The goal of geojp is to provide an easy access to various geographical data of Japan.
You can install the development version of geojp from GitHub with:
install.packages("devtools")
devtools::install_github("babayoshihiko/geojp")Load (attach) package geojp.
library(geojp)Load census boundary information. Specify the prefecture code (code_pref) and municipality code (code_muni). Here is an example for Osaki City (215) in Miyagi Prefecture (4).
sfCensus <- geojp::read_census_tract(code_pref = 4, code_muni = 215)
head(sfCensus)#> Simple feature collection with 6 features and 5 fields
#> Geometry type: POLYGON
#> Dimension: XY
#> Bounding box: xmin: 140.9491 ymin: 38.57324 xmax: 140.965 ymax: 38.57924
#> Geodetic CRS: JGD2000
#> # A tibble: 6 × 6
#> KEY_CODE AREA PERIMETER JINKO SETAI geometry
#> <chr> <dbl> <dbl> <dbl> <dbl> <POLYGON [°]>
#> 1 042150010 42064. 976. 215 59 ((140.9586 38.57839, 140.9582 38.5786…
#> 2 042150020 21813. 896. 88 42 ((140.9568 38.57566, 140.9567 38.5757…
#> 3 042150030 66933. 1286. 176 68 ((140.9625 38.57528, 140.9623 38.5753…
#> 4 042150040 52498. 1233. 156 69 ((140.9605 38.57737, 140.9603 38.577,…
#> 5 042150050 75934. 1390. 205 107 ((140.9574 38.57757, 140.9568 38.5778…
#> 6 042150060 133863. 1574. 490 191 ((140.9548 38.57702, 140.9547 38.5771…
The census has many columns, so only the important ones have been cut out.
Ordinance-designated cities will be in units of administrative
districts. The read_census_odcity() function returns all the wards
with the name of the ordinance-designated city.
sfCensus2 <- geojp::read_census_odcity("京都市")
head(sfCensus2)#> Simple feature collection with 6 features and 5 fields
#> Geometry type: POLYGON
#> Dimension: XY
#> Bounding box: xmin: 135.7368 ymin: 35.04067 xmax: 135.7477 ymax: 35.05123
#> Geodetic CRS: JGD2000
#> # A tibble: 6 × 6
#> KEY_CODE AREA PERIMETER JINKO SETAI geometry
#> <chr> <dbl> <dbl> <dbl> <dbl> <POLYGON [°]>
#> 1 26101001001 55664. 1272. 335 159 ((135.7431 35.04654, 135.743 35.046…
#> 2 26101001002 41500. 1040. 96 44 ((135.7403 35.0478, 135.7398 35.047…
#> 3 26101001003 49730. 951. 807 435 ((135.7388 35.04569, 135.7394 35.04…
#> 4 26101001004 289781. 2896. 867 407 ((135.7471 35.04318, 135.747 35.043…
#> 5 26101001005 52556. 1120. 941 424 ((135.7477 35.04751, 135.7477 35.04…
#> 6 26101001006 46270. 1051. 449 264 ((135.7473 35.05072, 135.7474 35.05…
Additional attribute information is set. Attributes are obtained using
the attr() function. One particularly important attribute is the
source. The source can be retrieved as follows
attr(sfCensus2, "sourceName")
#> [1] "「政府統計の総合窓口(e-Stat)」"
attr(sfCensus2, "sourceURL")
#> [1] "https://www.e-stat.go.jp/gis/"Load the zoning information from the National Land Information. Specify the prefecture code (code_pref) and municipality code (code_muni). The 2011 and 2019 versions are available, so we will try the 2011 version this time.
For more information about the National Land Information, see National Land Information Download Service.
The return value is an sf object.
sfYouto <- geojp::read_landnuminfo_landuse(code_pref = 26, code_muni = 100, year = 2019)The A29_004 and A29_005 columns, which indicate the zoning class,
are of type factor.
levels(sfYouto$A29_005)
#> [1] "第一種低層住居専用地域" "第二種低層住居専用地域"
#> [3] "第一種中高層住居専用地域" "第二種中高層住居専用地域"
#> [5] "第一種住居地域" "第二種住居地域"
#> [7] "準住居地域" "近隣商業地域"
#> [9] "商業地域" "準工業地域"
#> [11] "工業地域" "工業専用地域"
#> [13] "田園住居地域" "不明"Additional attribute information is set. Attributes are obtained using
the attr() function. One particularly important attribute is the
source. The source can be retrieved as follows
attr(sfYouto, "sourceName")
#> [1] "「国土数値情報（行政区域データ）」（国土交通省）"
attr(sfYouto, "sourceURL")
#> [1] "https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-A29-v2_1.html"The attribute “col” is the column name used for color separation. The attribute “palette” is the color palette for color separation. This is matched as closely as possible to the colors of the intended use area according to the Japanese Industrial Standards (JIS).
attr(sfYouto, "palette")
#> [1] "#00BEA9" "#6AD5BD" "#A8D666" "#FAE294" "#F4E268" "#F8D79C" "#FFB580"
#> [8] "#F3A5B9" "#EE534F" "#B3A8CB" "#8AD0E4" "#2CB3DE" "#F4B187" "#FFFFFF"Use package tmap to display the usage area. The last font specification is required only for macOS.
library(tmap)
#>
#> Attaching package: 'tmap'
#> The following object is masked from 'package:datasets':
#>
#> rivers
# Create a map.
myTm <- tm_shape(sfYouto) +
tm_polygons(fill = attr(sfYouto, "col"),
palette = attr(sfYouto, "palette"), alpha = 0.8) +
tm_borders()
#> Deprecated tmap v3 code detected. Code translated to v4
myTm <- myTm +
tm_scale_bar() +
tm_layout(tm_title = "京都市",
legend.text.fontfamily = "HiraginoSans-W3")
#> Warning: As of version 4.0, tm_scale_bar has been renamed to tm_scalebar and is
#> therefore deprecatedDisplay the plot.
myTm
To save, use the tmap_save() function.
tmap_save(tm = myTm, filename = "map.png")You can also superimpose census and zoning maps.
In addition, you can use The Geospatial Information Authority of Japan standard map in tiled format as a base map.
https://maps.gsi.go.jp/development/ichiran.html
library(tmap)
tmap_mode("view")
#> tmap mode set to 'view'
# Create a map.
myTm <- tm_shape(sfCensus2) +
tm_polygons("JINKO", alpha = 0.8)
#> Deprecated tmap v3 code detected. Code translated to v4
myTm <- myTm +
tm_shape(sfYouto) +
tm_polygons(fill = attr(sfYouto, "col"),
palette = attr(sfYouto, "palette"), alpha = 0.8) +
tm_borders()
#> Deprecated tmap v3 code detected. Code translated to v4
myTm <- myTm +
tm_basemap(server = "https://cyberjapandata.gsi.go.jp/xyz/std/{z}/{x}/{y}.png")
myTm <- myTm +
tm_scale_bar() +
tm_layout(tm_title = "京都市",
legend.text.fontfamily = "HiraginoSans-W3")
#> Warning: As of version 4.0, tm_scale_bar has been renamed to tm_scalebar and is
#> therefore deprecated
myTmlibrary(mapview)
mapviewOptions(fgb = FALSE) # needed when creating web pages
mapview(sfYouto[attr(sfYouto, "col")], col.regions = attr(sfYouto, "palette"), fgb = FALSE)