I am working with a large GridWorkFlow object; I am not able to load all the tiles due to in-memory compute resources (24.00 GB mem 8 CPU) and do not need to either. I am interested in intersecting the grid with a spatial boundary I have (GeoPandas GeoDataFrame object) and finding the indices of the tiles which intersect the shapes. Any advice on the best approach? I have a POC for converting the grid to GeoPandas object, but would like to know if it is possible without having to convert, and how I might do that?
from datacube import Datacube
from datacube.api import GridWorkflow
from datacube.model import GridSpec
from datacube.utils import geometry
size = (1024*30)
tiles_per_cluster=1
gs = GridSpec(crs=geometry.CRS(102003), tile_size=(size, size), resolution=(15,15))
dc = Datacube(app="my_app")
gw = GridWorkflow(dc.index, grid_spec=gs)
gw.list_tiles(product="landsat7") # breaks memory limits
If I index a particular tile, I am able to intersect it with tile_obj.geobox.extent.intersects(geom_obj) but I need to be able to do this with all tiles without breaking memory limits.
***EDIT:
small_geom = geometry.Geometry(my_polygon, crs=102003)
gw.list_cells(product='landsat7', geopolygon=small_geom)
was the final solution I needed. I did not know the kwarg here was "geopolygon" and that it would do the intersect I hoped for.
