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A tibble including the color map of 4 gradient palettes. All the palettes includes also a definition of colors limits in terms of elevation (meters), that can be used with ggplot2::scale_fill_gradientn().

Format

A tibble of 41 rows and 6 columns. with the following fields:

pal

Name of the palette.

limit

Recommended elevation limit (in meters) for each color.

r

Value of the red channel (RGB color mode).

g

Value of the green channel (RGB color mode).

b

Value of the blue channel (RGB color mode).

hex

Hex code of the color.

Source

Derived from:

  • Patterson, T., & Jenny, B. (2011). The Development and Rationale of Cross-blended Hypsometric Tints. Cartographic Perspectives, (69), 31 - 46. doi:10.14714/CP69.20 .

Details

From Patterson & Jenny (2011):

More recently, the role and design of hypsometric tints have come under scrutiny. One reason for this is the concern that people misread elevation colors as climate or vegetation information. Cross-blended hypsometric tints, introduced in 2009, are a partial solution to this problem. They use variable lowland colors customized to match the differing natural environments of world regions, which merge into one another.

Examples

# \donttest{

data("cross_blended_hypsometric_tints_db")

cross_blended_hypsometric_tints_db
#> # A tibble: 41 × 6
#>    pal   limit     r     g     b hex    
#>    <chr> <int> <int> <int> <int> <chr>  
#>  1 arid      0   160   152   141 #A0988D
#>  2 arid     50   170   160   150 #AAA096
#>  3 arid    200   180   170   158 #B4AA9E
#>  4 arid    600   202   190   174 #CABEAE
#>  5 arid   1000   212   201   180 #D4C9B4
#>  6 arid   2000   212   184   163 #D4B8A3
#>  7 arid   3000   212   193   179 #D4C1B3
#>  8 arid   4000   212   207   204 #D4CFCC
#>  9 arid   5000   220   220   220 #DCDCDC
#> 10 arid   6000   235   235   237 #EBEBED
#> # ℹ 31 more rows

# Select a palette
warm <- cross_blended_hypsometric_tints_db %>%
  filter(pal == "warm_humid")

f <- system.file("extdata/asia.tif", package = "tidyterra")
r <- terra::rast(f)

library(ggplot2)

p <- ggplot() +
  geom_spatraster(data = r) +
  labs(fill = "elevation")

p +
  scale_fill_gradientn(colors = warm$hex)


# Use with limits
p +
  scale_fill_gradientn(
    colors = warm$hex,
    values = scales::rescale(warm$limit),
    limit = range(warm$limit),
    na.value = "lightblue"
  )

# }