Session 12 Code

Read in packages:

Code

library(sf)

Linking to GEOS 3.11.2, GDAL 3.8.2, PROJ 9.3.1; sf_use_s2() is TRUE

Code

library(terra)

terra 1.7.78

Code

library(spDataLarge)
library(tigris)

To enable caching of data, set `options(tigris_use_cache = TRUE)`
in your R script or .Rprofile.


Attaching package: 'tigris'

The following object is masked from 'package:terra':

    blocks

Code

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2

── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ tidyr::extract() masks terra::extract()
✖ dplyr::filter()  masks stats::filter()
✖ dplyr::lag()     masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

Changing resolution:

Code

r <- rast()
r

class       : SpatRaster 
dimensions  : 180, 360, 1  (nrow, ncol, nlyr)
resolution  : 1, 1  (x, y)
extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84)

Code

values(r) <- 1:ncell(r)
plot(r)

Code

ra <- aggregate(r, 20)
ra

class       : SpatRaster 
dimensions  : 9, 18, 1  (nrow, ncol, nlyr)
resolution  : 20, 20  (x, y)
extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84) 
source(s)   : memory
name        :   lyr.1 
min value   :  3430.5 
max value   : 61370.5

Code

# rarely used
rd <- disagg(r, 20)


|---------|---------|---------|---------|
=

Code

plot(rd)

Crop and Mask

Code

srtm = rast(system.file("raster/srtm.tif", package = "spDataLarge"))
zion = read_sf(system.file("vector/zion.gpkg", package = "spDataLarge"))
zion = st_transform(zion, crs(srtm))

crs(srtm) == crs(zion)

[1] TRUE

Code

srtm.crop <- crop(x=srtm, y=zion, snap="near")

Code

srtm.crop.msk <- crop(x=srtm, y=vect(zion), snap="near", mask=TRUE)
plot(srtm.crop.msk)

Code

srtm.msk <- mask(srtm.crop, vect(zion), updatevalue=-1000)
plot(srtm.msk)

Code

srtm.msk2 <- mask(srtm.crop, vect(zion), inverse=TRUE, updatevalue=-1000)

Extend

Code

zion.buff <-  zion %>% 
  st_buffer(., 10000)
srtm.ext <- extend(srtm, vect(zion.buff))
ext(srtm.ext)

SpatExtent : -113.343749879444, -112.74541654615, 37.0479167631968, 37.5979167631601 (xmin, xmax, ymin, ymax)

Code

plot(srtm.ext)
plot(st_geometry(zion.buff), add=TRUE)

Practice

Load data:

Code

id <- rast("/opt/data/data/rasterexample/Copy of CRPS_ID.tif")
or <- rast("/opt/data/data/rasterexample/Copy of CRPS_OR.tif")

Aggregate

Code

id_agg <- aggregate(id, fact = 30)


|---------|---------|---------|---------|
=========================================

Code

or_agg <- aggregate(or, fact = 30)

Check for alignment

Code

crs(id_agg) == crs(or_agg)

[1] TRUE

Code

origin(id_agg) == origin(or_agg)

[1] FALSE FALSE

Code

ext(id_agg) == ext(or_agg)

[1] FALSE

Align the origins

Both project and resample don’t give the intended results.

Code

id_proj <- project(id_agg, or_agg)

id_resamp <- resample(id_agg, or_agg)

par(mfrow = c(1,2))
plot(id_proj)
plot(id_resamp)

We need to extend, then resample. Resample is the faster choice because the CRS’s of the the two rasters already match.

Code

id_ext <- extend(id_agg, or_agg)
or_ext <- extend(or_agg, id_ext)

id_resamp <- resample(id_ext, or_ext)

Code

crs(id_resamp) == crs(or_ext)

[1] TRUE

Code

origin(id_resamp) == origin(or_ext)

[1] TRUE TRUE

Code

ext(id_resamp) == ext(or_ext)

[1] TRUE

Mosaic

Code

idor <- mosaic(id_resamp, or_ext)

Crops and Masks

Code

idor_counties <- counties(state = c("ID", "OR"))

Retrieving data for the year 2022


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Code

east_id <- idor_counties %>%
  filter(NAME %in% c("Teton", "Jefferson", "Madison"))
plot(st_geometry(east_id))

mask without crop leaves a lot of white space.

Code

east_id_proj <- st_transform(east_id, crs(idor))

east_id_fire <- mask(x = idor, mask = east_id_proj)

east_id_fire2 <- crop(idor, east_id_proj, mask=TRUE)

Read in packages:

Code

library(sf)
library(terra)
library(spDataLarge)
library(tigris)
library(tidyverse)

Changing resolution:

Code

r <- rast()
r

class       : SpatRaster 
dimensions  : 180, 360, 1  (nrow, ncol, nlyr)
resolution  : 1, 1  (x, y)
extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84)

Code

values(r) <- 1:ncell(r)
plot(r)

Code

ra <- aggregate(r, 20)
ra

class       : SpatRaster 
dimensions  : 9, 18, 1  (nrow, ncol, nlyr)
resolution  : 20, 20  (x, y)
extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (CRS84) (OGC:CRS84) 
source(s)   : memory
name        :   lyr.1 
min value   :  3430.5 
max value   : 61370.5

Code

# rarely used
rd <- disagg(r, 20)


|---------|---------|---------|---------|
=

Code

plot(rd)

Crop and Mask

Code

srtm = rast(system.file("raster/srtm.tif", package = "spDataLarge"))
zion = read_sf(system.file("vector/zion.gpkg", package = "spDataLarge"))
zion = st_transform(zion, crs(srtm))

crs(srtm) == crs(zion)

[1] TRUE

Code

srtm.crop <- crop(x=srtm, y=zion, snap="near")

Code

srtm.crop.msk <- crop(x=srtm, y=vect(zion), snap="near", mask=TRUE)
plot(srtm.crop.msk)

Code

srtm.msk <- mask(srtm.crop, vect(zion), updatevalue=-1000)
plot(srtm.msk)

Code

srtm.msk2 <- mask(srtm.crop, vect(zion), inverse=TRUE, updatevalue=-1000)

Extend

Code

zion.buff <-  zion %>% 
  st_buffer(., 10000)
srtm.ext <- extend(srtm, vect(zion.buff))
ext(srtm.ext)

SpatExtent : -113.343749879444, -112.74541654615, 37.0479167631968, 37.5979167631601 (xmin, xmax, ymin, ymax)

Code

plot(srtm.ext)
plot(st_geometry(zion.buff), add=TRUE)

Practice

Load data:

Code

id <- rast("/opt/data/data/rasterexample/Copy of CRPS_ID.tif")
or <- rast("/opt/data/data/rasterexample/Copy of CRPS_OR.tif")

Aggregate

Code

id_agg <- aggregate(id, fact = 30)


|---------|---------|---------|---------|
=========================================

Code

or_agg <- aggregate(or, fact = 30)

Check for alignment

Code

crs(id_agg) == crs(or_agg)

[1] TRUE

Code

origin(id_agg) == origin(or_agg)

[1] FALSE FALSE

Code

ext(id_agg) == ext(or_agg)

[1] FALSE

Align the origins

Both project and resample don’t give the intended results.

Code

id_proj <- project(id_agg, or_agg)

id_resamp <- resample(id_agg, or_agg)

par(mfrow = c(1,2))
plot(id_proj)
plot(id_resamp)

We need to extend, then resample. Resample is the faster choice because the CRS’s of the the two rasters already match.

Code

id_ext <- extend(id_agg, or_agg)
or_ext <- extend(or_agg, id_ext)

id_resamp <- resample(id_ext, or_ext)

Code

crs(id_resamp) == crs(or_ext)

[1] TRUE

Code

origin(id_resamp) == origin(or_ext)

[1] TRUE TRUE

Code

ext(id_resamp) == ext(or_ext)

[1] TRUE

Mosaic

Code

idor <- mosaic(id_resamp, or_ext)

Crops and Masks

Code

idor_counties <- counties(state = c("ID", "OR"))

Retrieving data for the year 2022

Code

east_id <- idor_counties %>%
  filter(NAME %in% c("Teton", "Jefferson", "Madison"))
plot(st_geometry(east_id))

mask without crop leaves a lot of white space.

Code

east_id_proj <- st_transform(east_id, crs(idor))

east_id_fire <- mask(x = idor, mask = east_id_proj)

east_id_fire2 <- crop(idor, east_id_proj, mask=TRUE)