jpmesh

The jpmesh is a package that makes it easy to use “regional mesh (i.e. mesh code JIS X 0410 )” used in Japan from R. Regional mesh is a code given when subdividing Japanese landscape into rectangular subregions by latitude and longitude. Depending on the accuracy of the code, different regional mesh length. By using the same mesh in statistical survey etc., it will become possible to handle the survey results of a large area in the area mesh unit.

jpmesh

In jpmesh, mesh codes and latitude and longitude coordinates are compatible with mesh codes from the first region mesh, which is the standard region mesh, to the quarter regional mesh of the divided region mesh (from 80 km to 125 m). Features include “conversion from latitude and longitude to regional mesh”, “acquisition of latitude and longitude from regional mesh”, “mapping on prefecture unit and leaflet”.

Install

Available CRAN (version 1.1.0), and olso GitHub develop versions.

# CRAN
install.packages("jpmesh")

# the development version from GitHub:
install.packages("remotes")
remotes::install_github("uribo/jpmesh")

library(jpmesh)
library(sf)
library(leaflet)

Convert mesh code to coordinate and vice versa

Return the latitude and longitude for specifying the mesh range from the mesh code.

mesh_to_coords(5133) # 80km

## # A tibble: 1 x 4
##   lng_center lat_center lng_error lat_error
##        <dbl>      <dbl>     <dbl>     <dbl>
## 1       134.       34.3     0.500     0.333

mesh_to_coords(513377) # 10km
# ...
mesh_to_coords(51337783123) # 125m

Convert mesh code to coordinate and vice versa

Find the mesh code within the range from latitude and longitude.

coords_to_mesh(133, 34) # default as 1km meshcode

## [1] "51330000"

coords_to_mesh(133, 34, mesh_size = "80km")

## [1] "5133"

coords_to_mesh(133, 34, mesh_size = "125m")

## [1] "51330000111"

Detect fine and neighborhood mesh codes

mesh_80km <- coords_to_mesh(133, 34, "80km")
# Convert to sfc_POLYGON
mesh_polygon <- mesh_80km %>% 
  export_mesh()

mesh_polygon

## Geometry set for 1 feature 
## geometry type:  POLYGON
## dimension:      XY
## bbox:           xmin: 133 ymin: 34 xmax: 134 ymax: 34.66667
## epsg (SRID):    4326
## proj4string:    +proj=longlat +datum=WGS84 +no_defs

## POLYGON ((133 34, 134 34, 134 34.66667, 133 34....

Detect fine and neighborhood mesh codes

mesh_polygon %>% 
  st_geometry() %>% 
  plot()

Detect fine and neighborhood mesh codes

# Returns a finer mesh of the area of the mesh codes
# Such as, 80km to 10km mesh codes.
meshes_10km <- mesh_80km %>% 
  fine_separate()

meshes_10km

##  [1] "513300" "513301" "513302" "513303" "513304" "513305" "513306"
##  [8] "513307" "513310" "513311" "513312" "513313" "513314" "513315"
## [15] "513316" "513317" "513320" "513321" "513322" "513323" "513324"
## [22] "513325" "513326" "513327" "513330" "513331" "513332" "513333"
## [29] "513334" "513335" "513336" "513337" "513340" "513341" "513342"
## [36] "513343" "513344" "513345" "513346" "513347" "513350" "513351"
## [43] "513352" "513353" "513354" "513355" "513356" "513357" "513360"
## [50] "513361" "513362" "513363" "513364" "513365" "513366" "513367"
## [57] "513370" "513371" "513372" "513373" "513374" "513375" "513376"
## [64] "513377"

Detect fine and neighborhood mesh codes

meshes_10km %>% 
  export_meshes() %>% 
  plot()

Detect fine and neighborhood mesh codes

# the value of the adjacent mesh codes
coords_to_mesh(133, 34, "80km") %>% 
  neighbor_mesh()

## [1] "5032" "5033" "5034" "5132" "5133" "5134" "5232" "5233" "5234"

coords_to_mesh(133, 34, "500m") %>% 
  neighbor_mesh()

## [1] "503277994" "503370903" "503370904" "513207092" "513207094" "513300003"
## [7] "513300004" "513300001"

Detect fine and neighborhood mesh codes

mesh_1km_neighbors <- coords_to_mesh(133, 34, "1km") %>% 
  neighbor_mesh()
mesh_1km_neighbors %>% 
  export_meshes() %>% 
  st_geometry() %>% 
  plot()

1km neighborhood meshes

Administration mesh

set.seed(71)
# Select prefecture or city code
administration_mesh(code = 33, type = "prefecture") %>% 
  sample(5)

## Simple feature collection with 98 features and 4 fields
## geometry type:  POLYGON
## dimension:      XY
## bbox:           xmin: 133.25 ymin: 34.25 xmax: 134.5 ymax: 35.41667
## epsg (SRID):    4326
## proj4string:    +proj=longlat +datum=WGS84 +no_defs
## First 10 features:
##    lng_center lat_center meshcode  lat_error
## 1    133.8125   34.62500   513376 0.04166667
## 2    133.9375   34.62500   513377 0.04166667
## 3    133.6875   34.70833   523305 0.04166667
## 4    133.8125   34.70833   523306 0.04166667
## 5    133.9375   34.70833   523307 0.04166667
## 6    133.6875   34.79167   523315 0.04166667
## 7    133.8125   34.79167   523316 0.04166667
## 8    133.9375   34.79167   523317 0.04166667
## 9    133.8125   34.87500   523326 0.04166667
## 10   133.9375   34.87500   523327 0.04166667
##                          geometry
## 1  POLYGON ((133.75 34.58333, ...
## 2  POLYGON ((133.875 34.58333,...
## 3  POLYGON ((133.625 34.66667,...
## 4  POLYGON ((133.75 34.66667, ...
## 5  POLYGON ((133.875 34.66667,...
## 6  POLYGON ((133.625 34.75, 13...
## 7  POLYGON ((133.75 34.75, 133...
## 8  POLYGON ((133.875 34.75, 13...
## 9  POLYGON ((133.75 34.83333, ...
## 10 POLYGON ((133.875 34.83333,...

Mapping on Leaflet

leaflet() %>% 
  addTiles() %>% 
  addProviderTiles("OpenStreetMap.BlackAndWhite") %>% 
  addPolygons(data = administration_mesh(code = 33101, type = "city"))