3. stars tidyverse methods

This vignette shows how some of the tidyverse verbs can be used on stars objects.

The stars and tidyverse packages are loaded by

library(stars)
library(dplyr)

Methods now available for class stars are

methods(class = "stars")
##  [1] $<-               %in%              Math              Ops              
##  [5] [                 [<-               [[<-              adrop            
##  [9] aggregate         aperm             as.POSIXct        as.data.frame    
## [13] as.tbl_cube       as_tibble         c                 coerce           
## [17] contour           cut               dim               dimnames         
## [21] dimnames<-        drop_units        droplevels        expand_dimensions
## [25] filter            hist              image             initialize       
## [29] is.na             merge             mutate            plot             
## [33] prcomp            predict           print             pull             
## [37] rename            select            show              slice            
## [41] slotsFromS3       split             st_apply          st_area          
## [45] st_as_sf          st_as_sfc         st_as_stars       st_bbox          
## [49] st_coordinates    st_crop           st_crs            st_crs<-         
## [53] st_dimensions     st_dimensions<-   st_downsample     st_extract       
## [57] st_geometry       st_geotransform   st_geotransform<- st_interpolate_aw
## [61] st_intersects     st_join           st_mosaic         st_normalize     
## [65] st_redimension    st_rotate         st_sample         st_set_bbox      
## [69] st_transform      st_write          time              transmute        
## [73] write_stars      
## see '?methods' for accessing help and source code

We will work with a three-band section of a landsat image:

system.file("tif/L7_ETMs.tif", package = "stars") %>%
    read_stars -> x
x
## stars object with 3 dimensions and 1 attribute
## attribute(s):
##              Min. 1st Qu. Median     Mean 3rd Qu. Max.
## L7_ETMs.tif     1      54     69 68.91242      86  255
## dimension(s):
##      from  to  offset delta                     refsys point x/y
## x       1 349  288776  28.5 SIRGAS 2000 / UTM zone 25S FALSE [x]
## y       1 352 9120761 -28.5 SIRGAS 2000 / UTM zone 25S FALSE [y]
## band    1   6      NA    NA                         NA    NA

slice

slice slices a sub-array out of the cube; this is done by specifying the dimension on which to act, and the slice number.

x %>% slice(band, 6) -> x6
x6
## stars object with 2 dimensions and 1 attribute
## attribute(s):
##              Min. 1st Qu. Median     Mean 3rd Qu. Max.
## L7_ETMs.tif     1      32     60 59.97521      88  255
## dimension(s):
##   from  to  offset delta                     refsys point x/y
## x    1 349  288776  28.5 SIRGAS 2000 / UTM zone 25S FALSE [x]
## y    1 352 9120761 -28.5 SIRGAS 2000 / UTM zone 25S FALSE [y]

It returns a lower-dimensional array if a single element is selected along the slice dimension.

filter

Similar to slice, filter selects on dimensions but evaluates their values rather than their index: in

x %>% filter(x > 289000, x < 291000, band > 3) -> x7
x7
## stars object with 3 dimensions and 1 attribute
## attribute(s):
##              Min. 1st Qu. Median     Mean 3rd Qu. Max.
## L7_ETMs.tif     5      54     70 71.79194      88  252
## dimension(s):
##      from  to  offset delta                     refsys point x/y
## x       1  70  289004  28.5 SIRGAS 2000 / UTM zone 25S FALSE [x]
## y       1 352 9120761 -28.5 SIRGAS 2000 / UTM zone 25S FALSE [y]
## band    1   3       4     1                         NA    NA

the subarray is created based on the x coordinate values.

Note that filter converts the object to a tbl_cube, and uses the dplyr filter method for tbl_cube objects. This has the limitation that stars objects with rectilinear, curvilinear or simple feature geometries cannot be handled. For such objects, using regular [ selection or using st_crop may be an alternative.

pull

pull pulls out an array from a stars object:

x %>% pull(1) -> x8
class(x8)
## [1] "array"
dim(x8)
##    x    y band 
##  349  352    6

mutate

x %>% mutate(band2 = 2 * L7_ETMs.tif) -> x2 
x2
## stars object with 3 dimensions and 2 attributes
## attribute(s):
##              Min. 1st Qu. Median      Mean 3rd Qu. Max.
## L7_ETMs.tif     1      54     69  68.91242      86  255
## band2           2     108    138 137.82484     172  510
## dimension(s):
##      from  to  offset delta                     refsys point x/y
## x       1 349  288776  28.5 SIRGAS 2000 / UTM zone 25S FALSE [x]
## y       1 352 9120761 -28.5 SIRGAS 2000 / UTM zone 25S FALSE [y]
## band    1   6      NA    NA                         NA    NA

select

select selects an attribute, or a set of attributes:

x2 %>% select(band2) -> x9
x9
## stars object with 3 dimensions and 1 attribute
## attribute(s):
##        Min. 1st Qu. Median     Mean 3rd Qu. Max.
## band2     2     108    138 137.8248     172  510
## dimension(s):
##      from  to  offset delta                     refsys point x/y
## x       1 349  288776  28.5 SIRGAS 2000 / UTM zone 25S FALSE [x]
## y       1 352 9120761 -28.5 SIRGAS 2000 / UTM zone 25S FALSE [y]
## band    1   6      NA    NA                         NA    NA

geom_stars

geom_raster is a ggplot2 geom function that accepts stars objects as its data argument and

  • sets up the raster or vector spatial coordinates as plot dimensions, and the first attribute as the fill variable
  • allows for downsampling (without choosing a suitable downsampling level)
  • chooses between using geom_raster, geom_rect and geom_sf depending on whether the geometry is regular, rectilinear or has vector geometries

An example use is

library(ggplot2)
library(viridis)
ggplot() + 
  geom_stars(data = x) +
  coord_equal() +
  facet_wrap(~band) +
  theme_void() +
  scale_fill_viridis() +
  scale_x_discrete(expand = c(0, 0)) +
  scale_y_discrete(expand = c(0, 0))