# filter_geom
Filter data cube pixels by a polygon
```{r include=FALSE}
library(gdalcubes)
```
## Description
Create a proxy data cube, which filters pixels by a spatial (multi)polygon For all pixels whose center is within the polygon, the original
## Usage
```r
filter_geom(cube, geom, srs = NULL)
```
## Arguments
| Argument | Description |
|:------------|:----------------------------------|
| cube | source data cube |
| geom | either a WKT string, or an sfc or sfg object (sf package) |
| srs | string identifier of the polygon's coordinate reference system understandable for GDAL |
## Details
The resulting data cube will not be cropped but pixels outside of the
polygon will be set to NAN.
If `geom` is provided as an sfc object with length > 1, geometries will
be combined with `sf::st_combine()` before.
The geometry is automatically transformed to the data cube's spatial reference
system if needed.
## Value
a proxy data cube object
## Note
This function returns a proxy object, i.e., it will not start any computations besides deriving the shape of the result.
## Examples
```{r}
# create image collection from example Landsat data only
# if not already done in other examples
if (!file.exists(file.path(tempdir(), "L8.db"))) {
L8_files <- list.files(system.file("L8NY18", package = "gdalcubes"),
".TIF", recursive = TRUE, full.names = TRUE)
create_image_collection(L8_files, "L8_L1TP", file.path(tempdir(), "L8.db"), quiet = TRUE)
}
L8.col = image_collection(file.path(tempdir(), "L8.db"))
v = cube_view(extent=list(left=388941.2, right=766552.4,
bottom=4345299, top=4744931, t0="2018-01", t1="2018-06"),
srs="EPSG:32618", nx = 497, ny=526, dt="P1M")
L8.cube = raster_cube(L8.col, v)
L8.cube = select_bands(L8.cube, c("B04", "B05"))
L8.ndvi = apply_pixel(L8.cube, "(B05-B04)/(B05+B04)", "NDVI")
WKT = gsub(pattern='\\n',replacement="",x =
"Polygon ((-74.3541 40.9254,
-73.9813 41.2467,
-73.9997 41.4400,
-74.5362 41.1795,
-74.6286 40.9137,
-74.3541 40.9254))")
L8.ndvi.filtered = filter_geom(L8.ndvi, WKT, "EPSG:4326")
L8.ndvi.filtered
plot(L8.ndvi.filtered)
```