1. Spatial

2. Outline Types of Spatial Data R Spatial packages S4 R objects
Projections
Spatial methods
SpatialPoints
SpatialLines/SpatialPolygons
SpatialPixels
SpatialPoints - Sample Dataset
Importing/Exporting
Spatial information and slots
Displaying
SpatialPolygons - Sample Dataset
Reprojecting
SpatialPixels - Sample Dataset
Importing/Exporting rasters
Deriving
Thematic rasters (importing, spatial info, reclassing)
Temporary files

3. Spatial Data in R ## Types of Spatial Data
Points - a set of single point locations
Lines - an ordered set of points, connected by straight line segments
Polygons – an area, with enclosed lines, possibly containing holes
Rasters – a collection of points or rectangular cells, in grid format
## R Spatial packages
sp Basic R classes for handling geospatial data
maptools Read and write shapefiles. Cannot read the projection file.
rgeos Interface to spatial geometry for sp objects
rgdal Supports GDAL raster formats and OGR vector formats..
Retains projection information when reading and writing (PROJ.4 library)
raster Spatial data analysis for rasters.
## Help links for spatial tools in R
# Summary of tools for Spatial data analysis

4. Spatial Data in R # Set working directory # Load libraries
path <- "W:/Techniques/Projects/Peru/Rworkshop"
setwd(path)
# Load libraries
library(sp)
library(maptools)
library(rgeos)
library(rgdal)
library(raster)

5. Spatial Data in R ## Spatial classes (sp package) Bivand, et al. 2008
getClass("Spatial")
Bivand, et al. 2008

6. Spatial Data in R ## S4 R objects
New-style classes with formal definitions that specify the name and type of the object's components, called slots.
## The Spatial class has 2 pre-defined slots
bbox – The bounding box, consisting of a matrix of coordinates defining the extent of the spatial object.
proj4string – The class object defining the coordinate reference system (CRS)
CRS contains datum and projection
datum – a surface that represents the shape of the earth
projection – renders the surface of an ellipsoid as a plane

7. Spatial Data in R ## Projections # rgdal package
PROJ.4 - Cartographic Projections Library
A library of projection functions to perform respective forward and inverse transformation of cartographic data.
# Format of projection string (proj4string)
"+proj=prj +ellps=GRS80 +datum=datum +no_defs”
# List of common projections
# More proj4string options..
" +proj=longlat +ellps=GRS80 +datum=NAD83 +no_defs"
" +proj=utm +zone=13 +datum=NAD83"
" +proj=utm +ellps=WGS84 +datum=WGS84 +zone=11, +units=m +towgs84=0,0,0"
" +proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=23 +lon_0=-96 +x_0=0 +y_0=0 +datum=NAD83 +units=m"
" +no_defs +ellps=GRS80 +towgs84=0,0,0"

8. Spatial Data in R ## Spatial methods (sp package)
## Common attributes of R objects:
# method - a function associated with a particular type of object (ex. summary, print)
## Spatial methods (sp package)
Bivand, et al. 2008

9. SpatialPoints
Bivand, et al. 2008

10. SpatialLines/Polygons
Lists of List Objects
List of Objects
Object
Bivand, et al. 2008

11. SpatialPixels
Similar to SpatialPoints with regularly spaced coordinates.
Bivand, et al. 2008

12. Sample Dataset
Utah, USA

13. Sample Dataset Uinta Mountains, Utah,USA
Highest East-West oriented mountain range in the contiguous U.S. - up to 13,528 ft (4,123 m)
High Uinta Wilderness
## Vegetation
5 different life zones:
shrub-montane
aspen
lodgepole pine
spruce-fir
alpine

14. SpatialPoints

15. SpatialPoints - Importing/Exporting
Sample Dataset
SpatialPoints - Importing/Exporting
## Import data frame with X/Y coordinates
## (FIA plot data with fuzzed/swapped coordinates)
plt <- read.csv("PlotData/plt.csv", header=TRUE, stringsAsFactors=FALSE)
## Generate SpatialPoints
x <- "LON"
y <- "LAT"
prj <- "longlat"
datum <- "NAD83"
prj4str <- "+proj=longlat +ellps=GRS80 +datum=NAD83 +no_defs"
ptshp <- SpatialPointsDataFrame(plt[,c(x,y)], plt, proj4string = CRS(prj4str))
class(ptshp)
# Export SpatialPoints
help(writeOGR)
writeOGR(ptshp, "Outfolder", "ptshp", driver="ESRI Shapefile")

16. SpatialPoints – Spatial Info
Sample Dataset
SpatialPoints – Spatial Info
## Get spatial information for ptshp
summary(ptshp) # General info and summary statistics for attribute # data of ptshp
mode(ptshp) # Get mode of ptshp
class(ptshp) # Get class of ptshp
is.projected(ptshp) # Check if ptshp has projection information
proj4string(ptshp) # Set or get projection information
str(ptshp) # Structure of ptshp

17. Sample Dataset SpatialPoints - Slots
## Get slot names and access slots for SpatialPoints
slotNames(ptshp) # Get name of ptshp components (slots)
# Get data frame attributes of ptshp
# Get coordinates of ptshp
# Get extent of ptshp
# Get projection information
# Get first 6 rows of data frame of ptshp
dim(ptshp) # Get dimensions of data frame of ptshp

18. SpatialPoints - Displaying
Sample Dataset
SpatialPoints - Displaying
## Display ptshp
plot(ptshp)
# Display ptshp points with red dots, half size
plot(ptshp, col="RED", pch=16, cex=0.5)
# Display subsets of ptshp
plot(ptshp[ptshp$INVYR==2002,], col="BLUE")
plot(subset(ptshp, INVYR==2003), col="RED", add=TRUE)
# pch codes
# Colors
colors()
## Help for point graphics

19. Sample Dataset ## Exercise 1 Exercise
## 1.1 Get the min and max coordinates of the boundary of ptshp.
## 1.2 Display points where elevation (ELEVM) are >= 3000 in dark green.
## 1.3 Add points where elevation (ELEVM) are < 3000 in yellow.
## 1.4 Overlay the point with the maximum elevation (ELEVM) in red.

20. SpatialPolygons

21. Sample Dataset SpatialPolygons # SpatialPolygons – file names
# Area of Interest (AOI) boundary (Uinta Mountains, UT)
aoifn <- "uintaN_aoi.shp"
# National Forest System boundary within AOI
nfsfn <- "uintaN_nfs.shp"
# High Uinta Wilderness boundary within AOI
wildfn <- "uintaN_wild.shp"

22. SpatialPolygons - Importing/Exporting
Sample Dataset
SpatialPolygons - Importing/Exporting
## Importing shapefiles using OGR drivers (rgdal)
## OGR functions
From the Geospatial Data Abstraction Library (GDAL), interfaced through rgdal.
Reads spatial data, including the spatial reference.
readOGR – reads OGR data source and layer into an R Spatial object
writeOGR – writes data out using supported drivers
Note: There are 2 main arguments.. that may take different forms, depending on the available drivers.
dsn – data source name
layer – the name of the layer
Note: A driver is a software component loaded on demand to enable a device to work with a computer's operating system.
ogrDrivers()
help(readOGR)

23. SpatialPolygons - Import
Sample Dataset
SpatialPolygons - Import
## Importing polygon shapefiles
## (AOI boundary, NFS boundary, Wilderness boundary)
# dsn – data source name (folder with layers)
# layer – the name of the layer (no extension)
## Set dsn
dsn <- "SpatialData"
## Spatial layer names
aoinm <- "uintaN_aoi"
nfsnm <- "uintaN_nfs"
wildnm <- "uintaN_wild"
## Import shapefiles
bndpoly <- readOGR(dsn=dsn, layer=aoinm, stringsAsFactors=FALSE)
nfspoly <- readOGR(dsn=dsn, layer=nfsnm, stringsAsFactors=FALSE)
wildpoly <- readOGR(dsn=dsn, layer=wildnm, stringsAsFactors=FALSE)

24. SpatialPolygons – Spatial Info
Sample Dataset
SpatialPolygons – Spatial Info
## Get spatial information for bndpoly
bndpoly # Get general information of polygon
summary(bndpoly) # Summary information for polygon
mode(bndpoly) # Get mode of bndpoly
typeof(bndpoly) # Get typeof
class(bndpoly) # Get class of bndpoly
proj4string(bndpoly) # Set or get projection information of bndpoly
bbox(bndpoly) # Get extent of bndpoly
dim(bndpoly) # Get dimension of bndpoly
str(bndpoly) # Get structure of bndpoly

25. SpatialPolygons - slots
Sample Dataset
SpatialPolygons - slots
(1)
(2)
(3)
# Get slot names for class SpatialPolygons (1)
getClass("SpatialPolygons")
slotNames(bndpoly)
@polygons # the list of Polygons objects
@plotOrder # the order to plot the Polygons
@bbox # bounding box slot
@proj4string # coordinate reference system slot
@data # associated data frame (for class SpatialPolygonsDataFrame objects)

26. SpatialPolygons – Displaying
Sample Dataset
SpatialPolygons – Displaying
## Display bndpoly
plot(bndpoly) # Display polygon shapefile
plot(bndpoly, col="blue") # Display polygon with blue fill color
plot(bndpoly, border="red", lwd=3) # red outline and line width=3
plot(bndpoly, col="blue", border="red", lwd=3) # blue fill
plot(bndpoly, col="blue", border="red", lwd=3, bg="black", axes=TRUE)
# with background colored and axes labels

27. SpatialPolygons – Spatial Info
Sample Dataset
SpatialPolygons – Spatial Info
# Get spatial information for nfspoly
nfspoly # Get general information of nfspoly
summary(nfspoly) # Summary information for nfspoly
dim(nfspoly) # Dimensions of nfspoly
str(nfspoly) # Get structure of nfspoly

28. SpatialPolygons - slots
Sample Dataset
SpatialPolygons - slots
(1)
(2)
(3)
# Get slot names for class SpatialPolygons (1)
getClass("SpatialPolygons")
slotNames(nfspoly)
@polygons # the list of Polygons objects
@plotOrder # the order to plot the Polygons
@bbox # bounding box slot
@proj4string # coordinate reference system slot
@data # associated data frame (for class SpatialPolygonsDataFrame objects)

29. SpatialPolygons - slots
Sample Dataset
SpatialPolygons - slots
(1)
(2)
(3)
# Get slot names for class Polygons (2)
getClass("Polygons")
# First feature
# a list of rings (islands/holes) that make up the feature
# the order to plot the feature
# label point coordinates of the feature
# unique identifier of the feature
# area of the feature (in units of feature projection)

30. SpatialPolygons - slots
Sample Dataset
SpatialPolygons - slots
(1)
(2)
(3)
# Get slot names for class Polygon (3)
getClass("Polygon")
"Polygons")[[1]])
# first ring of feature - class 'Polygon'
# label point coordinates of the feature ring
# area of the feature ring
# coordinates of the feature ring

31. SpatialPolygons - slots
Sample Dataset
SpatialPolygons - slots
# Accessing slots of SpatialPolygons
# Data frame attributes of shp
# Get info of each polygon within Spatial Polygons
# Get order of polygons within Spatial Polygons
# Get extent of bndpoly
# Accessing slots of Polygons
slot(nfspoly, "polygons") # (2)slots
slotsPolygons <- slot(nfspoly, "polygons") # (2)slots
typeof(slotsPolygons)
length(slotsPolygons)
sapply(slotsPolygons, function(x)slot(x, "ID")) # (2)slots
sapply(slotsPolygons, function(x)slot(x, "area")) # (2)slots
slotsPolygon <- "Polygons") # (3)slots
slotsPolygon <- "Polygons") # (3)slots

32. SpatialPolygons - Displaying
Sample Dataset
SpatialPolygons - Displaying
## Display nfspoly and wildpoly
plot(bndpoly, col="dark blue")
plot(nfspoly, border="yellow", add=TRUE, lwd=2)
plot(wildpoly, add=TRUE, border="green")
# Add points – in red
plot(ptshp, add=TRUE, col="red", pch=16, cex=0.5)

33. SpatialPolygons - Reprojecting
Sample Dataset
SpatialPolygons - Reprojecting
## Notice, the point layer did not display. Check the projections.
projection(bndpoly)
projection(ptshp)
## Reproject ptshp to projection of bndpoly
polyprj <- projection(bndpoly)
ptshpprj <- spTransform(ptshp, CRSobj=CRS(polyprj))
projection(ptshpprj)
# Add points – in red
plot(ptshpprj, add=TRUE, col="red", pch=16, cex=0.5)
# Add thicker boundary line
plot(bndpoly, lwd=3, add=TRUE)
# Add labels for nfspoly
text(nfspoly, nfspoly$FORESTNAME, cex=0.75, pos=3, col="white")

34. Sample Dataset ## Exercise 2 Exercise
## 2.1 Get projection of nfspoly.
## 2.2 Display the area of interest boundary (bndpoly) with no color fill.
## 2.3 Add the wilderness boundary (wildpoly) with green fill and with no outline.
## 2.4 Get total sum of area of nfspoly.

35. SpatialPixels

36. Sample Dataset # Elevation (m) SpatialPixels
# National Elevation Dataset (NED) in meters
elevfn <- "SpatialData/uintaN_elevm.img"
# Elevation (m)

37. Sample Dataset # Forest/Nonforest map SpatialPixels
fnffn <- "SpatialData/uintaN_fnf.img"

38. SpatialPixels - Importing/Exporting
Sample Dataset
SpatialPixels - Importing/Exporting
## Importing SpatialPixels (raster) files
help(raster)
elev <- raster("SpatialData/uintaN_elevm.img")
elev
dim(elev)
class(elev)
## Importing a raster stack
help(stack)
rstack <- stack("SpatialData/uintaN_elevm.img", "SpatialData/uintaN_fnf.img")
rstack
dim(rstack)
class(rstack)
## Exporting a raster
help(writeRaster)
writeRaster(rstack, filename="Outfolder/rstack1.img")
# Add integer datatype and notice size of file
writeRaster(rstack, filename="Outfolder/rstack2.img", datatype="INT1U",
overwrite=TRUE)

39. SpatialPixels - Spatial Info
Sample Dataset
SpatialPixels - Spatial Info
## Get spatial information for elev
elev
class(elev)
inMemory(elev) # Checks if raster is stored in memory (RAM)
unique(elev) # Get unique values of raster
extent(elev) # Get extent of raster
boxplot(elev) # Display boxplot of raster values
dim(elev) # Get dimensions of raster
res(elev) # Get the resolution of raster (x y)
ncell(elev) # Number of cells of raster
maxValue(elev) # Get Maximum value in raster
freq(elev) # Get frequency table of raster
## Overview of functions in raster package

40. Sample Dataset SpatialPixels - slots
## Get slot names for class SpatialPixels
getClass("SpatialPixels")
slotNames(elev)
str(elev)
the source (file name) of raster
list of attributes of raster
the legend features of raster, if exist
the title of raster, if exists
the bounding box of raster
number of columns of raster
number of rows of raster
coordinate reference system slot
## Get slot names for class SpatialPixels slots

41. SpatialPixels - Displaying
Sample Dataset
SpatialPixels - Displaying
## Display rasters
plot(elev)
# Display with terrain colors – 4 classes
plot(elev, col=terrain.colors(n=4))
# Display with terrain colors – 20 classes
plot(elev, col=terrain.colors(n=20))
# Exclude axis labels
plot(elev, col=terrain.colors(n=4), axes=FALSE)
# Get help with other colors for continuous data
help(terrain.colors)
# Display elevation data with contours
contour(elev)

42. SpatialPixels - Deriving
Sample Dataset
SpatialPixels - Deriving
## Derive new rasters
# Generate slope and aspect and hillshade from elevation dataset
slp <- terrain(elev, opt=c('slope'), unit='radians')
asp <- terrain(elev, opt=c('aspect'), unit='radians')
hill <- hillShade(slope, asp) # Generate hillshade
# Display hillshade in grey scale
plot(hill, col=grey(0:100/100), legend=FALSE)
# Classify raster
elevcl <- cut(elev, breaks=5) # 5 classes
plot(elevcl) # Display classified raster
cols <- c("brown", "palegreen", "orange1", "dark green", "snow")
plot(elevcl, col=cols, breaks=c(0:5))
# Converts raster from meters to feet
elevft <- elev *
summary(elev)
summary(elevft)

43. Sample Dataset SpatialPixels - fnf
## Get spatial information for fnf (thematic raster)
fnf <- raster("SpatialData/uintaN_fnf.img")
unique(fnf) # Get unique values of raster
extent(fnf) # Get extent of raster
barplot(fnf) # Display barplot of raster values
## Display fnf
fnfvals <- sort(unique(fnf))
plot(fnf, breaks=fnfvals, col=c("green", "brown", "blue"), legend=TRUE)
## Overview of functions in raster package

44. Sample Dataset reclass raster ## Reclass raster layer to 2 categories
help(reclassify)
fromvect <- c(0,1,2,3)
tovect <- c(2,1,2,2)
rclmat <- matrix(c(fromvect, tovect), 4, 2)
fnfrcl <- reclassify(x=fnf, rclmat)
fnfrcl
unique(fnfrcl)
freq(fnfrcl)
## To save to file
help(writeRaster)
stratrcl <- reclassify(x=fnf, rclmat, datatype='INT2U', filename="SpatialData/uintaN_fnfrcl.img", overwrite=TRUE)
## Plot new reclassed raster
fnfrclvals <- c(0, unique(fnfrcl))
plot(fnfrcl, breaks=fnfrclvals, col=c("green","brown"), legend=TRUE)
barplot(fnfrcl)

45. Temporary Files ## Note:
Functions in raster package create temporary files if the values of an output
RasterLayer cannot be stored in memory (RAM). This can happen when no
filename is provided to a function an in functions where you cannot provide
a filename. Temporary files are automatically removed at the start of each session.
## During session:
showTmpFiles()
removeTmpFiles()
## You can change where the temporary folder is in the Rprofile.site file.
## (C:\Program Files\R\R-3.0.0\etc\Rprofile.site)
# Added
options(scipen=6)
options(rasterTmpDir='c:/Temp/')
rasterOptions()
rasterOptions(chunksize = 1e+04, maxmemory = 1e+06)

46. Sample Dataset ## Exercise 3 Exercise
## 3.1 Get the minimum value of elev
## 3.2 Display elev raster with heat colors and 10 classes
## 3.3 Generate slope (in degrees)
## 3.4 Classify the slope raster from 3.3 into 4 classes
## 3.5 Display the classified slope raster with unique colors. Use colors() to select color choices. Exclude axes labels.

47. Spatial Help Links # Summary of tools for Spatial data analysis
# Presentation – Introduction to representing spatial objects in R – Roger Bivand
# List of common projections
## Help for point graphics
## Overview of functions in raster package