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Raster Display

Source: vignettes/articles/raster-display.Rmd
raster-display.Rmd

plot_raster() displays data using base R graphics. The function will read from an open dataset, or use pixel values that have already been read into a vector.

library(gdalraster)
#> GDAL 3.4.1, released 2021/12/27, GEOS 3.10.2, PROJ 8.2.1

base_url <- "/vsicurl/https://raw.githubusercontent.com/usdaforestservice/gdalraster/main/sample-data/"

Single-band grayscale or color ramp 

f <- paste0(base_url, "lf_elev_220_mt_hood_utm.tif")
ds <- new(GDALRaster, f)

# gray
plot_raster(ds, legend=TRUE, main="Mount Hood elevation (m)")

A plot of an elevation raster for an area of interest around Mt. Hood, Oregon, USA. Elevation is shown in grayscale with the lowest values dark gray (minimum 553 m) and the highest values almost white (maximum 3421 m).

elev_pal <- c("#00A60E","#63C600","#E6E600","#E9BD3B","#ECB176","#EFC2B3","#F2F2F2")
ramp <- scales::colour_ramp(elev_pal, alpha=FALSE)

plot_raster(ds, legend=TRUE, col_map_fn=ramp, main="Mount Hood elevation (m)")

A plot of an elevation raster for an area of interest around Mt. Hood, Oregon, USA. A terrain color ramp is used with the lowest values green (minimum 553 m), intermediate values yellow to orange, and the highest values almost white (maximum 3421 m).

ds$close()

RGB 

f <- paste0(base_url, "landsat_c2ard_sr_mt_hood_jul2022_utm.tif")
ds <- new(GDALRaster, f)

# passing a vector of pixel values rather than the open dataset
r <- read_ds(ds, bands=c(7,5,4))
ds$close()

# normalizing to ranges derived from the full Landsat scene (2-98 percentiles)
plot_raster(r,
            minmax_def=c(7551,7679,7585,14842,24997,12451),
            main="Mount Hood July 2022 Landsat 7-5-4 (SWIR)"
           )

A plot of a Landsat image for an area of interest around Mt. Hood, Oregon, USA. The image is from July 2022. It is shown as a false color composite of Landsat bands 7, 5 and 4 (SWIR).

Color table 

f <- paste0(base_url, "lf_fbfm40_220_mt_hood_utm.tif")
ds <- new(GDALRaster, f)
dm <- ds$dim()
print(paste("Size is", dm[1], "x",  dm[2], "x", dm[3]))
#> [1] "Size is 1013 x 799 x 1"

# using the CSV attribute table distributed by LANDFIRE
fbfm_csv <- system.file("extdata/LF20_F40_220.csv", package="gdalraster")
vat <- read.csv(fbfm_csv)
head(vat)
#>   VALUE FBFM40   R   G   B      RED    GREEN     BLUE
#> 1    91    NB1 104 104 104 0.407843 0.407843 0.407843
#> 2    92    NB2 225 225 225 0.882353 0.882353 0.882353
#> 3    93    NB3 255 237 237 1.000000 0.929412 0.929412
#> 4    98    NB8   0  14 214 0.000000 0.054902 0.839216
#> 5    99    NB9  77 110 112 0.301961 0.431373 0.439216
#> 6   101    GR1 255 235 190 1.000000 0.921569 0.745098
vat <- vat[,c(1,6:8)]

# read at reduced resolution for display
plot_raster(ds, xsize=dm[1] / 2, ysize=dm[2] / 2,
            col_tbl=vat, interpolate=FALSE,
            main="LANDFIRE surface fuel class (FBFM40)")

A plot of LANDFIRE surface fuel classes for an area of interest around Mt. Hood, Oregon, USA.

ds$close()

Axis labels 

f <- paste0(base_url, "bl_mrbl_ng_jul2004_rgb_720x360.tif")
ds <- new(GDALRaster, f)
srs_is_projected(ds$getProjectionRef())
#> [1] FALSE
r <- read_ds(ds)
ds$close()

plot_raster(r,
            xlab="longitude", ylab="latitude",
            main="NASA Earth Observatory Blue Marble July 2004"
           )

A plot of the NASA Earth Observatory Blue Marble image from July 2004. NASA's Blue Marble: Next Generation images show Earth in true color. The images show how the surface would look to a human in space if our world had no clouds and no atmosphere. NASA's Terra satellite collected these images. There is one Blue Marble image for each month of the year 2004.