Geographical data

Maps

Roland Krause

MADS6

Friday, 13 December 2024

Introduction

Maps

Learning objectives

  • Paths to simple maps with ggplot2
  • Limitations of default maps
  • Projected maps with standard geographic packages
    • spatial features with sf
  • Learn about the Coordinate Reference System (CRS)
  • Drawing choropleths

Material

  • maps and ggplot2 for simple maps
  • sf for spatial maps
  • rnaturalearth for sf compatible data sources
  • Claus O. Wilke’s Data visualisation guides
  • Geocomputating with R

Basic maps

Basic map data in R

Basics from maps

library(maps) # R Built-in library
iso3166|> gt()
a2 a3 ISOname mapname sovereignty
AW ABW Aruba Aruba Netherlands
AF AFG Afghanistan Afghanistan Afghanistan
AO AGO Angola Angola Angola
AI AIA Anguilla Anguilla Anguilla
AX ALA Aland Islands Finland:Aland Islands Finland
AL ALB Albania Albania Albania
AD AND Andorra Andorra Andorra
AE ARE United Arab Emirates United Arab Emirates United Arab Emirates
AR ARG Argentina Argentina Argentina
AM ARM Armenia Armenia Armenia
AS ASM American Samoa American Samoa USA
AQ ATA Antarctica Antarctica Antarctica
TF ATF French Southern and Antarctic Lands French Southern and Antarctic Lands France
AG ATG Antigua and Barbuda Barbuda Antigua and Barbuda
AG ATG Antigua and Barbuda Antigua Antigua and Barbuda
AU AUS Australia Australia Australia
AT AUT Austria Austria Austria
AZ AZE Azerbaijan Azerbaijan Azerbaijan
BI BDI Burundi Burundi Burundi
BE BEL Belgium Belgium Belgium
BJ BEN Benin Benin Benin
BQ BES Bonaire, Sint Eustatius and Saba Bonaire Netherlands
BQ BES Bonaire, Sint Eustatius and Saba Sint Eustatius Netherlands
BQ BES Bonaire, Sint Eustatius and Saba Saba Netherlands
BF BFA Burkina Faso Burkina Faso Burkina Faso
BD BGD Bangladesh Bangladesh Bangladesh
BG BGR Bulgaria Bulgaria Bulgaria
BH BHR Bahrain Bahrain Bahrain
BS BHS Bahamas Bahamas Bahamas
BA BIH Bosnia and Herzegovina Bosnia and Herzegovina Bosnia and Herzegovina
BL BLM Saint Barthelemy Saint Barthelemy France
BY BLR Belarus Belarus Belarus
BZ BLZ Belize Belize Belize
BM BMU Bermuda Bermuda UK
BO BOL Bolivia, Plurinational State of Bolivia Bolivia
BR BRA Brazil Brazil Brazil
BB BRB Barbados Barbados Barbados
BN BRN Brunei Darussalam Brunei Brunei
BT BTN Bhutan Bhutan Bhutan
BV BVT Bouvet Island Bouvet Island Norway
BW BWA Botswana Botswana Botswana
CF CAF Central African Republic Central African Republic Central African Republic
CA CAN Canada Canada Canada
CC CCK Cocos (Keeling) Islands Cocos Islands Australia
CH CHE Switzerland Switzerland Switzerland
CL CHL Chile Chile Chile
CN CHN China China China
CN CHN Paracel Islands Paracel Islands China
CI CIV Cote d'Ivoire Ivory Coast Ivory Coast
CM CMR Cameroon Cameroon Cameroon
CD COD Democratic Republic of the Congo Democratic Republic of the Congo Democratic Republic of the Congo
CG COG Republic of Congo Republic of Congo Republic of Congo
CK COK Cook Islands Cook Islands Cook Islands
CO COL Colombia Colombia Colombia
KM COM Comoros Comoros Comoros
CV CPV Cape Verde Cape Verde Cape Verde
CR CRI Costa Rica Costa Rica Costa Rica
CU CUB Cuba Cuba Cuba
CW CUW Curacao Curacao Netherlands
CX CXR Christmas Island Christmas Island Australia
KY CYM Cayman Islands Cayman Islands UK
CY CYP Cyprus Cyprus Cyprus
CZ CZE Czech Republic Czech Republic Czech Republic
DE DEU Germany Germany Germany
DJ DJI Djibouti Djibouti Djibouti
DM DMA Dominica Dominica Dominica
DK DNK Denmark Denmark Denmark
DO DOM Dominican Republic Dominican Republic Dominican Republic
DZ DZA Algeria Algeria Algeria
EC ECU Ecuador Ecuador Ecuador
EG EGY Egypt Egypt Egypt
ER ERI Eritrea Eritrea Eritrea
EH ESH Western Sahara Western Sahara Western Sahara
ES ESP Spain Spain Spain
ES ESP Spain Canary Islands Spain
EE EST Estonia Estonia Estonia
ET ETH Ethiopia Ethiopia Ethiopia
FI FIN Finland Finland(?!:Aland) Finland
FJ FJI Fiji Fiji Fiji
FK FLK Falkland Islands (Malvinas) Falkland Islands UK
FR FRA France France France
FR FRA Clipperton Island Clipperton Island France
FO FRO Faroe Islands Faroe Islands Denmark
FM FSM Federated States of Micronesia Micronesia Micronesia
GA GAB Gabon Gabon Gabon
GB GBR United Kingdom of Great Britain and Northern Ireland UK(?!r) UK
GE GEO Georgia Georgia Georgia
GG GGY Guernsey Guernsey Guernsey
GH GHA Ghana Ghana Ghana
GI GIB Gibraltar Gibraltar UK
GN GIN Guinea Guinea Guinea
GP GLP Guadeloupe Guadeloupe France
GM GMB Gambia Gambia Gambia
GW GNB Guinea-Bissau Guinea-Bissau Guinea-Bissau
GQ GNQ Equatorial Guinea Equatorial Guinea Equatorial Guinea
GR GRC Greece Greece Greece
GD GRD Grenada Grenada Grenada
GL GRL Greenland Greenland Denmark
GT GTM Guatemala Guatemala Guatemala
GF GUF French Guiana French Guiana France
GU GUM Guam Guam USA
GY GUY Guyana Guyana Guyana
HK HKG Hong Kong China:Hong Kong China
HM HMD Heard Island and McDonald Islands Heard Island Australia
HM HMD Heard Island and McDonald Islands McDonald Islands Australia
HN HND Honduras Honduras Honduras
HR HRV Croatia Croatia Croatia
HT HTI Haiti Haiti Haiti
HU HUN Hungary Hungary Hungary
ID IDN Indonesia Indonesia Indonesia
IM IMN Isle of Man Isle of Man Isle of Man
IN IND India India India
IO IOT British Indian Ocean Territory British Indian Ocean Territory UK
IO IOT British Indian Ocean Territory Chagos Archipelago UK
IE IRL Ireland Ireland Ireland
IR IRN Iran, Islamic Republic of Iran Iran
IQ IRQ Iraq Iraq Iraq
IS ISL Iceland Iceland Iceland
IL ISR Israel Israel Israel
IT ITA Italy Italy Italy
JM JAM Jamaica Jamaica Jamaica
JE JEY Jersey Jersey Jersey
JO JOR Jordan Jordan Jordan
JP JPN Japan Japan Japan
KZ KAZ Kazakhstan Kazakhstan Kazakhstan
KE KEN Kenya Kenya Kenya
KG KGZ Kyrgyzstan Kyrgyzstan Kyrgyzstan
KH KHM Cambodia Cambodia Cambodia
KI KIR Kiribati Kiribati Kiribati
KN KNA Saint Kitts and Nevis Saint Kitts Saint Kitts and Nevis
KN KNA Saint Kitts and Nevis Nevis Saint Kitts and Nevis
KR KOR Republic of Korea South Korea South Korea
KW KWT Kuwait Kuwait Kuwait
LA LAO Lao People's Democratic Republic Laos Laos
LB LBN Lebanon Lebanon Lebanon
LR LBR Liberia Liberia Liberia
LY LBY Libya Libya Libya
LC LCA Saint Lucia Saint Lucia Saint Lucia
LI LIE Liechtenstein Liechtenstein Liechtenstein
LK LKA Sri Lanka Sri Lanka Sri Lanka
LS LSO Lesotho Lesotho Lesotho
LT LTU Lithuania Lithuania Lithuania
LU LUX Luxembourg Luxembourg Luxembourg
LV LVA Latvia Latvia Latvia
MO MAC Macao China:Macao China
MF MAF Saint Martin (French part) Saint Martin France
MA MAR Morocco Morocco Morocco
MC MCO Monaco Monaco Monaco
MD MDA Moldova, Republic of Moldova Moldova
MG MDG Madagascar Madagascar Madagascar
MV MDV Maldives Maldives Maldives
MX MEX Mexico Mexico Mexico
MH MHL Marshall Islands Marshall Islands Marshall Islands
MK MKD Republic of North Macedonia North Macedonia North Macedonia
ML MLI Mali Mali Mali
MT MLT Malta Malta Malta
MM MMR Myanmar Myanmar Myanmar
ME MNE Montenegro Montenegro Montenegro
MN MNG Mongolia Mongolia Mongolia
MP MNP Northern Mariana Islands Northern Mariana Islands USA
MZ MOZ Mozambique Mozambique France
MR MRT Mauritania Mauritania Mauritania
MS MSR Montserrat Montserrat UK
MQ MTQ Martinique Martinique France
MU MUS Mauritius Mauritius Mauritius
MW MWI Malawi Malawi Malawi
MY MYS Malaysia Malaysia Malaysia
YT MYT Mayotte Mayotte France
NA NAM Namibia Namibia Namibia
NC NCL New Caledonia New Caledonia France
NE NER Niger Niger Niger
NF NFK Norfolk Island Norfolk Island Australia
NG NGA Nigeria Nigeria Nigeria
NI NIC Nicaragua Nicaragua Nicaragua
NU NIU Niue Niue Niue
NL NLD Netherlands Netherlands Netherlands
NO NOR Norway Norway(?!:Bouvet|:Svalbard|:Jan Mayen) Norway
NP NPL Nepal Nepal Nepal
NR NRU Nauru Nauru Nauru
NZ NZL New Zealand New Zealand New Zealand
OM OMN Oman Oman Oman
PK PAK Pakistan Pakistan Pakistan
PA PAN Panama Panama Panama
PN PCN Pitcairn Islands Pitcairn Islands UK
PE PER Peru Peru Peru
PH PHL Philippines Philippines Philippines
PW PLW Palau Palau USA
PG PNG Papua New Guinea Papua New Guinea Papua New Guinea
PL POL Poland Poland Poland
PR PRI Puerto Rico Puerto Rico Puerto Rico
KP PRK Democratic People's Republic of Korea North Korea North Korea
PT PRT Portugal Portugal Portugal
PT PRT Portugal Azores Portugal
PT PRT Portugal Madeira Islands Portugal
PY PRY Paraguay Paraguay Paraguay
PS PSE Palestine, State of Palestine Palestine
PF PYF French Polynesia French Polynesia France
QA QAT Qatar Qatar Qatar
RE REU Reunion Reunion France
RO ROU Romania Romania Romania
RU RUS Russian Federation Russia Russia
RW RWA Rwanda Rwanda Rwanda
SA SAU Saudi Arabia Saudi Arabia Saudi Arabia
SD SDN Sudan Sudan Sudan
SN SEN Senegal Senegal Senegal
SG SGP Singapore Singapore Singapore
GS SGS South Georgia and the South Sandwich Islands South Georgia UK
GS SGS South Georgia and the South Sandwich Islands South Sandwich Islands UK
SH SHN Saint Helena, Ascension and Tristan da Cunha Saint Helena UK
SH SHN Saint Helena, Ascension and Tristan da Cunha Ascension Island UK
SH SHN Saint Helena, Ascension and Tristan da Cunha Tristan da Cunha UK
SJ SJM Svalbard and Jan Mayen Norway:Svalbard Norway
SJ SJM Svalbard and Jan Mayen Norway:Jan Mayen Norway
SB SLB Solomon Islands Solomon Islands Solomon Islands
SL SLE Sierra Leone Sierra Leone Sierra Leone
SV SLV El Salvador El Salvador El Salvador
SM SMR San Marino San Marino San Marino
SO SOM Somalia Somalia Somalia
PM SPM Saint Pierre and Miquelon Saint Pierre and Miquelon France
RS SRB Serbia Serbia Serbia
SS SSD South Sudan South Sudan South Sudan
ST STP Sao Tome and Principe Sao Tome and Principe Sao Tome and Principe
SR SUR Suriname Suriname Suriname
SK SVK Slovakia Slovakia Slovakia
SI SVN Slovenia Slovenia Slovenia
SE SWE Sweden Sweden Sweden
SZ SWZ Swaziland Swaziland Swaziland
SX SXM Sint Maarten (Dutch part) Sint Maarten Netherlands
SC SYC Seychelles Seychelles Seychelles
SY SYR Syrian Arab Republic Syria Syria
TC TCA Turks and Caicos Islands Turks and Caicos Islands UK
TD TCD Chad Chad Chad
TG TGO Togo Togo Togo
TH THA Thailand Thailand Thailand
TJ TJK Tajikistan Tajikistan Tajikistan
TK TKL Tokelau Tokelau New Zealand
TM TKM Turkmenistan Turkmenistan Turkmenistan
TL TLS Timor-Leste Timor-Leste Timor-Leste
TO TON Tonga Tonga Tonga
TT TTO Trinidad and Tobago Trinidad Trinidad and Tobago
TT TTO Trinidad and Tobago Tobago Trinidad and Tobago
TN TUN Tunisia Tunisia Tunisia
TR TUR Turkey Turkey Turkey
TV TUV Tuvalu Tuvalu Tuvalu
TW TWN Taiwan Taiwan Taiwan
TZ TZA Tanzania, United Republic of Tanzania Tanzania
UG UGA Uganda Uganda Uganda
UA UKR Ukraine Ukraine Ukraine
UM UMI United States Minor Outlying Islands US Minor Outlying Islands USA
UY URY Uruguay Uruguay Uruguay
US USA United States USA USA
UZ UZB Uzbekistan Uzbekistan Uzbekistan
VA VAT Holy See (Vatican City State) Vatican Vatican
VC VCT Saint Vincent and the Grenadines Saint Vincent Saint Vincent and the Grenadines
VC VCT Saint Vincent and the Grenadines Grenadines Saint Vincent and the Grenadines
VE VEN Venezuela, Bolivarian Republic of Venezuela Venezuela
VG VGB Virgin Islands, British Virgin Islands, British UK
VI VIR Virgin Islands, U.S. Virgin Islands, US USA
VN VNM Vietnam Vietnam Vietnam
VU VUT Vanuatu Vanuatu Vanuatu
WF WLF Wallis and Futuna Wallis and Futuna France
WS WSM Samoa Samoa Samoa
XK XKX Kosovo Kosovo Kosovo
YE YEM Yemen Yemen Yemen
ZA ZAF South Africa South Africa South Africa
ZM ZMB Zambia Zambia Zambia
ZW ZWE Zimbabwe Zimbabwe Zimbabwe
?? ?? Akrotiri Cyprus:Akrotiri UK
?? ?? Dhekeli Cyprus:Dhekeli UK 
ggplot(world) + # from maps
  geom_sf()

Basic maps with ggplot

ggplot knows the world

library(ggplot2)

gworld <- ggplot2::map_data("world")
luxembourg <- map_data("world", region = "Luxembourg")

gworld |> 
  filter(region == "Luxembourg") |> 
  slice_sample(n = 10)
       long      lat group order     region subregion
1  5.744043 49.91963   958 59742 Luxembourg      <NA>
2  6.484766 49.70781   958 59715 Luxembourg      <NA>
3  5.928906 49.47754   958 59728 Luxembourg      <NA>
4  6.277344 49.47754   958 59721 Luxembourg      <NA>
5  5.823438 49.50508   958 59730 Luxembourg      <NA>
6  5.837597 49.57832   958 59733 Luxembourg      <NA>
7  6.256054 49.87217   958 59710 Luxembourg      <NA>
8  6.406738 49.64497   958 59717 Luxembourg      <NA>
9  6.089062 50.15459   958 59748 Luxembourg      <NA>
10 6.344336 49.45274   958 59720 Luxembourg      <NA>

… which we can easily visualise

ggplot(gworld) +
  geom_line(aes(x = long, y = lat))

Basic maps with ggplot

ggplot knows the world

library(ggplot2)

gworld <- map_data("world")

gworld |> 
  slice_sample(n = 10)
         long        lat group  order    region subregion
1  155.160446  59.190140  1309  82079    Russia      <NA>
2  167.436127 -16.515236  1603  99530   Vanuatu  Malakula
3   33.000000 -12.899610  1623 100410    Zambia      <NA>
4   -9.464892  52.823193   845  52338   Ireland      <NA>
5   43.603321  66.291214  1309  79775    Russia      <NA>
6  -71.832420 -43.527149    20   1866 Argentina      <NA>
7  126.778908   3.843164   817  49878 Indonesia       126
8   38.822266  47.837013  1441  91499   Ukraine      <NA>
9   28.244337  46.451271  1241  75718   Romania      <NA>
10 -73.366211   9.194140   438  32997  Colombia      <NA>

… which we can easily visualise if groups are respected

ggplot(gworld) +
  geom_polygon(aes(x = long, y = lat, group = group))

geom_polygon() give us countries

ggplot(gworld) +
  geom_polygon(aes(x=long, 
                   y = lat, 
                   group = group),
               color = "white")

geom_map()

ggplot(gworld) +
  geom_map(map = gworld, 
           data = gworld,
           aes(map_id = region,
               fill = region)) +
  expand_limits(x = gworld$long, y = gworld$lat) +
  guides(fill = "none") +
  scale_fill_discrete_qualitative(palette = "Dark 2")

Caution

map() != mapping()

Great map, but input data is limited. And geom_map() is barely explained.

Zooming in on Luxembourg

msa_2230 = data.frame(long = c(5.949440), 
                      lat = c(49.504432))
ggplot() +
  geom_map(data = gworld,
    map = gworld,
           aes(map_id = region,
               fill = region),
           color = "black") +
  geom_point(data = msa_2230, 
    aes(long, lat)) +
  expand_limits(x = gworld$long, y = gworld$lat) +
  coord_cartesian(xlim = c(5.5, 6.75), 
                  ylim = c(48.5, 51)) + 
  scale_fill_discrete_qualitative(palette = "Dark 2") +
  guides(fill = "none")

Projections

Parallels (latitude) and meridians (longitude)

Claus O. Wilke on projections.

Figure from Claus O. Wilke. Fundamentals of Data Visualization. O’Reilly, 2019.

There are many ways to project onto a 2D plane

Figure from Claus O. Wilke. Fundamentals of Data Visualization. O’Reilly, 2019.

There are many ways to project onto a 2D plane

Mercator projection

Shapes are preserved, areas are severely distorted.

Figure from Claus O. Wilke. Fundamentals of Data Visualization. O’Reilly, 2019.

There are many ways to project onto a 2D plane

Goode homolosine

Areas are preserved, shapes are somewhat distorted

Figure from Claus O. Wilke. Fundamentals of Data Visualization. O’Reilly, 2019.

Projecting the US

Note

Alaska, Hawaii, and the lower 48 are far apart; difficult to show on one map

Figure from Claus O. Wilke. Fundamentals of Data Visualization. O’Reilly, 2019.

Projecting the US

A fair, area-preserving projection

Figure from Claus O. Wilke. Fundamentals of Data Visualization. O’Reilly, 2019.

Simple features - sf

The sf package: Simple Features in R

Artwork by Allison Horst

Simple features in R

#euro_map <- world[world$continent == "Europe", ] 
euro_map <- rnaturalearth::ne_countries(scale = 110, 
                                        returnclass = 'sf', 
                                        continent = "Europe")

euro_map
Simple feature collection with 39 features and 168 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -180 ymin: 2.053389 xmax: 180 ymax: 81.2504
Geodetic CRS:  WGS 84
First 10 features:
         featurecla scalerank labelrank sovereignt sov_a3 adm0_dif level
19  Admin-0 country         1         2     Russia    RUS        0     2
22  Admin-0 country         1         3     Norway    NOR        0     2
44  Admin-0 country         1         2     France    FR1        1     2
111 Admin-0 country         1         3     Sweden    SWE        0     2
112 Admin-0 country         1         4    Belarus    BLR        0     2
113 Admin-0 country         1         3    Ukraine    UKR        0     2
114 Admin-0 country         1         3     Poland    POL        0     2
115 Admin-0 country         1         4    Austria    AUT        0     2
116 Admin-0 country         1         5    Hungary    HUN        0     2
117 Admin-0 country         1         6    Moldova    MDA        0     2
                 type  tlc   admin adm0_a3 geou_dif geounit gu_a3 su_dif
19  Sovereign country    1  Russia     RUS        0  Russia   RUS      0
22  Sovereign country <NA>  Norway     NOR        0  Norway   NOR      0
44            Country    1  France     FRA        0  France   FRA      0
111 Sovereign country    1  Sweden     SWE        0  Sweden   SWE      0
112 Sovereign country    1 Belarus     BLR        0 Belarus   BLR      0
113 Sovereign country    1 Ukraine     UKR        0 Ukraine   UKR      0
114 Sovereign country    1  Poland     POL        0  Poland   POL      0
115 Sovereign country    1 Austria     AUT        0 Austria   AUT      0
116 Sovereign country    1 Hungary     HUN        0 Hungary   HUN      0
117 Sovereign country    1 Moldova     MDA        0 Moldova   MDA      0
    subunit su_a3 brk_diff    name          name_long brk_a3 brk_name brk_group
19   Russia   RUS        0  Russia Russian Federation    RUS   Russia      <NA>
22   Norway   NOR        0  Norway             Norway    NOR   Norway      <NA>
44   France   FRA        0  France             France    FRA   France      <NA>
111  Sweden   SWE        0  Sweden             Sweden    SWE   Sweden      <NA>
112 Belarus   BLR        0 Belarus            Belarus    BLR  Belarus      <NA>
113 Ukraine   UKR        0 Ukraine            Ukraine    UKR  Ukraine      <NA>
114  Poland   POL        0  Poland             Poland    POL   Poland      <NA>
115 Austria   AUT        0 Austria            Austria    AUT  Austria      <NA>
116 Hungary   HUN        0 Hungary            Hungary    HUN  Hungary      <NA>
117 Moldova   MDA        0 Moldova            Moldova    MDA  Moldova      <NA>
    abbrev postal           formal_en formal_fr name_ciawf note_adm0 note_brk
19    Rus.    RUS  Russian Federation      <NA>     Russia      <NA>     <NA>
22    Nor.      N   Kingdom of Norway      <NA>     Norway      <NA>     <NA>
44     Fr.      F     French Republic      <NA>     France      <NA>     <NA>
111   Swe.      S   Kingdom of Sweden      <NA>     Sweden      <NA>     <NA>
112  Bela.     BY Republic of Belarus      <NA>    Belarus      <NA>     <NA>
113   Ukr.     UA             Ukraine      <NA>    Ukraine      <NA>     <NA>
114   Pol.     PL  Republic of Poland      <NA>     Poland      <NA>     <NA>
115  Aust.      A Republic of Austria      <NA>    Austria      <NA>     <NA>
116   Hun.     HU Republic of Hungary      <NA>    Hungary      <NA>     <NA>
117   Mda.     MD Republic of Moldova      <NA>    Moldova      <NA>     <NA>
             name_sort name_alt mapcolor7 mapcolor8 mapcolor9 mapcolor13
19  Russian Federation     <NA>         2         5         7          7
22              Norway     <NA>         5         3         8         12
44              France     <NA>         7         5         9         11
111             Sweden     <NA>         1         4         2          4
112            Belarus     <NA>         1         1         5         11
113            Ukraine     <NA>         5         1         6          3
114             Poland     <NA>         3         7         1          2
115            Austria     <NA>         3         1         3          4
116            Hungary     <NA>         4         6         1          5
117            Moldova     <NA>         3         5         4         12
      pop_est pop_rank pop_year  gdp_md gdp_year                    economy
19  144373535       17     2019 1699876     2019   3. Emerging region: BRIC
22    5347896       13     2019  403336     2019 2. Developed region: nonG7
44   67059887       16     2019 2715518     2019    1. Developed region: G7
111  10285453       14     2019  530883     2019 2. Developed region: nonG7
112   9466856       13     2019   63080     2019       6. Developing region
113  44385155       15     2019  153781     2019       6. Developing region
114  37970874       15     2019  595858     2019 2. Developed region: nonG7
115   8877067       13     2019  445075     2019 2. Developed region: nonG7
116   9769949       13     2019  163469     2019 2. Developed region: nonG7
117   2657637       12     2019   11968     2019       6. Developing region
                income_grp fips_10 iso_a2 iso_a2_eh iso_a3 iso_a3_eh iso_n3
19  3. Upper middle income      RS     RU        RU    RUS       RUS    643
22    1. High income: OECD     -99    -99        NO    -99       NOR    -99
44    1. High income: OECD      FR    -99        FR    -99       FRA    -99
111   1. High income: OECD      SW     SE        SE    SWE       SWE    752
112 3. Upper middle income      BO     BY        BY    BLR       BLR    112
113 4. Lower middle income      UP     UA        UA    UKR       UKR    804
114   1. High income: OECD      PL     PL        PL    POL       POL    616
115   1. High income: OECD      AU     AT        AT    AUT       AUT    040
116   1. High income: OECD      HU     HU        HU    HUN       HUN    348
117 4. Lower middle income      MD     MD        MD    MDA       MDA    498
    iso_n3_eh un_a3 wb_a2 wb_a3   woe_id woe_id_eh
19        643   643    RU   RUS 23424936  23424936
22        578   -99   -99   -99      -90  23424910
44        250   250    FR   FRA      -90  23424819
111       752   752    SE   SWE 23424954  23424954
112       112   112    BY   BLR 23424765  23424765
113       804   804    UA   UKR 23424976  23424976
114       616   616    PL   POL 23424923  23424923
115       040   040    AT   AUT 23424750  23424750
116       348   348    HU   HUN 23424844  23424844
117       498   498    MD   MDA 23424885  23424885
                                                               woe_note
19                                           Exact WOE match as country
22  Does not include Svalbard, Jan Mayen, or Bouvet Islands (28289410).
44                Includes only Metropolitan France (including Corsica)
111                                          Exact WOE match as country
112                                          Exact WOE match as country
113                                          Exact WOE match as country
114                                          Exact WOE match as country
115                                          Exact WOE match as country
116                                          Exact WOE match as country
117                                          Exact WOE match as country
    adm0_iso adm0_diff adm0_tlc adm0_a3_us adm0_a3_fr adm0_a3_ru adm0_a3_es
19       RUS      <NA>      RUS        RUS        RUS        RUS        RUS
22       NOR      <NA>      NOR        NOR        NOR        NOR        NOR
44       FRA      <NA>      FRA        FRA        FRA        FRA        FRA
111      SWE      <NA>      SWE        SWE        SWE        SWE        SWE
112      BLR      <NA>      BLR        BLR        BLR        BLR        BLR
113      UKR      <NA>      UKR        UKR        UKR        UKR        UKR
114      POL      <NA>      POL        POL        POL        POL        POL
115      AUT      <NA>      AUT        AUT        AUT        AUT        AUT
116      HUN      <NA>      HUN        HUN        HUN        HUN        HUN
117      MDA      <NA>      MDA        MDA        MDA        MDA        MDA
    adm0_a3_cn adm0_a3_tw adm0_a3_in adm0_a3_np adm0_a3_pk adm0_a3_de
19         RUS        RUS        RUS        RUS        RUS        RUS
22         NOR        NOR        NOR        NOR        NOR        NOR
44         FRA        FRA        FRA        FRA        FRA        FRA
111        SWE        SWE        SWE        SWE        SWE        SWE
112        BLR        BLR        BLR        BLR        BLR        BLR
113        UKR        UKR        UKR        UKR        UKR        UKR
114        POL        POL        POL        POL        POL        POL
115        AUT        AUT        AUT        AUT        AUT        AUT
116        HUN        HUN        HUN        HUN        HUN        HUN
117        MDA        MDA        MDA        MDA        MDA        MDA
    adm0_a3_gb adm0_a3_br adm0_a3_il adm0_a3_ps adm0_a3_sa adm0_a3_eg
19         RUS        RUS        RUS        RUS        RUS        RUS
22         NOR        NOR        NOR        NOR        NOR        NOR
44         FRA        FRA        FRA        FRA        FRA        FRA
111        SWE        SWE        SWE        SWE        SWE        SWE
112        BLR        BLR        BLR        BLR        BLR        BLR
113        UKR        UKR        UKR        UKR        UKR        UKR
114        POL        POL        POL        POL        POL        POL
115        AUT        AUT        AUT        AUT        AUT        AUT
116        HUN        HUN        HUN        HUN        HUN        HUN
117        MDA        MDA        MDA        MDA        MDA        MDA
    adm0_a3_ma adm0_a3_pt adm0_a3_ar adm0_a3_jp adm0_a3_ko adm0_a3_vn
19         RUS        RUS        RUS        RUS        RUS        RUS
22         NOR        NOR        NOR        NOR        NOR        NOR
44         FRA        FRA        FRA        FRA        FRA        FRA
111        SWE        SWE        SWE        SWE        SWE        SWE
112        BLR        BLR        BLR        BLR        BLR        BLR
113        UKR        UKR        UKR        UKR        UKR        UKR
114        POL        POL        POL        POL        POL        POL
115        AUT        AUT        AUT        AUT        AUT        AUT
116        HUN        HUN        HUN        HUN        HUN        HUN
117        MDA        MDA        MDA        MDA        MDA        MDA
    adm0_a3_tr adm0_a3_id adm0_a3_pl adm0_a3_gr adm0_a3_it adm0_a3_nl
19         RUS        RUS        RUS        RUS        RUS        RUS
22         NOR        NOR        NOR        NOR        NOR        NOR
44         FRA        FRA        FRA        FRA        FRA        FRA
111        SWE        SWE        SWE        SWE        SWE        SWE
112        BLR        BLR        BLR        BLR        BLR        BLR
113        UKR        UKR        UKR        UKR        UKR        UKR
114        POL        POL        POL        POL        POL        POL
115        AUT        AUT        AUT        AUT        AUT        AUT
116        HUN        HUN        HUN        HUN        HUN        HUN
117        MDA        MDA        MDA        MDA        MDA        MDA
    adm0_a3_se adm0_a3_bd adm0_a3_ua adm0_a3_un adm0_a3_wb continent region_un
19         RUS        RUS        RUS        -99        -99    Europe    Europe
22         NOR        NOR        NOR        -99        -99    Europe    Europe
44         FRA        FRA        FRA        -99        -99    Europe    Europe
111        SWE        SWE        SWE        -99        -99    Europe    Europe
112        BLR        BLR        BLR        -99        -99    Europe    Europe
113        UKR        UKR        UKR        -99        -99    Europe    Europe
114        POL        POL        POL        -99        -99    Europe    Europe
115        AUT        AUT        AUT        -99        -99    Europe    Europe
116        HUN        HUN        HUN        -99        -99    Europe    Europe
117        MDA        MDA        MDA        -99        -99    Europe    Europe
          subregion             region_wb name_len long_len abbrev_len tiny
19   Eastern Europe Europe & Central Asia        6       18          4  -99
22  Northern Europe Europe & Central Asia        6        6          4  -99
44   Western Europe Europe & Central Asia        6        6          3  -99
111 Northern Europe Europe & Central Asia        6        6          4  -99
112  Eastern Europe Europe & Central Asia        7        7          5  -99
113  Eastern Europe Europe & Central Asia        7        7          4  -99
114  Eastern Europe Europe & Central Asia        6        6          4  -99
115  Western Europe Europe & Central Asia        7        7          5  -99
116  Eastern Europe Europe & Central Asia        7        7          4  -99
117  Eastern Europe Europe & Central Asia        7        7          4  -99
    homepart min_zoom min_label max_label   label_x  label_y      ne_id
19         1        0       1.7       5.2 44.686469 58.24936 1159321201
22         1        0       3.0       7.0  9.679975 61.35709 1159321109
44         1        0       1.7       6.7  2.552275 46.69611 1159320637
111        1        0       2.0       7.0 19.017050 65.85918 1159321287
112        1        0       3.0       8.0 28.417701 53.82189 1159320427
113        1        0       2.7       7.0 32.140865 49.72474 1159321345
114        1        0       2.5       7.0 19.490468 51.99032 1159321179
115        1        0       3.0       8.0 14.130515 47.51886 1159320379
116        1        0       4.0       9.0 19.447867 47.08684 1159320841
117        1        0       5.0      10.0 28.487904 47.43500 1159321045
    wikidataid   name_ar name_bn         name_de name_en     name_es  name_fa
19        Q159     روسيا  রাশিয়া        Russland  Russia       Rusia    روسیه
22         Q20   النرويج   নরওয়ে        Norwegen  Norway     Noruega     نروژ
44        Q142     فرنسا   ফ্রান্স      Frankreich  France     Francia   فرانسه
111        Q34    السويد   সুইডেন        Schweden  Sweden      Suecia     سوئد
112       Q184 بيلاروسيا  বেলারুশ         Belarus Belarus Bielorrusia   بلاروس
113       Q212  أوكرانيا  ইউক্রেন         Ukraine Ukraine     Ucrania  اوکراین
114        Q36    بولندا পোল্যান্ড           Polen  Poland     Polonia   لهستان
115        Q40    النمسا অস্ট্রিয়া      Österreich Austria     Austria    اتریش
116        Q28     المجر হাঙ্গেরি          Ungarn Hungary     Hungría مجارستان
117       Q217   مولدوفا  মলদোভা Republik Moldau Moldova    Moldavia  مولداوی
        name_fr    name_el  name_he name_hi          name_hu  name_id
19       Russie      Ρωσία    רוסיה      रूस      Oroszország    Rusia
22      Norvège   Νορβηγία נורווגיה    नॉर्वे         Norvégia Norwegia
44       France     Γαλλία     צרפת   फ़्रान्स    Franciaország  Prancis
111       Suède    Σουηδία   שוודיה   स्वीडन       Svédország   Swedia
112 Biélorussie Λευκορωσία   בלארוס   बेलारूस Fehéroroszország  Belarus
113     Ukraine   Ουκρανία אוקראינה    युक्रेन          Ukrajna  Ukraina
114     Pologne    Πολωνία    פולין    पोलैंड    Lengyelország Polandia
115    Autriche    Αυστρία  אוסטריה ऑस्ट्रिया         Ausztria  Austria
116     Hongrie   Ουγγαρία  הונגריה    हंगरी     Magyarország Hongaria
117    Moldavie   Μολδαβία  מולדובה मॉल्डोवा          Moldova  Moldova
        name_it      name_ja    name_ko     name_nl  name_pl      name_pt
19       Russia       ロシア     러시아     Rusland    Rosja       Rússia
22     Norvegia   ノルウェー   노르웨이   Noorwegen Norwegia      Noruega
44      Francia     フランス     프랑스   Frankrijk  Francja       França
111      Svezia スウェーデン     스웨덴      Zweden  Szwecja       Suécia
112 Bielorussia   ベラルーシ   벨라루스 Wit-Rusland Białoruś Bielorrússia
113     Ucraina   ウクライナ 우크라이나    Oekraïne  Ukraina      Ucrânia
114     Polonia   ポーランド     폴란드       Polen   Polska      Polónia
115     Austria オーストリア 오스트리아  Oostenrijk  Austria      Áustria
116    Ungheria   ハンガリー     헝가리   Hongarije    Węgry      Hungria
117    Moldavia     モルドバ     몰도바    Moldavië Mołdawia     Moldávia
       name_ru   name_sv     name_tr  name_uk name_ur   name_vi  name_zh
19      Россия  Ryssland       Rusya    Росія     روس       Nga   俄罗斯
22    Норвегия     Norge      Norveç Норвегія   ناروے     Na Uy     挪威
44     Франция Frankrike      Fransa  Франція   فرانس      Pháp     法国
111     Швеция   Sverige       İsveç   Швеція   سویڈن Thụy Điển     瑞典
112 Белоруссия   Belarus Beyaz Rusya Білорусь بیلاروس   Belarus 白俄罗斯
113    Украина   Ukraina     Ukrayna  Україна  یوکرین   Ukraina   乌克兰
114     Польша     Polen     Polonya   Польща  پولینڈ    Ba Lan     波兰
115    Австрия Österrike   Avusturya  Австрія  آسٹریا        Áo   奥地利
116    Венгрия    Ungern  Macaristan Угорщина   ہنگری   Hungary   匈牙利
117   Молдавия Moldavien     Moldova  Молдова مالدووا   Moldova 摩尔多瓦
    name_zht      fclass_iso tlc_diff      fclass_tlc fclass_us fclass_fr
19    俄羅斯 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
22      挪威    Unrecognized     <NA>    Unrecognized      <NA>      <NA>
44      法國 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
111     瑞典 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
112 白俄羅斯 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
113   烏克蘭 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
114     波蘭 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
115   奧地利 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
116   匈牙利 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
117 摩爾多瓦 Admin-0 country     <NA> Admin-0 country      <NA>      <NA>
    fclass_ru fclass_es fclass_cn fclass_tw fclass_in fclass_np fclass_pk
19       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
22       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
44       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
111      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
112      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
113      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
114      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
115      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
116      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
117      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
    fclass_de fclass_gb fclass_br fclass_il fclass_ps fclass_sa fclass_eg
19       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
22       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
44       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
111      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
112      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
113      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
114      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
115      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
116      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
117      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
    fclass_ma fclass_pt fclass_ar fclass_jp fclass_ko fclass_vn fclass_tr
19       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
22       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
44       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
111      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
112      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
113      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
114      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
115      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
116      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
117      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
    fclass_id fclass_pl fclass_gr fclass_it fclass_nl fclass_se fclass_bd
19       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
22       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
44       <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
111      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
112      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
113      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
114      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
115      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
116      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
117      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
    fclass_ua                       geometry
19       <NA> MULTIPOLYGON (((178.7253 71...
22       <NA> MULTIPOLYGON (((15.14282 79...
44       <NA> MULTIPOLYGON (((-51.6578 4....
111      <NA> MULTIPOLYGON (((11.02737 58...
112      <NA> MULTIPOLYGON (((28.17671 56...
113      <NA> MULTIPOLYGON (((31.78599 52...
114      <NA> MULTIPOLYGON (((23.48413 53...
115      <NA> MULTIPOLYGON (((16.97967 48...
116      <NA> MULTIPOLYGON (((22.08561 48...
117      <NA> MULTIPOLYGON (((26.61934 48...

Plotting Europe

Code 
ggplot(euro_map) +  geom_sf()

Plotting Europe geographically

Code 
limits_x <- c(-25, 40)
limits_y <- c(32, 72.5)

euro_map |> 
  ggplot() +
  geom_sf() +
  coord_sf(xlim = limits_x,
           ylim = limits_y)

GPD per person in Europe

Code 
euro_map |>
  ggplot() +
   geom_sf(aes(fill = gdp_md/pop_est)) + 
    coord_sf(xlim = limits_x,
           ylim = limits_y) +
  guides(fill = guide_legend(title = "GDP/Population")) +
  theme(legend.position = "bottom") +
  scale_fill_binned_sequential()

The variable gdp_md is not a median GDP!

GPD per person in Europe - white borders

euro_map |>
  ggplot() +
  geom_sf(aes(fill = gdp_md/pop_est),
          colour = "white") + 
  coord_sf(xlim = limits_x,
           ylim = limits_y) +
  guides(fill = guide_legend(title = "GDP/Population"))+
  theme(legend.position = "bottom") +
  scale_fill_binned_sequential()

Select Luxembourg

euro_map |> 
   filter(name == "Luxembourg") |> 
   relocate(geometry)
Simple feature collection with 1 feature and 168 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: 5.674052 ymin: 49.44267 xmax: 6.242751 ymax: 50.12805
Geodetic CRS:  WGS 84
                        geometry      featurecla scalerank labelrank sovereignt
1 MULTIPOLYGON (((6.043073 50... Admin-0 country         1         6 Luxembourg
  sov_a3 adm0_dif level              type tlc      admin adm0_a3 geou_dif
1    LUX        0     2 Sovereign country   1 Luxembourg     LUX        0
     geounit gu_a3 su_dif    subunit su_a3 brk_diff       name  name_long
1 Luxembourg   LUX      0 Luxembourg   LUX        0 Luxembourg Luxembourg
  brk_a3   brk_name brk_group abbrev postal                 formal_en formal_fr
1    LUX Luxembourg      <NA>   Lux.      L Grand Duchy of Luxembourg      <NA>
  name_ciawf note_adm0 note_brk  name_sort name_alt mapcolor7 mapcolor8
1 Luxembourg      <NA>     <NA> Luxembourg     <NA>         1         7
  mapcolor9 mapcolor13 pop_est pop_rank pop_year gdp_md gdp_year
1         3          7  619896       11     2019  71104     2019
                     economy           income_grp fips_10 iso_a2 iso_a2_eh
1 2. Developed region: nonG7 1. High income: OECD      LU     LU        LU
  iso_a3 iso_a3_eh iso_n3 iso_n3_eh un_a3 wb_a2 wb_a3   woe_id woe_id_eh
1    LUX       LUX    442       442   442    LU   LUX 23424881  23424881
                    woe_note adm0_iso adm0_diff adm0_tlc adm0_a3_us adm0_a3_fr
1 Exact WOE match as country      LUX      <NA>      LUX        LUX        LUX
  adm0_a3_ru adm0_a3_es adm0_a3_cn adm0_a3_tw adm0_a3_in adm0_a3_np adm0_a3_pk
1        LUX        LUX        LUX        LUX        LUX        LUX        LUX
  adm0_a3_de adm0_a3_gb adm0_a3_br adm0_a3_il adm0_a3_ps adm0_a3_sa adm0_a3_eg
1        LUX        LUX        LUX        LUX        LUX        LUX        LUX
  adm0_a3_ma adm0_a3_pt adm0_a3_ar adm0_a3_jp adm0_a3_ko adm0_a3_vn adm0_a3_tr
1        LUX        LUX        LUX        LUX        LUX        LUX        LUX
  adm0_a3_id adm0_a3_pl adm0_a3_gr adm0_a3_it adm0_a3_nl adm0_a3_se adm0_a3_bd
1        LUX        LUX        LUX        LUX        LUX        LUX        LUX
  adm0_a3_ua adm0_a3_un adm0_a3_wb continent region_un      subregion
1        LUX        -99        -99    Europe    Europe Western Europe
              region_wb name_len long_len abbrev_len tiny homepart min_zoom
1 Europe & Central Asia       10       10          4    5        1        0
  min_label max_label label_x  label_y      ne_id wikidataid   name_ar  name_bn
1       5.7        10 6.07762 49.73373 1159321031        Q32 لوكسمبورغ লুক্সেমবুর্গ
    name_de    name_en    name_es    name_fa    name_fr      name_el   name_he
1 Luxemburg Luxembourg Luxemburgo لوکزامبورگ Luxembourg Λουξεμβούργο לוקסמבורג
  name_hi   name_hu    name_id     name_it        name_ja    name_ko   name_nl
1 लक्ज़मबर्ग Luxemburg Luksemburg Lussemburgo ルクセンブルク 룩셈부르크 Luxemburg
     name_pl    name_pt    name_ru   name_sv    name_tr    name_uk name_ur
1 Luksemburg Luxemburgo Люксембург Luxemburg Lüksemburg Люксембург لکسمبرگ
     name_vi name_zh name_zht      fclass_iso tlc_diff      fclass_tlc
1 Luxembourg  卢森堡   盧森堡 Admin-0 country     <NA> Admin-0 country
  fclass_us fclass_fr fclass_ru fclass_es fclass_cn fclass_tw fclass_in
1      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
  fclass_np fclass_pk fclass_de fclass_gb fclass_br fclass_il fclass_ps
1      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
  fclass_sa fclass_eg fclass_ma fclass_pt fclass_ar fclass_jp fclass_ko
1      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
  fclass_vn fclass_tr fclass_id fclass_pl fclass_gr fclass_it fclass_nl
1      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>      <NA>
  fclass_se fclass_bd fclass_ua
1      <NA>      <NA>      <NA>
#lux <-  world[world$name_long == "Luxembourg", ]

Plotting Luxembourg

ggplot(
euro_map |> 
   filter(name == "Luxembourg") |> 
   relocate(geometry)) + geom_sf()

More resolution is needed

euro_map50 <- rnaturalearth::ne_countries(
  scale = 50, 
  type = 'map_units', 
  returnclass = 'sf')

euro_map50 |> filter(name == "Luxembourg") |> 
  ggplot() +
  geom_sf()

High-resolution maps from Shapefiles

f = system.file("shapes/world.gpkg", package = "spData")
world = read_sf(f)
lux_shp <- sf::st_read("data/LIMADM_COMMUNES.shp")
Reading layer `LIMADM_COMMUNES' from data source 
  `/builds/t2_oYmfyB/0/uniluxembourg/lcsb/r-training/mads6/slides/data/LIMADM_COMMUNES.shp' 
  using driver `ESRI Shapefile'
Simple feature collection with 102 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: 48930.25 ymin: 57015.29 xmax: 106113.8 ymax: 138759.2
Projected CRS: Luxembourg 1930 / Gauss
ggplot(lux_shp) + 
  geom_sf(aes(fill = CANTON)) +
  theme_bw() -> lux_commune_map
lux_commune_map +
#  paletteer::scale_fill_paletteer_d("rtist::vangogh")
  scale_fill_discrete_qualitative(palette = "Dark 3")

Data source for Luxembourg

Four color theorem

Code 
commune <- c(
  Redange = "#00A4E1",
  Grevenmacher = "#00A4E1",
  Luxembourg = "#777",
  Vianden = "#00A4E1",
  Mersch = "#DC021B",
  "Esch-sur-Alzette" = "#00A4E1",
  Wiltz = "#DC021B",
  Clervaux = "#FFF",
  Diekirch = "#777",
  Remich =  "#FFF",
  Capellen = "#FFF",
  Echternach = "#FFF"
)

lux_shp |> 
  group_by(CANTON) |> 
  mutate(n = row_number(),
    canton_label = if_else(n ==1, CANTON, ""),
    # centroid of each elements (county level)
    lon = st_coordinates(st_centroid(geometry))[,1],
    lat = st_coordinates(st_centroid(geometry))[,2],
    # median lon/lat of county centroids. It's a hack.
    med_lon = median(lon),
    med_lat = median(lat))  |> 
  ungroup() |> 
ggplot() + 
  geom_sf(aes(fill = CANTON) , 
          alpha = 0.7, 
          show.legend = FALSE, linewidth = 0.1) +
  theme_bw()  + scale_fill_manual(values = commune) +
  geom_text(aes(x = med_lon, y = med_lat, label = canton_label), size = 4) +
  # geom_sf_text does not take x, y
  labs(title = "The cantons of Luxembourg",
       x = NULL, 
       y = NULL)

Four color theorem

Projection

CRS 4326

euro_map |> 
  ggplot() +
 geom_sf(aes(fill = gdp_md/pop_est)) + 
    coord_sf(xlim = c(-15, 35),
           ylim = c(32, 72.5), 
           crs = 4326) + #<< 
  guides(fill = "none")

CRS 4181

euro_map |> 
  ggplot() +
 geom_sf(aes(fill = gdp_md/pop_est)) + 
    coord_sf(xlim = c(-15, 35),
           ylim = c(32, 72.5),
           crs = 4181) + #<<
  guides(fill = "none")

Luxembourg by different CRS

CRS 4326

lux_commune_map + coord_sf(crs = 4326)

CRS 4100

lux_commune_map + coord_sf(crs = 4100)

Transforming using the Coordinate Reference System (CRS)

(ggplot(data = world) +
  geom_sf(mapping = aes(fill = continent)) +
  scale_fill_viridis_d(name = "Continent",
                      na.value = "grey50") +
  theme(legend.position = "bottom") -> continent_map)

We want to add our spot; just using coordinates will not work after transformations.

msa_2230
     long      lat
1 5.94944 49.50443
  • coord_sf(crs = 4100)

Projections

continent_map +
  # Converting our position
  geom_sf(data =
            st_as_sf(msa_2230, 
                     coords = c("long", "lat"), 
                     crs = 4181), #<< Spatial reference
          color = "red") 
st_as_sf(msa_2230,
         coords = c("long", "lat"), 
         crs = 4181)
Simple feature collection with 1 feature and 0 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: 5.94944 ymin: 49.50443 xmax: 5.94944 ymax: 49.50443
Geodetic CRS:  Luxembourg 1930
                  geometry
1 POINT (5.94944 49.50443)

CRS4181: Luxembourg 1930

View from the pole

continent_map +
  # Converting our position
  geom_sf(data =
            st_as_sf(msa_2230, 
                     coords = c("long", "lat"), 
                     crs = 4181), color = "red") +
  # rotating globe
  coord_sf(crs = 3572) #<<

Removing Antarctica

world |> 
  filter(continent != "Antarctica") |> 
ggplot() +
  geom_sf() +
  geom_sf(mapping = aes(fill = continent)) +
  scale_fill_viridis_d(name = "Continent",
                      na.value = "grey50") +
  # Converting our position
  geom_sf(data =
            st_as_sf(msa_2230, 
                     coords = c("long", "lat"), 
                     crs = 4181), color = "red") +
  # rotating globe
  coord_sf(crs = 3572) #<<

Before we stop

We looked at

  • Basic maps in ggplot
  • Spatial features in sf
  • Data from the Natural Earth project in R
  • Importing Shapefiles for high-resolution maps
  • Using the Coordinate Reference System

Acknowledgements

  • Claus O. Wilke

Thank for your attention!