Geospatial Data Geospatial Representations

class: left, top, title-slide

.title[
# Geospatial Data<br>Geospatial Representations
]
.author[
### Keith VanderLinden<br>Calvin University
]

---

# Example

.pull-left[

```r
library(leaflet)
popup = c("Calvin", "CU", "ITRI", "CSIRO")
leaflet(width = 500, height = 500) %>%
  addProviderTiles(
    "NASAGIBS.ViirsEarthAtNight2012"
    ) %>%
  addMarkers(
    lng = c(-85.67, -105.27, -0.15, 151.20),
    lat = c(42.96, 40.01, 50.82, -33.86), 
    popup = popup
  ) %>%
  addPolylines(
    lng = c(-180.0, 180.0),
    lat = c(0.0, 0.0),
    weight = 1, color = "red"
  ) %>%
  addPolylines(
    lng = c(0.0, 0.0),
    lat = c(-90.0, 90.0), 
    weight = 1, color = "red"
  )
```
]
.pull-right[
<div id="htmlwidget-8f836166d559454ecd73" style="width:500px;height:500px;" class="leaflet html-widget "></div>
<script type="application/json" data-for="htmlwidget-8f836166d559454ecd73">{"x":{"options":{"crs":{"crsClass":"L.CRS.EPSG3857","code":null,"proj4def":null,"projectedBounds":null,"options":{}}},"calls":[{"method":"addProviderTiles","args":["NASAGIBS.ViirsEarthAtNight2012",null,null,{"errorTileUrl":"","noWrap":false,"detectRetina":false}]},{"method":"addMarkers","args":[[42.96,40.01,50.82,-33.86],[-85.67,-105.27,-0.15,151.2],null,null,null,{"interactive":true,"draggable":false,"keyboard":true,"title":"","alt":"","zIndexOffset":0,"opacity":1,"riseOnHover":false,"riseOffset":250},["Calvin","CU","ITRI","CSIRO"],null,null,null,null,{"interactive":false,"permanent":false,"direction":"auto","opacity":1,"offset":[0,0],"textsize":"10px","textOnly":false,"className":"","sticky":true},null]},{"method":"addPolylines","args":[[[[{"lng":[-180,180],"lat":[0,0]}]]],null,null,{"interactive":true,"className":"","stroke":true,"color":"red","weight":1,"opacity":0.5,"fill":false,"fillColor":"red","fillOpacity":0.2,"smoothFactor":1,"noClip":false},null,null,null,{"interactive":false,"permanent":false,"direction":"auto","opacity":1,"offset":[0,0],"textsize":"10px","textOnly":false,"className":"","sticky":true},null]},{"method":"addPolylines","args":[[[[{"lng":[0,0],"lat":[-90,90]}]]],null,null,{"interactive":true,"className":"","stroke":true,"color":"red","weight":1,"opacity":0.5,"fill":false,"fillColor":"red","fillOpacity":0.2,"smoothFactor":1,"noClip":false},null,null,null,{"interactive":false,"permanent":false,"direction":"auto","opacity":1,"offset":[0,0],"textsize":"10px","textOnly":false,"className":"","sticky":true},null]}],"limits":{"lat":[-90,90],"lng":[-180,180]}},"evals":[],"jsHooks":[]}</script>
]

???
- The lat/long data are floats, but their meaning is based on geospatial relationships.
- The satellite image is raster data from https://wiki.earthdata.nasa.gov/display/GIBS/GIBS+API+for+Developers#GIBSAPIforDevelopers-TimeDimension.
- The points are vector data representing the equator, the prime meridian, and a few sites of interest.
- Cf. Google Maps with "satellite view" (except at night).

---
# GeoSpatial Data

.pull-left[
Geospatial data are numerical but the numbers carry spatial meaning. These data come in two basic forms:

- *Raster* data represent sensory data using two-dimensional arrays of cells of fixed size.

- *Vector* data represent geometric features using points, lines and polygons.

We will primarily focus on the latter.

.footnote[Images from [DataCarpentry](https://datacarpentry.org/organization-geospatial/) &amp; [R. Lovelace et al](https://geocompr.robinlovelace.net).]
]

.pull-right[
Raster Primitives
![Raster Data](images/raster.png)
Vector 
![Vector Data](images/vector.png)
]

???
- Raster data are used for images (and other sensing devices). 
  - The images comprise 2D arrays of pixels (grid cells), each with a set color (or other sensory value).
  - They're good for continuous features.
  - They're commonly used in environmental sciences, where remote sensor data matters.
- Vector data are precise and are used for locations, boundaries, ...
  - These data use coordinates to specify points/lines/polygons,, e.g., multipolygons for geographical objects, e.g., Indonesia.
  - They're good for features with discrete boundaries.
  - They're commonly used in the social sciences, where political borders matter. 
  - Don't confuse geospatial vector data with R vectors.
- Related terms: GIS (1960s), GeoInformatics

---
# Raster Data

The [`terra` library](https://rspatial.github.io/terra/) supports raster images.

.pull-left[

```r
library(terra)
library(spDataLarge)

zion_raster <- rast(
  system.file(
    "raster/srtm.tif", 
    package = "spDataLarge"
    )
  )

plot(zion_raster)
```
]
.pull-right[
Zion National Park Area Elevation
<img src="data_files/figure-html/unnamed-chunk-4-1.png" width="90%" style="display: block; margin: auto;" />
]

???
- So does the older `raster` library.

---
# Vector Data

The [`sf` library](https://r-spatial.github.io/sf/index.html) supports vector data.

.pull-left[

```r
library(sf)

zion_vector <- read_sf(
  system.file(
    "vector/zion.gpkg", 
    package = "spDataLarge"
    )
  )

plot(st_geometry(zion_vector["REGION"]))
```
]
.pull-right[
Zion National Park Boundary
<img src="data_files/figure-html/unnamed-chunk-5-1.png" width="90%" style="display: block; margin: auto;" />
]

???
- So do the older `sp`, `rgeos`, & `rdal` libraries.
- SF stands for "Simple Features" or, perhaps more appropriately, "Spatial data Frames"
- `sf` treats geospatial objects as regular dataframes and integrates with the tidyverse. 
- `plot`ing an `sf` object displays a map.

---
# Combining Raster and Vector Data

It&rsquo;s often useful to combine raster and vector data.

.pull-left[

```r
# Unify the coordinate reference systems.
zion_vector_wgs84 <- zion_vector %>%
  st_transform(crs(zion_raster))

# Mask out 
zion_raster_cropped <- zion_raster %>%
  mask(vect(zion_vector_wgs84))

plot(zion_raster_cropped)
```
]
.pull-right[
Zion National Park Elevation
<img src="data_files/figure-html/unnamed-chunk-6-1.png" width="90%" style="display: block; margin: auto;" />
]

???
- We convert `zion` to the CRS of the `srtm` dataset
  (`crs(srtm)` - WGS84, aka EPSG4326 - used by GPS & GoogleEarth). 
- Open [the combined image](http://vps58738.lws-hosting.com/Teaching/RSIG/Cours/_book/_main_files/figure-html/srtmZion-1.png) in a photo editor and show how the raster pixelates when zoomed but not the vector data.
- References:
  - https://geocompr.robinlovelace.net/raster-vector.html