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] $<-               Math              Ops              
##  [4] [                 [<-               adrop            
##  [7] aggregate         aperm             as.data.frame    
## [10] as.tbl_cube       as_tibble         c                
## [13] coerce            contour           cut              
## [16] dim               dimnames          dimnames<-       
## [19] drop_units        filter            image            
## [22] initialize        is.na             merge            
## [25] mutate            plot              predict          
## [28] print             pull              select           
## [31] show              slice             slotsFromS3      
## [34] split             st_apply          st_area          
## [37] st_as_sf          st_as_sfc         st_as_stars      
## [40] st_bbox           st_coordinates    st_crop          
## [43] st_crs            st_crs<-          st_dimensions    
## [46] st_geometry       st_interpolate_aw st_intersects    
## [49] st_join           st_normalize      st_redimension   
## [52] st_transform      st_transform_proj 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):
##   L7_ETMs.tif    
##  Min.   :  1.00  
##  1st Qu.: 54.00  
##  Median : 69.00  
##  Mean   : 68.91  
##  3rd Qu.: 86.00  
##  Max.   :255.00  
## dimension(s):
##      from  to  offset delta                       refsys point values    
## x       1 349  288776  28.5 +proj=utm +zone=25 +south... FALSE   NULL [x]
## y       1 352 9120761 -28.5 +proj=utm +zone=25 +south... FALSE   NULL [y]
## band    1   6      NA    NA                           NA    NA   NULL

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):
##   L7_ETMs.tif    
##  Min.   :  1.00  
##  1st Qu.: 32.00  
##  Median : 60.00  
##  Mean   : 59.98  
##  3rd Qu.: 88.00  
##  Max.   :255.00  
## dimension(s):
##   from  to  offset delta                       refsys point values    
## x    1 349  288776  28.5 +proj=utm +zone=25 +south... FALSE   NULL [x]
## y    1 352 9120761 -28.5 +proj=utm +zone=25 +south... FALSE   NULL [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):
##   L7_ETMs.tif    
##  Min.   :  5.00  
##  1st Qu.: 54.00  
##  Median : 70.00  
##  Mean   : 71.79  
##  3rd Qu.: 88.00  
##  Max.   :252.00  
## dimension(s):
##      from  to  offset delta                       refsys point values    
## x       1  70  289004  28.5 +proj=utm +zone=25 +south... FALSE   NULL [x]
## y       1 352 9120761 -28.5 +proj=utm +zone=25 +south... FALSE   NULL [y]
## band    1   3       4     1                           NA    NA   NULL

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):
##   L7_ETMs.tif         band2      
##  Min.   :  1.00   Min.   :  2.0  
##  1st Qu.: 54.00   1st Qu.:108.0  
##  Median : 69.00   Median :138.0  
##  Mean   : 68.91   Mean   :137.8  
##  3rd Qu.: 86.00   3rd Qu.:172.0  
##  Max.   :255.00   Max.   :510.0  
## dimension(s):
##      from  to  offset delta                       refsys point values    
## x       1 349  288776  28.5 +proj=utm +zone=25 +south... FALSE   NULL [x]
## y       1 352 9120761 -28.5 +proj=utm +zone=25 +south... FALSE   NULL [y]
## band    1   6      NA    NA                           NA    NA   NULL

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):
##      band2      
##  Min.   :  2.0  
##  1st Qu.:108.0  
##  Median :138.0  
##  Mean   :137.8  
##  3rd Qu.:172.0  
##  Max.   :510.0  
## dimension(s):
##      from  to  offset delta                       refsys point values    
## x       1 349  288776  28.5 +proj=utm +zone=25 +south... FALSE   NULL [x]
## y       1 352 9120761 -28.5 +proj=utm +zone=25 +south... FALSE   NULL [y]
## band    1   6      NA    NA                           NA    NA   NULL

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))