Spatial analysis in R

class: center, middle, inverse, title-slide

# Spatial analysis in R
### Alec Robitaille
### Wildlife Evolutionary Ecology Lab
### 2020-05-04

---

class: clear, middle, review

.center[
.large[
First, a discussion: why use R for spatial analysis?
]
]

???
Walk away from long running tasks
History of commands, steps
Automated complex workflows
Use Git

---
# Spatial R ecosystem

![](https://keen-swartz-3146c4.netlify.app/images/sf_deps.png)

CRAN Task Views:  [Spatial](https://cran.r-project.org/web/views/Spatial.html) and  [SpatioTemporal](https://cran.r-project.org/web/views/SpatioTemporal.html). [History of R spatial](https://bookdown.org/robinlovelace/geocompr/intro.html#the-history-of-r-spatial)

???
Note: we are going to emphasize the `sf` package here since it is the *way forward*

---
# Vector file formats: Shapefile

.pull-left[

\+ widely used and supported

\- multifile format

\- limit to 10 character attribute names, automatic

\- maximum file size of 2-4GB

\- limited to single geometry types
]

.pull-right[

```
input/
├── breweries.dbf
├── breweries.prj
├── breweries.shp
└── breweries.shx
```

]

---
# Vector file formats: GeoJSON

```json
{
  "type": "Feature",
  "geometry": {
    "type": "Point",
    "coordinates": [125.6, 10.1]
  },
  "properties": {
    "name": "Dinagat Islands"
  }
}
```

---
# Vector file formats: GeoPackage

\+ single file

\+ stores vectors and rasters

\+ widely supported

\+ uses a SQLite backend

\- non-streaming format

---
# Encoding vectors: Simple features

.center[
![](https://bookdown.org/robinlovelace/geocompr/figures/sf-classes.png)
]

---
# Raster data
https://bookdown.org/robinlovelace/geocompr/spatial-class.html#raster-data

---
# Resources

(This is not a comprehensive list)

Packages

* [`sf`](https://github.com/r-spatial/sf)
* [`raster`](https://rspatial.org/raster/pkg/index.html)
* [`mapview`](https://r-spatial.github.io/mapview/index.html)

Spatial books

* [Geocomputation with R - Robin Lovelace, Jakub Nowosad, Jannes Muenchow ](https://bookdown.org/robinlovelace/geocompr)

* [Spatial Data Science - Edzer Pebesma, Roger Bivand](https://keen-swartz-3146c4.netlify.app/)

* [Spatial Data Science with R](https://rspatial.org/)

* A good basic overview: [mapschool.io](https://mapschool.io/)

General R books

* [Efficient R programming](https://csgillespie.github.io/efficientR/)