Displaying Geo-Spatial Data with RIASSL WorkshopDr. Priyanga D. Talagala, University of Moratuwa 21-25, February, 20221

Main packages required

# Data manipulation and plotting functions
library(tidyverse)
# sf: objects with simple features
library("sf")
# Provides a map of countries of the entire world
library("rnaturalearth")
library("rnaturalearthdata")

The combination of ggplot2 and sf therefore enables to programmatically create maps.

world <- ne_countries(scale = "medium", returnclass = "sf")
class(world)

## [1] "sf"         "data.frame"

colnames(world)

##  [1] "scalerank"  "featurecla" "labelrank"  "sovereignt" "sov_a3"    
##  [6] "adm0_dif"   "level"      "type"       "admin"      "adm0_a3"   
## [11] "geou_dif"   "geounit"    "gu_a3"      "su_dif"     "subunit"   
## [16] "su_a3"      "brk_diff"   "name"       "name_long"  "brk_a3"    
## [21] "brk_name"   "brk_group"  "abbrev"     "postal"     "formal_en" 
## [26] "formal_fr"  "note_adm0"  "note_brk"   "name_sort"  "name_alt"  
## [31] "mapcolor7"  "mapcolor8"  "mapcolor9"  "mapcolor13" "pop_est"   
## [36] "gdp_md_est" "pop_year"   "lastcensus" "gdp_year"   "economy"   
## [41] "income_grp" "wikipedia"  "fips_10"    "iso_a2"     "iso_a3"    
## [46] "iso_n3"     "un_a3"      "wb_a2"      "wb_a3"      "woe_id"    
## [51] "adm0_a3_is" "adm0_a3_us" "adm0_a3_un" "adm0_a3_wb" "continent" 
## [56] "region_un"  "subregion"  "region_wb"  "name_len"   "long_len"  
## [61] "abbrev_len" "tiny"       "homepart"   "geometry"

world %>%
  filter(admin == "Sri Lanka")

## Simple feature collection with 1 feature and 63 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 79.70781 ymin: 5.949365 xmax: 81.87695 ymax: 9.812695
## CRS:           +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0
##   scalerank      featurecla labelrank sovereignt sov_a3 adm0_dif level
## 1         1 Admin-0 country         3  Sri Lanka    LKA        0     2
##                type     admin adm0_a3 geou_dif   geounit gu_a3 su_dif   subunit
## 1 Sovereign country Sri Lanka     LKA        0 Sri Lanka   LKA      0 Sri Lanka
##   su_a3 brk_diff      name name_long brk_a3  brk_name brk_group abbrev postal
## 1   LKA        0 Sri Lanka Sri Lanka    LKA Sri Lanka      <NA> Sri L.     LK
##                                    formal_en formal_fr note_adm0 note_brk
## 1 Democratic Socialist Republic of Sri Lanka      <NA>      <NA>     <NA>
##   name_sort name_alt mapcolor7 mapcolor8 mapcolor9 mapcolor13  pop_est
## 1 Sri Lanka     <NA>         3         5         4          9 21324791
##   gdp_md_est pop_year lastcensus gdp_year              economy
## 1      91870       NA       2001       NA 6. Developing region
##               income_grp wikipedia fips_10 iso_a2 iso_a3 iso_n3 un_a3 wb_a2
## 1 4. Lower middle income        NA    <NA>     LK    LKA    144   144    LK
##   wb_a3 woe_id adm0_a3_is adm0_a3_us adm0_a3_un adm0_a3_wb continent region_un
## 1   LKA     NA        LKA        LKA         NA         NA      Asia      Asia
##       subregion  region_wb name_len long_len abbrev_len tiny homepart
## 1 Southern Asia South Asia        9        9          6   NA        1
##                         geometry
## 1 MULTIPOLYGON (((79.8748 9.0...

Creating a base map of the world using ggplot2

ggplot(data = world) + 
  geom_sf()

ggplot(data = world) +
    geom_sf() +
    xlab("Longitude") + ylab("Latitude") +
    ggtitle("World map", 
            subtitle = paste0("(",
                  length(unique(world$NAME)), " countries)"))

Shows the population of each country using the population (which is stored in the variable POP_EST of the world object)

ggplot(data = world) +
    geom_sf(aes(fill = pop_est)) +
    scale_fill_viridis_c(option = "plasma")

Shows the population of each country using the square root of the population (which is stored in the variable POP_EST of the world object)

ggplot(data = world) +
    geom_sf(aes(fill = pop_est)) +
    scale_fill_viridis_c(option = "plasma", trans = "sqrt")

`ceylon` package

The goal of ceylon is to provide data to plot maps of Sri Lanka.

https://github.com/thiyangt/ceylon

# install.packages("devtools")
# devtools::install_github("thiyangt/ceylon")
library(ceylon)

Country level

data(sf_sl_0)
ggplot(sf_sl_0) +
  geom_sf()

Provinces of Sri Lanka

data(province)
province

## Simple feature collection with 9 features and 3 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 362203.3 ymin: 380301.9 xmax: 621918.1 ymax: 813560.9
## Projected CRS: SLD99 / Sri Lanka Grid 1999
## # A tibble: 9 × 4
##                                              geometry PROVINCE Status population
## *                                  <MULTIPOLYGON [m]> <chr>    <chr>       <dbl>
## 1 (((498211.2 611042.6, 498401.7 610897.1, 498415.9 … CENTRAL  Provi…    2781000
## 2 (((609877 559315.9, 609857.5 559313, 609845.2 5593… EASTERN  Provi…    1746000
## 3 (((501928.5 712099.6, 501970.4 712098.8, 502020 71… NORTH C… Provi…    1386000
## 4 (((393087.5 629959, 393098.1 629956.7, 393103.2 62… NORTH W… Provi…    2563000
## 5 (((405858.7 700083.7, 405855.3 700082, 405851.5 70… NORTHERN Provi…    1152000
## 6 (((432117.3 521875.5, 432083.5 521852.9, 432041.7 … SABARAG… Provi…    2070000
## 7 (((481925.5 381353.7, 481922.9 381350.3, 481919 38… SOUTHERN Provi…    2669000
## 8 (((522825 568220.9, 522872.6 568217.7, 522926.1 56… UVA      Provi…    1387000
## 9 (((411888.2 438189.4, 411886.4 438182.3, 411881.7 … WESTERN  Provi…    6165000

Provinces of Sri Lanka

ggplot(province) + 
  geom_sf()

Provinces of Sri Lanka

ggplot(province) + 
  geom_sf(mapping = aes(fill = PROVINCE),
          show.legend = TRUE)

Distribution of Population by Provinces

ggplot(province) + 
  geom_sf(mapping = aes(fill = population),
          show.legend = TRUE)

Distribution of Population by Districts

library(viridis)
data(district)
ggplot(district) +
  geom_sf(aes(fill = population),
          show.legend = TRUE) + 
  scale_fill_viridis()

Divisional secretariat

data(sf_sl_3)
ggplot(sf_sl_3) + 
  geom_sf()

Join (merge) data with dplyr in R

Source: https://data-lessons.github.io/gapminder-R/12-joins.html

Learn more: https://rpubs.com/williamsurles/293454

head(district)

## Simple feature collection with 6 features and 3 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 391095.2 ymin: 445857.8 xmax: 621918.1 ymax: 712393.4
## Projected CRS: SLD99 / Sri Lanka Grid 1999
## # A tibble: 6 × 4
##                                              geometry DISTRICT Status population
##                                    <MULTIPOLYGON [m]> <chr>    <chr>       <dbl>
## 1 (((392952.6 594064.2, 392985.8 593971.5, 392986.2 … [UNKNOW… <NA>           NA
## 2 (((551311.8 581603.6, 551324.5 581599.7, 551334.5 … AMPARA   Distr…     736000
## 3 (((501928.5 712099.6, 501970.4 712098.8, 502020 71… ANURADH… Distr…     943000
## 4 (((522825 568220.9, 522872.6 568217.7, 522926.1 56… BADULLA  Distr…     886000
## 5 (((609877 559315.9, 609857.5 559313, 609845.2 5593… BATTICA… Distr…     579000
## 6 (((400911.5 497888.4, 401032.5 497869.3, 401035.2 … COLOMBO  Distr…    2455000

Dealing with our own datasets

DISTRICT <- c("Ampara", "Anuradhapura", "Badulla", 
              "Batticaloa", "Colombo", "Galle", "Gampaha",
              "Hambantota", "Jaffna", "Kalutara", "Kandy",
              "Kegalle", "Kilinochchi", "Kurunegala",
              "Mannar", "Matale", "Matara", "Monaragala",
              "Mullaitivu", "Nuwara eliya", "Polonnaruwa", 
              "Puttalam", "Ratnapura", "Trincomalee", 
              "Vavuniya"   )
covidcount<- c(13867, 14351, 14290, 9824, 132418, 42314, 111221, 18631,
              12222, 56672, 21369, 13225, 9597, 30507, 2523, 15211, 20905,
              14723, 2192, 12240, 5197, 14901, 22650, 4364, 3644)
newdate <- tibble(DISTRICT, covidcount )

Convert case of a string

https://stringr.tidyverse.org/reference/case.html

head(newdate)

## # A tibble: 6 × 2
##   DISTRICT     covidcount
##   <chr>             <dbl>
## 1 Ampara            13867
## 2 Anuradhapura      14351
## 3 Badulla           14290
## 4 Batticaloa         9824
## 5 Colombo          132418
## 6 Galle             42314

newdate <- newdate %>%
  mutate(DISTRICT= stringr::str_to_upper(
    DISTRICT, locale = "en"))
head(newdate)

## # A tibble: 6 × 2
##   DISTRICT     covidcount
##   <chr>             <dbl>
## 1 AMPARA            13867
## 2 ANURADHAPURA      14351
## 3 BADULLA           14290
## 4 BATTICALOA         9824
## 5 COLOMBO          132418
## 6 GALLE             42314

Merge Data

full_data <- left_join(district, newdate, by= "DISTRICT")
head(full_data)

## Simple feature collection with 6 features and 4 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 391095.2 ymin: 445857.8 xmax: 621918.1 ymax: 712393.4
## Projected CRS: SLD99 / Sri Lanka Grid 1999
## # A tibble: 6 × 5
##                                   geometry DISTRICT Status population covidcount
##                         <MULTIPOLYGON [m]> <chr>    <chr>       <dbl>      <dbl>
## 1 (((392952.6 594064.2, 392985.8 593971.5… [UNKNOW… <NA>           NA         NA
## 2 (((551311.8 581603.6, 551324.5 581599.7… AMPARA   Distr…     736000      13867
## 3 (((501928.5 712099.6, 501970.4 712098.8… ANURADH… Distr…     943000      14351
## 4 (((522825 568220.9, 522872.6 568217.7, … BADULLA  Distr…     886000      14290
## 5 (((609877 559315.9, 609857.5 559313, 60… BATTICA… Distr…     579000       9824
## 6 (((400911.5 497888.4, 401032.5 497869.3… COLOMBO  Distr…    2455000     132418

Distribution of Total Covid Count by Districts

ggplot(full_data) +
  geom_sf(aes(fill = covidcount),
          show.legend = TRUE) + 
  scale_fill_viridis()

pridiltal and thiyangt

Acknowledgements:

This work was supported in part by RETINA research lab funded by the OWSD, a program unit of United Nations Educational, Scientific and Cultural Organization (UNESCO).

# Data manipulation and plotting functions library(tidyverse) # sf: objects with simple features library("sf") # Provides a map of countries of the entire world library("rnaturalearth") library("rnaturalearthdata")

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Displaying Geo-Spatial Data with R

IASSL Workshop

Dr. Priyanga D. Talagala, University of Moratuwa

21-25, February, 2022

Main packages required

ceylon package

Dealing with our own datasets

Convert case of a string

Acknowledgements:

Main packages required

Help

`ceylon` package