Maps and Administrative Boundaries of Mongolia and Ulaanbaatar

Ready-to-use 'sf' maps of Mongolia at every openly available administrative level: country, economic regions, aimags (provinces), soums and Ulaanbaatar districts, and Ulaanbaatar khoroos (subdistricts), with codes and names for every bag. Provides a crosswalk between English and Cyrillic names, common spelling variants, ISO 3166-2 codes, humanitarian P-codes and National Statistics Office codes; helpers to join statistics to maps; thematic layers (settlements, rivers, lakes, roads, railways, airports, elevation, land cover, population and protected areas); and quick 'ggplot2' and 'leaflet' maps. Boundaries derive from the Common Operational Dataset published by the National Statistics Office of Mongolia and the United Nations Office for the Coordination of Humanitarian Affairs < https://data.humdata.org/dataset/cod-ab-mng>.

mongolmaps

Maps of Mongolia and Ulaanbaatar for R, at every openly available administrative level. One package, no downloads to start, and names that match however you spell them.

Монгол хэлээр: https://temuulene.github.io/mongolmaps/mn/

Every function returns an sf table with the same columns (codes, English and Mongolian names, parent units, area), so maps at different levels work the same way.

Installation

# install.packages("pak")
pak::pak("temuulene/mongolmaps")

Your first map

library(mongolmaps)

mn_map(label = TRUE)

mn_map() picks a projection suited to Mongolia, labels places inside their borders and credits the data source.

Your data on a map

mn_join() attaches a data frame to the boundaries. The place column can use any spelling, Cyrillic, or the codes used in National Statistics Office (NSO) tables. Totals and other levels in NSO tables are dropped for you.

pop <- mn_example_population[mn_example_population$Year == 2025, ]

pop_map <- mn_join(pop, by = "Region", level = "aimag")
#> ℹ Joining at the aimag level; dropped 6 rows for larger units ("country" and
#>   "region") and 2196 rows for smaller units ("soum" and "bag").

mn_map(pop_map, fill = value, trans = "log10", context = TRUE,
       title = "Population by aimag, 2025")

Ulaanbaatar down to khoroos

# The six central districts, by their usual abbreviations
central <- c("BGD", "BZD", "ChD", "KhUD", "SKhD", "SBD")
khoroo_pop <- mn_join(pop, by = "Region", level = "bag", within = central)
#> ℹ Joining at the bag level; dropped 371 rows for larger units ("country",
#>   "region", "aimag", and "soum").

mn_map(khoroo_pop, fill = value / area_km2, trans = "log10",
       title = "People per km2 by khoroo, central Ulaanbaatar, 2025")

Khoroos are labelled with their number; districts and other units with their name, in English or Mongolian:

mn_map(mn_ub_districts(), label = TRUE, lang = "mn")

Names in any spelling

mn_match(c("Khuvsgul", "Hovsgol", "Khövsgöl", "Хөвсгөл", "MN-041", "267"))
#> [1] "MN67" "MN67" "MN67" "MN67" "MN67" "MN67"

mn_match("Sukhbaatar district")
#> [1] "MN1119"
mn_match("Bayan-Uul", level = "soum", within = "Dornod")
#> [1] "MN2110"

mn_codes("soum", within = "Khovd")
#> # A tibble: 17 × 16
#>    pcode  name     name_en name_mn name_mns level type  number iso_code nso_code
#>    <chr>  <chr>    <chr>   <chr>   <chr>    <chr> <chr>  <int> <chr>    <chr>   
#>  1 MN8401 Jargala… Jargal… Жаргал… Jargala… soum  soum      NA <NA>     18401   
#>  2 MN8404 Altai    Altai   Алтай   Altai    soum  soum      NA <NA>     18404   
#>  3 MN8407 Bulgan   Bulgan  Булган  Bulgan   soum  soum      NA <NA>     18407   
#>  4 MN8410 Buyant   Buyant  Буянт   Buyant   soum  soum      NA <NA>     18410   
#>  5 MN8413 Darvi    Darvi   Дарви   Darvi    soum  soum      NA <NA>     18413   
#>  6 MN8416 Durgun   Durgun  Дөргөн  Dörgön   soum  soum      NA <NA>     18416   
#>  7 MN8419 Duut     Duut    Дуут    Duut     soum  soum      NA <NA>     18419   
#>  8 MN8422 Zereg    Zereg   Зэрэг   Zereg    soum  soum      NA <NA>     18422   
#>  9 MN8425 Mankhan  Mankhan Манхан  Mankhan  soum  soum      NA <NA>     18425   
#> 10 MN8428 Munkhkh… Munkhk… Мөнхха… Mönkhkh… soum  soum      NA <NA>     18428   
#> 11 MN8431 Must     Must    Мөст    Möst     soum  soum      NA <NA>     18431   
#> 12 MN8434 Myangad  Myangad Мянгад  Myangad  soum  soum      NA <NA>     18434   
#> 13 MN8437 Uyench   Uyench  Үенч    Üyench   soum  soum      NA <NA>     18437   
#> 14 MN8440 Khovd    Khovd   Ховд    Khovd    soum  soum      NA <NA>     18440   
#> 15 MN8443 Tsetseg  Tsetseg Цэцэг   Tsetseg  soum  soum      NA <NA>     18443   
#> 16 MN8446 Chandma… Chandm… Чандма… Chandma… soum  soum      NA <NA>     18446   
#> 17 MN8449 Erdeneb… Erdene… Эрдэнэ… Erdeneb… soum  soum      NA <NA>     18449   
#> # ℹ 6 more variables: parent_pcode <chr>, region_pcode <chr>,
#> #   aimag_pcode <chr>, soum_pcode <chr>, area_km2 <dbl>, has_geometry <lgl>

More

• Interactive maps: mn_leaflet(mn_khoroos(), fill = area_km2).
• Labels in Mongolian: lang = "mn" in any function, or options(mongolmaps.lang = "mn").
• Full-resolution boundaries: resolution = "high" (downloaded once and cached).
• Settlements, rivers, lakes and neighbouring countries: mn_settlements(), mn_rivers(), mn_lakes(), mn_neighbours().
• Roads, railways, airports and places from OpenStreetMap: mn_roads(within = "Ulaanbaatar"), mn_railways(), mn_airports(), mn_places() (downloaded once and cached).
• Elevation, hillshade, land cover and population grids (with terra): mn_map(mn_elevation()), mn_landcover(), mn_population(2025), and mn_zonal() to sum them by aimag, soum or khoroo.
• Protected areas: mn_protected_areas().
• Small multiples: mn_aimag_grid for geofacet::facet_geo().

Data sources

Khoroo boundaries come from an open project that does not state their origin, so treat them as unofficial. Bag boundaries are not openly published; see ?mn_bags for how to use them once you get them from NSO. Please credit the providers when you publish maps: mn_citation() returns the text, and mn_map() adds it as a caption.