I am currently struggling with rasterizing and later, resampling a vector object using functions from `stars` and `terra`. Let's start with the example dataset here: https://drive.google.com/drive/u/2/folders/1uDVQt1F64rUTfCXclwr-sM-oFjyJ2NwV This is a dataset of waterbodies and I load them first using `sf` ``` waterBodies_nil1870 <- st_read("data\spatial\waterBodies_nil1870.shp") waterBodies_nil1870 <- st_transform(waterBodies_nil1870, 32643) > waterBodies_nil1870 Simple feature collection with 5 features and 3 fields Geometry type: MULTIPOLYGON Dimension: XY Bounding box: xmin: 667536.9 ymin: 1240976 xmax: 704538.2 ymax: 1276926 Projected CRS: WGS 84 / UTM zone 43N id class gridcode geometry 1 1 waterbodies 1 MULTIPOLYGON (((683042.8 12... 2 2 waterbodies 1 MULTIPOLYGON (((669090.5 12... 3 3 waterbodies 1 MULTIPOLYGON (((675343.5 12... 4 4 waterbodies 1 MULTIPOLYGON (((702393.8 12... 5 5 waterbodies 1 MULTIPOLYGON (((688438.4 12... ``` Now I would like to rasterize this simple feature and resample it so that I further compute area statistics to compare with other rasters. To do so I have been struggling with using functions from both the `stars` and the `terra` package and each time, I believe I am losing values and data associated. Let's start with functions from the `stars` package: ``` > new <- st_rasterize(waterBodies_nil1870) > new stars object with 2 dimensions and 2 attributes attribute(s): Min. 1st Qu. Median Mean 3rd Qu. Max. NA's id 1 2 2 2.547945 3 5 64790 gridcode 1 1 1 1.000000 1 1 64790 dimension(s): from to offset delta refsys point values x/y x 1 259 667537 143.276 WGS 84 / UTM zone 43N FALSE NULL [x] y 1 251 1276926 -143.276 WGS 84 / UTM zone 43N FALSE NULL [y] ``` In the above scenario, I have now lost the `class` attribute column and only id and gridcode are preserved for some reason. Notice that this error continues to surface even if I do: `st_rasterize(waterBodies_nil1870["class"])`. Let's try functions from the `terra` package now: ``` v1 <- vect(waterBodies_nil1870) > v1 class : SpatVector geometry : polygons dimensions : 5, 3 (geometries, attributes) extent : 667536.9, 704538.2, 1240976, 1276926 (xmin, xmax, ymin, ymax) coord. ref. : WGS 84 / UTM zone 43N (EPSG:32643) names : id class gridcode type : <num> <chr> <num> values : 1 waterbodies 1 2 waterbodies 1 3 waterbodies 1 > r1 <- rast(v1) > r1 class : SpatRaster dimensions : 10, 10, 1 (nrow, ncol, nlyr) resolution : 3700.129, 3595.036 (x, y) extent : 667536.9, 704538.2, 1240976, 1276926 (xmin, xmax, ymin, ymax) coord. ref. : WGS 84 / UTM zone 43N (EPSG:32643) > hasValues(r1) [1] FALSE ``` Any suggestions/solutions to rasterize a simple features object and then resample it in R would be highly appreciated!