Geospatial Visualization using R

# Geospatial Visualization using R
## Part 3: Spatial Data
### Bhaskar V. Karambelkar
### 2017/07/04

---

# Part3: Spatial Data

- Vector Data

- Raster Data

- Spatio-Temporal Data

- Multi-Dimensional Spatial Data

---

# Vector Data

---

# The `sp` Package

- **`sp`** package contains S4 classes to represent 2D vector data.

- Line / Lines / Polygon / Polygons

- SpatialPoints / SpatialMultiPoints / SpatialLines / SpatialPolygons

- SpatialPointsDataFrame (SPnDF), SMPnPDF, SLDF, SPoDF (Not really data.frame objects)

- `rgdal::readOGR` function returns `sp` object/s from data stored in files.

- Not compatible with the 'tidyverse' way, and `sp` operations can be slow.

- `ggplot2` + `sp` is cumbersome as we shall see in Part 5.

---

# A sample `sp` Object

```r
suppressPackageStartupMessages(library(sp))
data(meuse)
class(meuse)
```

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

```r
colnames(meuse)
```

```
##  [1] "x"       "y"       "cadmium" "copper"  "lead"    "zinc"    "elev"   
##  [8] "dist"    "om"      "ffreq"   "soil"    "lime"    "landuse" "dist.m"
```

```r
* coordinates(meuse) <- ~x+y 
* proj4string(meuse) <- CRS("+init=epsg:28992")  # see footnote 1.
class(meuse)
```

```
## [1] "SpatialPointsDataFrame"
## attr(,"package")
## [1] "sp"
```

.footnote[1: See this [PDF](https://www.nceas.ucsb.edu/~frazier/RSpatialGuides/OverviewCoordinateReferenceSystems.pdf) for CRS support in R.]
---

# Plot a `sp` Object

```r
plot(meuse); box(); title('The meuse dataset')
```

---

# Read a `sp` Object

```r
# For some fun and enlightenment run w/o suppressing the output.
suppressPackageStartupMessages(library(rgdal))
dsn <- system.file("vectors", package = "rgdal")[1]
 # Uncomment and See
# ogrInfo(dsn=dsn, layer="scot_BNG")
# OGRSpatialRef(dsn=dsn, layer="scot_BNG")

* scot_BNG <- readOGR(dsn=dsn, layer="scot_BNG") 
```

```
## OGR data source with driver: ESRI Shapefile 
## Source: "/home/bhaskar/Library/R/3.x/cran/rgdal/vectors", layer: "scot_BNG"
## with 56 features
## It has 13 fields
```

```r
class(scot_BNG)
```

```
## [1] "SpatialPolygonsDataFrame"
## attr(,"package")
## [1] "sp"
```

---

# Simple Features

- Simple Features is a two part OGC and ISO standard for common storage and access model of 2D geometries.

- Part one defines a hierarchy of classes and their textual and binary representation using Well-known text (WKT) and binary (WKB) formats.

- e.g. `POLYGON ((30 10, 40 40, 20 40, 10 20, 30 10))` ![](https://upload.wikimedia.org/wikipedia/commons/thumb/3/3f/SFA_Polygon.svg/51px-SFA_Polygon.svg.png)

- Part two specifies the SQL interface to access this data.

- Everything on this slide came straight from the Wikipedia entry for [Simple Features](https://en.wikipedia.org/wiki/Simple_Features) and [Well-known text](https://en.wikipedia.org/wiki/Well-known_text).

---

# The `sf` Package

- The `sf` package is the implementation of Simple Features Access standard.

- Instead of S4 classes, uses `data.frame`s with `list-columns` for storing geometries.

- Way faster than `sp` and plays nicely with `tidyverse` packages.

- Easy to plot with `ggplot2` or `leaflet`.

- Also unlike `sp`, a single `sf` object can contain geometries of different kinds.

- `sf` functions start with `st`, `sfg` is the geometry of a feature,<br/> `sfc` is the list-column of a `sf` `data.frame` object containing a list of geometries.

---

# Sample `sf` Object

```r
library(sf)
```

```
## Linking to GEOS 3.5.1, GDAL 2.1.3, proj.4 4.9.2, lwgeom 2.3.2 r15302
```

```r
* scot_BNG <- sf::st_read(system.file("vectors", package = "rgdal")[1], 'scot_BNG') 
```

```
## Reading layer `scot_BNG' from data source `/home/bhaskar/Library/R/3.x/cran/rgdal/vectors' using driver `ESRI Shapefile'
## Simple feature collection with 56 features and 13 fields
## geometry type:  MULTIPOLYGON
## dimension:      XY
## bbox:           xmin: 7094.552 ymin: 529495 xmax: 468285.5 ymax: 1218342
## epsg (SRID):    NA
## proj4string:    +proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000 +datum=OSGB36 +units=m +no_defs
```

```r
names(scot_BNG)
```

```
##  [1] "SP_ID"    "NAME"     "ID_x"     "COUNT"    "SMR"      "LONG"    
##  [7] "LAT"      "PY"       "EXP_"     "AFF"      "X_COOR"   "Y_COOR"  
## [13] "ID_y"     "geometry"
```

---

# Raster Data

---

# The `raster` package

- Defines `RasterLayer` / `RasterStack` / `RasterBrick` classes.

- Defines operations on raster data.

## Sample `raster` object

```r
suppressPackageStartupMessages(library(raster))
* r <- raster(system.file("external/test.grd", package="raster")) 
class(r)
```

```
## [1] "RasterLayer"
## attr(,"package")
## [1] "raster"
```

---

# Plot a `raster` object

```r
* plot(r)  
plot(meuse, add=T) # Add Vector Data
box(); title('Raster + Vector')
```

---

# Part 3: The End!

Continue to [Part 4: Spatial Data Operations](04-Spatial_Data_Operations.html)