Spatial Data Visualization with R

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.title[
# Spatial Data Visualization with R
]
.author[
### Dr Thiyanga S. Talagala
]
.author[
### 
]

---

## What geometries do you see on the map?

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# Geospatial Vector Data

1. Points: single (x, y) point

2. Lines: two or more connected (x, y) points

3. Polygon: three or more (x, y) points connected and closed

---

## Globe to Plane

What do we want to plot?

Globe - 3D Space

Where do we plot?

Computer screen or paper - 2D Space

To define the location of objects on the Earth, which is round, we need a coordinate system that adapts to the Earth’s shape.

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# Coordinate Reference System (CRS)

- the way in which spatial data that represent the earth’s surface (which is round / 3 dimensional) are flattened so that you can “Draw” them on a 2-dimensional surface.

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## Components of CRS

Coordinate system: X, Y grid to define a point located in space

Horizontal and vertical units

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## Why multiple CRS?

To optimize to best represent the

shape and/or

scale / distance and/or

area

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### Maps of the United States in Different CRS

Source: https://www.earthdatascience.org/

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### Human head projections using different CRS

.pull-left[

<img src="https://thiyanga-spatiotemporal.netlify.app/posts/time_series/head.jpeg" width="90%" style="display: block; margin: auto;" />
]

.pull-right[

Source: https://www.earthdatascience.org/

]

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# Shapefile

- Vector data storage format for storing the location, shape, and attributes of geographic features

- A shapefile is made up of three required files with the same prefix ('spatial-data' in this case) but different extensions:

- spatial-data.shp: main file that stores records of each shape geometries

- spatial-data.shx: index of how the geometries in the main file relate to one-another

- spatial-data.dbf: attributes of each record

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### CRS vs Shapefile

- Shapefiles contain geographic vector data that is expressed in a particular CRS

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## Map types

.pull-left[
<img src="https://open.lib.umn.edu/app/uploads/sites/178/2017/07/Image076.jpg" width="90%" style="display: block; margin: auto;" />
]

.pull-right[

source: https://open.lib.umn.edu/mapping/chapter/5-simplification/

]

---

## Sri Lanka

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

```r
library(ceylon)
library(tidyverse)
library(sp)
library(viridis)
```

---

```r
data(sf_sl_0)
ggplot(sf_sl_0) + geom_sf()
```

More information: https://github.com/thiyangt/ceylon

---

# ozmaps package

```r
library(sf)
library(ozmaps)
library(kableExtra)
library(knitr)
sf_oz <- ozmap_data("country")
sf_oz %>% kable()
```

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> NAME </th>
   <th style="text-align:left;"> geometry </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Australia </td>
   <td style="text-align:left;"> MULTIPOLYGON (((144.8691 -4... </td>
  </tr>
</tbody>
</table>

---

```r
ggplot(sf_oz) + geom_sf()
```

---

![](mapcrs.png)

---

## Tutorial: Visualizing spatial data

https://tstdataviz.netlify.app/slides/spatiotemporal.html