Seudullinen osoiteluettelo (Regional Address List)
- Helsingin osoiteluettelo (Register of Addresses of the City of Helsinki)
- Rakennusrekisterin ote (Helsinki building registry)
- Source: Helsingin kaupungin Kiinteistövirasto (HKK)
National Land Survey data (Maanmittauslaitoksen avointa dataa)
- Yleiskartat: kunta-, maakuntarajat (municipality and province borders)
- Source: Maanmittauslaitos (MML)
IP address geographic coordinates
Statistics Finland geospatial data (Tilastokeskuksen paikkatietoaineistoja)
- Väestöruutuaineisto (Population grid)
- Tuotanto- ja teollisuuslaitokset (Production and industrial facilities)
- Oppilaitokset (Educational institutions)
- Tieliikenneonnettomuudet (Road accidents)
- Source: Statistics Finland
Finnish postal code areas (Suomalaiset postinumero KML-muodossa)
- Source: Duukkis
Examples (Further usage examples)
List of potential data sources to be added to the package can be found here.
Installation
Requirements
The gisfin package uses the rgdal package, which depends on GDAL (Geospatial Data Abstraction Library). Some rgdal installation tips for various platforms are listed below. The gisfin package has been tested with recent versions of the dependency packages and libraries and it is recommended to use the recent releases. The older versions are known to cause problems in some cases. If you encounter problems, please contact us by email: louhos@googlegroups.com.
Windows
Install binaries from CRAN
OSX
Follow these instructions to install rgeos and rgdal on OSX. If these don't work, install the rgdal from KyngChaos Wiki.This is preferred over using the CRAN binaries.
Linux
Install the following packages through your distribution's package manager
Ubuntu/Debian
sudo apt-get -y install libgdal1-dev libproj-dev
Fedora
sudo yum -y install gdal-devel proj-devel
openSUSE
sudo zypper --non-interactive in libgdal-devel libproj-devel
Additional dependencies
These may be needed: GDAL, freeglut, XML, GEOS and PROJ.4.
Installing the package
Development version for developers:
install.packages("devtools")
library("devtools")
install_github("ropengov/gisfin")
Load package.
library("gisfin")
Helsinki region district maps
Helsinki region district maps (Helsingin seudun aluejakokartat) from Helsingin kaupungin Kiinteistövirasto (HKK).
List available maps with get_helsinki_aluejakokartat().
get_helsinki_aluejakokartat()
## [1] "kunta" "pienalue" "pienalue_piste"
## [4] "suuralue" "suuralue_piste" "tilastoalue"
## [7] "tilastoalue_piste" "aanestysalue"
Below the 'suuralue' districts is used for plotting examples with spplot() and
ggplot2. The other district types can be plotted
similarly.
Plot with spplot
Retrieve 'suuralue' spatial object with get_helsinki_aluejakokartat() and plot
with spplot().
sp.suuralue <- get_helsinki_aluejakokartat(map.specifier="suuralue")
spplot(sp.suuralue, zcol="Name")
Function generate_map_colours() allows nice region colouring separable
adjacent regions. This is used here with the rainbow() colour scale to plot
the regions with spplot().
sp.suuralue@data$COL <- factor(generate_map_colours(sp=sp.suuralue))
spplot(sp.suuralue, zcol="COL",
col.regions=rainbow(length(levels(sp.suuralue@data$COL))),
colorkey=FALSE)
Plot with ggplot2
Use the 'sp.suuralue' retrieved above, and retrieve also the center points of
the districts. Use sp2df() function to tranform the spatial objects into data
frames. Plot with ggplot2, using blank map theme with
get_theme_map().
# Retrieve center points
sp.suuralue.piste <- get_helsinki_aluejakokartat(map.specifier="suuralue_piste")
# Get data frames
df.suuralue <- sp2df(sp.suuralue)
df.suuralue.piste <- sp2df(sp.suuralue.piste)
# Set map theme
library(ggplot2)
theme_set(get_theme_map())
# Plot regions, add labels using the points data
ggplot(df.suuralue, aes(x=long, y=lat)) +
geom_polygon(aes(fill=COL, group=Name)) +
geom_text(data=df.suuralue.piste, aes(label=Name)) +
theme(legend.position="none")
Plot election districts
Retrieve and plot äänetysaluejako (election districts) with
get_helsinki_aluejakokartat() and spplot(), use colours to separate
municipalities.
sp.aanestys <- get_helsinki_aluejakokartat(map.specifier="aanestysalue")
spplot(sp.aanestys, zcol="KUNTA",
col.regions=rainbow(length(levels(sp.aanestys@data$KUNTA))),
colorkey=FALSE)
Helsinki spatial data
Other Helsinki region spatial data from Helsingin Kaupungin Kiinteistövirasto (HKK).
List available spatial data with get_helsinki_spatial().
get_helsinki_spatial()
Retrieve municipality map for the larger Helsinki region with
get_helsinki_spatial() and transform coordinates with sp::spTransform().
sp.piiri <- get_helsinki_spatial(map.type="piirijako",
map.specifier="ALUEJAKO_PERUSPIIRI")
# Check current coordinates
sp.piiri@proj4string
# Transform coordinates to WGS84
sp.piiri <- sp::spTransform(sp.piiri, CRS("+proj=longlat +datum=WGS84"))
National Land Survey Finland
Spatial data from National Land Survey Finland (Maanmittauslaitos, MML). These data are preprocessed into RData format, see details here.
Retrieve regional borders for Finland with get_mml().
# Get a specific map
sp.mml <- get_mml(map.id="Yleiskartta-4500", data.id="HallintoAlue")
# Investigate available variables in this map
library(knitr)
kable(head(as.data.frame(sp.mml)))
| | Kohderyhma| Kohdeluokk| Enklaavi|AVI |Maakunta |Kunta |AVI_ni1 |AVI_ni2 |Maaku_ni1 |Maaku_ni2 |Kunta_ni1 |Kunta_ni2 |Kieli_ni1 |Kieli_ni2 |AVI.FI |Kieli.FI |Maakunta.FI |Kunta.FI | |:---|----------:|----------:|--------:|:---|:--------|:-----|:-----------------------------------------|:--------------------------------------------------|:-----------------|:-------------------|:---------|:---------|:---------|:---------|:-----------------------------------------|:--------|:-----------------|:--------| |005 | 71| 84200| 1|4 |14 |005 |Länsi- ja Sisä-Suomen aluehallintovirasto |Regionförvaltningsverket i Västra och Inre Finland |Etelä-Pohjanmaa |Södra Österbotten |Alajärvi |N_A |Suomi |N_A |Länsi- ja Sisä-Suomen aluehallintovirasto |Suomi |Etelä-Pohjanmaa |NA | |009 | 71| 84200| 1|5 |17 |009 |Pohjois-Suomen aluehallintovirasto |Regionförvaltningsverket i Norra Finland |Pohjois-Pohjanmaa |Norra Österbotten |Alavieska |N_A |Suomi |N_A |Pohjois-Suomen aluehallintovirasto |Suomi |Pohjois-Pohjanmaa |NA | |010 | 71| 84200| 1|4 |14 |010 |Länsi- ja Sisä-Suomen aluehallintovirasto |Regionförvaltningsverket i Västra och Inre Finland |Etelä-Pohjanmaa |Södra Österbotten |Alavus |N_A |Suomi |N_A |Länsi- ja Sisä-Suomen aluehallintovirasto |Suomi |Etelä-Pohjanmaa |NA | |016 | 71| 84200| 1|1 |07 |016 |Etelä-Suomen aluehallintovirasto |Regionförvaltningsverket i Södra Finland |Päijät-Häme |Päijänne-Tavastland |Asikkala |N_A |Suomi |N_A |Etelä-Suomen aluehallintovirasto |Suomi |Päijät-Häme |NA | |018 | 71| 84200| 1|1 |01 |018 |Etelä-Suomen aluehallintovirasto |Regionförvaltningsverket i Södra Finland |Uusimaa |Nyland |Askola |N_A |Suomi |N_A |Etelä-Suomen aluehallintovirasto |Suomi |Uusimaa |NA | |019 | 71| 84200| 1|2 |02 |019 |Lounais-Suomen aluehallintovirasto |Regionförvaltningsverket i Sydvästra Finland |Varsinais-Suomi |Egentliga Finland |Aura |N_A |Suomi |N_A |Lounais-Suomen aluehallintovirasto |Suomi |Varsinais-Suomi |NA |
You can list other available data sets:
list_mml_datasets()
## $`2012`
## character(0)
##
## $`2016`
## character(0)
##
## $`Maastotietokanta-tiesto1`
## [1] "N61_v"
##
## $`Maastotietokanta-tiesto2`
## [1] "N62_p" "N62_s" "N62_t" "N62_v"
##
## $`Yleiskartta-1000`
## [1] "AmpumaRaja" "HallintoAlue"
## [3] "HallintoAlue_DataFrame" "HallintoalueRaja"
## [5] "KaasuJohto" "KarttanimiPiste500"
## [7] "KarttanimiPiste1000" "KorkeusAlue"
## [9] "KorkeusViiva500" "KorkeusViiva1000"
## [11] "LentokenttaPiste" "LiikenneAlue"
## [13] "MaaAlue" "Maasto1Reuna"
## [15] "Maasto2Alue" "MetsaRaja"
## [17] "PeltoAlue" "RautatieViiva"
## [19] "SahkoLinja" "SuojaAlue"
## [21] "SuojametsaRaja" "SuojeluAlue"
## [23] "TaajamaAlue" "TaajamaPiste"
## [25] "TieViiva" "VesiAlue"
## [27] "VesiViiva"
##
## $`Yleiskartta-4500`
## [1] "HallintoAlue" "HallintoalueRaja" "KarttanimiPiste2000"
## [4] "KarttanimiPiste4500" "KarttanimiPiste8000" "KorkeusAlue"
## [7] "KorkeusViiva" "Maasto1Reuna" "RautatieViiva"
## [10] "TaajamaPiste2000" "TaajamaPiste4500" "TaajamaPiste8000"
## [13] "TieViiva2000" "TieViiva4500" "TieViiva8000"
## [16] "VesiAlue" "VesiViiva2000" "VesiViiva4500"
## [19] "VesiViiva8000"
Further examples
Visualizing Finnish municipalities with your own data
Here we show examples with the standard shape tools. For interactive maps, see leaflet and rMaps. Examples to be added later.
First, retrieve population data (2013) for Finnish municipalities:
# Get municipality population data from Statistics Finland
# using the pxweb package
library(pxweb)
mydata <- get_pxweb_data(url = "http://pxwebapi2.stat.fi/PXWeb/api/v1/fi/Kuntien_talous_ja_toiminta/Kunnat/ktt14/080_ktt14_2013_fi.px",
dims = list(Alue = c('*'),
Tunnusluku = c('30'),
Vuosi = c('Arvo')),
clean = TRUE)
# Pick municipality ID from the text field
mydata$Kuntakoodi <- sapply(strsplit(as.character(mydata$Alue), " "), function (x) x[[1]])
mydata$Kunta <- sapply(strsplit(as.character(mydata$Alue), " "), function (x) x[[2]])
# Rename fields for clarity
mydata$Asukasluku <- mydata$values
# Pick only the necessary fields for clarity
mydata <- mydata[, c("Kunta", "Kuntakoodi", "Asukasluku")]
Visualize population with Land Survey Finland (MML) maps. See also blog post on this topic. Use a fast wrapper that generates ggplot2-object that can be further modified if necessary:
# Get the municipality map for visualization
sp <- get_municipality_map(data.source = "MML")
# Merge the Finnish map shape file and the population data based on
# the 'Kunta' field. The population data contains also some other
# regions besides municipalities. These will be ignored when merged
# with the municipality map:
sp2 <- sp::merge(sp, mydata, all.x = TRUE, by.x = "kuntakoodi", by.y="Kuntakoodi")
p <- region_plot(sp2, color = "Asukasluku", region = "kuntakoodi", by = 100000)
print(p)
Using GADM maps
Same with GADM maps. You can select the desired maps at the GADM service. Choose Finland and file format R. This will give the link to the Finnish municipality data file. GADM contains very useful maps but the Finnish municipality map data seems a bit outdated:
# Load municipality borders from GADM:
# sp <- get_municipality_map(data.source = "GADM") # also possible
gadm.url <- "http://biogeo.ucdavis.edu/data/gadm2/R/FIN_adm4.RData"
con <- url(gadm.url)
load(con); close(con)
# Convert NAME field into factor (needed for plots)
gadm$NAME_4 <- factor(gadm$NAME_4)
# Merge the Finnish map shape file and the population data based on
# the 'Kunta' field (see above)
gadm2 <- sp::merge(gadm, mydata, by.x = "NAME_4", by.y = "Kunta", all.x = TRUE)
# Plot the shape file, colour municipalities by population
# It turns out that not all municipality names can be matched.
# We are happy to add solutions here if you have any.
spplot(gadm2, zcol="Asukasluku", colorkey=TRUE, main = "Population in Finnish municipalities")
Geocoding
Get geocodes for given location (address etc.) using one of the available services. Please read carefully the usage policies for the different services:
The function get_geocode() returns both latitude and longitude for the first
hit, and the raw output (varies depending on the service used).
Warning! The geocode results may vary between sources, use with care!
gc1 <- get_geocode("Mannerheimintie 100, Helsinki", service="okf")
unlist(gc1[1:2])
## lat lon
## 60.18856 24.91736
gc2 <- get_geocode("Mannerheimintie 100, Helsinki", service="openstreetmap")
unlist(gc2[1:2])
## lat lon
## 60.18864 24.91750
gc3 <- get_geocode("Mannerheimintie 100, Helsinki", service="google")
unlist(gc3[1:2])
## lat lon
## 60.18864 24.91753
Get geocode for a city (instead of street address; only implemented for OSM at the moment):
gc4 <- get_geocode("&city=Helsinki", service="openstreetmap", raw_query=T)
unlist(gc4[1:2])
## lat lon
## 60.16741 24.94257
IP Location
Geographic coordinates for a given IP-address from Data Science Toolkit:
ip_location("137.224.252.10")
## [1] "51.9667015075684" "5.66669988632202"
Statistics Finland geospatial data
Geospatial data provided by Statistics Finland.
Retrieve a list of the available data sets for population density. In case the
service is unreachable, character(0) is returned.
request <- gisfin::GeoStatFiWFSRequest$new()$getPopulationLayers()
client <- gisfin::GeoStatFiWFSClient$new(request)
layers <- client$listLayers()
if (length(layers) > 0) layers
## [1] "vaestoruutu:vaki2005_1km" "vaestoruutu:vaki2005_1km_kp"
## [3] "vaestoruutu:vaki2010_1km" "vaestoruutu:vaki2010_1km_kp"
## [5] "vaestoruutu:vaki2011_1km" "vaestoruutu:vaki2011_1km_kp"
## [7] "vaestoruutu:vaki2012_1km" "vaestoruutu:vaki2012_1km_kp"
## [9] "vaestoruutu:vaki2013_1km" "vaestoruutu:vaki2013_1km_kp"
## [11] "vaestoruutu:vaki2014_1km" "vaestoruutu:vaki2014_1km_kp"
## [13] "vaestoruutu:vaki2015_1km" "vaestoruutu:vaki2015_1km_kp"
## [15] "vaestoruutu:vaki2005_5km" "vaestoruutu:vaki2010_5km"
## [17] "vaestoruutu:vaki2011_5km" "vaestoruutu:vaki2012_5km"
## [19] "vaestoruutu:vaki2013_5km" "vaestoruutu:vaki2014_5km"
## [21] "vaestoruutu:vaki2015_5km"
## attr(,"driver")
## [1] "WFS"
## attr(,"nlayers")
## [1] 21
Get population density in year 2005 on a 5 km x 5 km grid, convert to RasterStack object and plot on log scale.
library(raster)
request$getPopulation(layers[11])
client <- gisfin::GeoStatFiWFSClient$new(request)
population <- client$getLayer(layers[11])
if (length(population) > 0) {
x <- sp::SpatialPixelsDataFrame(coordinates(population), population@data, proj4string=population@proj4string)
population <- raster::stack(x)
plot(log(population[["vaesto"]]))
}
Finnish postal code areas
Spatial data provided by Duukkis.
Get the postal code areas and plot them for the Helsinki region.
pnro.sp <- get_postalcode_areas()
pnro.sp@data$COL <- factor(generate_map_colours(sp=pnro.sp))
pnro.pks.sp <- pnro.sp[substr(pnro.sp$pnro, 1, 2) %in% c("00", "01", "02"), ]
spplot(pnro.pks.sp, zcol="COL",
col.regions=rainbow(length(levels(pnro.pks.sp@data$COL))),
colorkey=FALSE)
Citation
Citing the data: See help() to get citation information for each data
source individually.
Citing the R package:
citation("gisfin")
Kindly cite the gisfin R package as follows:
(C) Joona Lehtomaki, Juuso Parkkinen, Leo Lahti, Jussi Jousimo
and Janne Aukia 2015-2016. gisfin R package
A BibTeX entry for LaTeX users is
@Misc{,
title = {gisfin R package},
author = {Joona Lehtomaki and Juuso Parkkinen and Leo Lahti and Jussi Jousimo and Janne Aukia},
year = {2015-2016},
}
Many thanks for all contributors! For more info, see:
https://github.com/rOpenGov/gisfin
Session info
This vignette was created with
sessionInfo()
## R version 3.3.1 (2016-06-21)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.1 LTS
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=de_BE.UTF-8 LC_COLLATE=en_US.UTF-8
## [5] LC_MONETARY=de_BE.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=de_BE.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=de_BE.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] raster_2.5-8 pxweb_0.6.3 ggplot2_2.1.0 maptools_0.8-39
## [5] rgeos_0.3-21 gisfin_0.9.27 R6_2.2.0 rgdal_1.1-10
## [9] sp_1.2-3 knitr_1.14
##
## loaded via a namespace (and not attached):
## [1] Rcpp_0.12.7 spdep_0.6-8 formatR_1.4 plyr_1.8.4
## [5] highr_0.6 bitops_1.0-6 LearnBayes_2.15 tools_3.3.1
## [9] boot_1.3-18 digest_0.6.10 jsonlite_1.1 evaluate_0.10
## [13] nlme_3.1-128 gtable_0.2.0 lattice_0.20-34 Matrix_1.2-7.1
## [17] curl_2.1 coda_0.18-1 httr_1.2.1 stringr_1.1.0
## [21] gtools_3.5.0 grid_3.3.1 data.table_1.9.6 XML_3.98-1.4
## [25] foreign_0.8-67 RJSONIO_1.3-0 gdata_2.17.0 deldir_0.1-12
## [29] magrittr_1.5 scales_0.4.0 MASS_7.3-45 splines_3.3.1
## [33] gmodels_2.16.2 colorspace_1.2-7 labeling_0.3 stringi_1.1.2
## [37] RCurl_1.95-4.8 munsell_0.4.3 chron_2.3-47 rjson_0.2.15
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.