Displaying Geo-Spatial Data with R

class: center, middle, inverse, title-slide

# Displaying Geo-Spatial Data with R
## IASSL Workshop
### Dr. Priyanga D. Talagala, University of Moratuwa
### 21-25, February, 2022

---

### Main packages required

```r
# 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.

---

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

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

```r
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"
```

---

```r
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

```r
ggplot(data = world) + 
* geom_sf()
```

<img src="11_maps_files/figure-html/unnamed-chunk-4-1.png" style="display: block; margin: auto;" />
---

```r
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)

```r
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)

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

<img src="11_maps_files/figure-html/unnamed-chunk-7-1.png" style="display: block; margin: auto;" />
---

## `ceylon` package

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

https://github.com/thiyangt/ceylon

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

<img src="fig/1_ceylon.png" width="20%" style="display: block; margin: auto;" />
---

Country level

.pull-left[

```r
data(sf_sl_0)
ggplot(sf_sl_0) +
  geom_sf()
```
].pull-right[

]
---
Provinces of Sri Lanka

```r
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

.pull-left[

```r
ggplot(province) + 
  geom_sf()
```
]..pull-right[

<img src="11_maps_files/figure-html/unnamed-chunk-14-1.png" style="display: block; margin: auto;" />
]
---

Provinces of Sri Lanka

.pull-left[

```r
ggplot(province) + 
* geom_sf(mapping = aes(fill = PROVINCE),
*         show.legend = TRUE)
```
]..pull-right[

<img src="11_maps_files/figure-html/unnamed-chunk-16-1.png" style="display: block; margin: auto;" />
]

---
Distribution of Population by Provinces
 
.pull-left[

```r
ggplot(province) + 
  geom_sf(mapping = aes(fill = population),
          show.legend = TRUE)
```
]..pull-right[

<img src="11_maps_files/figure-html/unnamed-chunk-18-1.png" style="display: block; margin: auto;" />
]
---
Distribution of Population by Districts

.pull-left[

```r
library(viridis)
*data(district)
*ggplot(district) +
  geom_sf(aes(fill = population),
          show.legend = TRUE) + 
  scale_fill_viridis()
```
]..pull-right[

<img src="11_maps_files/figure-html/unnamed-chunk-20-1.png" style="display: block; margin: auto;" />
]
---
Divisional secretariat

.pull-left[

```r
data(sf_sl_3)
ggplot(sf_sl_3) + 
  geom_sf()
```
]..pull-right[

<img src="11_maps_files/figure-html/unnamed-chunk-22-1.png" style="display: block; margin: auto;" />
]
---
Join (merge) data with `dplyr` in R

[Source: https://data-lessons.github.io/gapminder-R/12-joins.html](https://data-lessons.github.io/gapminder-R/12-joins.html)

[Learn more: https://rpubs.com/williamsurles/293454](https://rpubs.com/williamsurles/293454)
---

```r
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

```r
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

.pull-left[

```r
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
```
].pull-right[

```r
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

```r
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

.pull-left[

```r
*ggplot(full_data) +
* geom_sf(aes(fill = covidcount),
          show.legend = TRUE) + 
  scale_fill_viridis()
```
].pull-right[

<img src="11_maps_files/figure-html/unnamed-chunk-30-1.png" style="display: block; margin: auto;" />
]
---
class: inverse, middle, center

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).