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spatial resolution #104
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Hi @Sonicious, thanks for reporting.
Up to now, most users knew the spatial resolution in advance for their use case, especially when multiple data source are fused together. Unfortunately, we do not maintain a list of spatial default resolutions for the supported datasets. It may also not be obvious, e.g., as you know, Sentinel 2 has 10, 20, and 60m.
No, this is currently not supported. However, we see the need to let users choose whether they provide Would you be happy with a new, optional |
I absolutely agree. But the spatial resolution is to be given in parts of degrees, right?
That might be a solution. In this case it works according to the examples in Sentinel Hub. Al this is actually about data which was accessed today to Sentinel 5, TROPOMI. Here we experienced artifacts. According to https://docs.sentinel-hub.com/api/latest/data/sentinel-5p-l2/ the resolution is also not that clear. I will bring a minimal example tomorrow to show the behaviour. |
No. It must be provided in the units of the spatial CRS given by the
Ok! |
So here is an example which ran in DeepESDL Hub with kernel: from xcube.core.store import find_data_store_extensions
from xcube.core.store import get_data_store_params_schema
from xcube.core.store import new_data_store
import IPython.display
from IPython.display import JSON
import shapely.geometry
import os
import xarray as xr
import matplotlib.pyplot as plt
# setup datastore
store = new_data_store('sentinelhub',
client_id=os.environ["SH_CLIENT_ID"],
client_secret=os.environ["SH_CLIENT_SECRET"],
api_url='https://creodias.sentinel-hub.com',
num_retries=400)
store.describe_data('S5PL2')
# list IDs
# Question here: why there is no sentinel-5p-l2? according to https://docs.sentinel-hub.com/api/latest/data/sentinel-5p-l2/#data-type-identifier-sentinel-5p-l2
store.list_data_ids()
# Region of interest
bbox = [-70, -22, -40, -2]
# Plot the area of interest
IPython.display.GeoJSON(shapely.geometry.box(*bbox).__geo_interface__)
# Let's look for TROPOMI data
ds = store.open_data(
'S5PL2',
variable_names=['CO'],
bbox=bbox,
spatial_res=0.0025,
#upsampling='BICUBIC',
time_range=['2020-06-01', '2020-07-31'],
time_period='1D'
)
da = ds['CO'];
da.isel(time=10).plot.imshow()
Notebook as zip: |
Sorry @Sonicious, |
Ok. Thank you very much. Maybe most things will be resolved through a |
When accessing Sentinel 5 (not limited to Sentinel 5 though) data, it is often required to tell the API the exact spatial resolution. There are mapping issues when you access bigger aeas (like completely south america) and you type not the exact resolution.
This leads to two problems:
Anyway I know SH is not meant to access such big areas to extract such big datacubes. Still there shouldn't be errors, when doing so.
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