First steps to create a datacube

To create a datacube using Earth Data Store from EarthDaily you have two possibilities.

The first one is the more classic one, you request items, then you build your datacube, and then you can mask pixels using a cloudmask asset. The second one is the most turnkey one, the one we recommend, it allows to do all the process at once.

Import librairies

from matplotlib import pyplot as plt

import earthdaily
from earthdaily import EarthDataStore, datasets

Loading geometry

geometry = datasets.load_pivot()

Init earthdatastore with environment variables or default credentials

eds = EarthDataStore()

Traceback (most recent call last):
  File "/private/var/folders/_t/czv_cfrd613_6_gd_p8qpqd80000gp/T/tmpmap_d3kq/7261d0bf6bc6b22a0278281791f6623d19ddf89a/examples/first_steps_create_datacube.py", line 30, in <module>
    eds = EarthDataStore()
          ^^^^^^^^^^^^^^^^
  File "/private/var/folders/_t/czv_cfrd613_6_gd_p8qpqd80000gp/T/tmpmap_d3kq/7261d0bf6bc6b22a0278281791f6623d19ddf89a/earthdaily/__init__.py", line 51, in EarthDataStore
    return earthdatastore.Auth.from_credentials(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/private/var/folders/_t/czv_cfrd613_6_gd_p8qpqd80000gp/T/tmpmap_d3kq/7261d0bf6bc6b22a0278281791f6623d19ddf89a/earthdaily/earthdatastore/__init__.py", line 464, in from_credentials
    config = cls.read_credentials(
             ^^^^^^^^^^^^^^^^^^^^^
  File "/private/var/folders/_t/czv_cfrd613_6_gd_p8qpqd80000gp/T/tmpmap_d3kq/7261d0bf6bc6b22a0278281791f6623d19ddf89a/earthdaily/earthdatastore/__init__.py", line 529, in read_credentials
    raise NotImplementedError("Credentials weren't found.")
NotImplementedError: Credentials weren't found.

Create datacube (in one step)

s2_datacube = eds.datacube(
    "sentinel-2-l2a",
    assets=["blue", "green", "red", "nir"],
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
    mask_with="native",  # equal to "scl" for sentinel-2
    clear_cover=50,
)

s2_datacube.clear_percent.plot.scatter(x="time")
plt.title("Percentage of clear pixels on the study site")
plt.show()

s2_datacube.ed.plot_rgb(vmin=0, vmax=0.2, col="time", col_wrap=4)

Create datacube in three steps

Request items

items = eds.search(
    "sentinel-2-l2a",
    intersects=geometry,
    datetime=["2022-08-01", "2022-08-09"],
)

Creata datacube (independent from being log into earthdatastore) We request the “scl” assets which is the native cloudmask

s2_datacube = earthdaily.earthdatastore.datacube(
    items, assets=["blue", "green", "red", "nir", "scl"], intersects=geometry
)

Mask datacube

# intersects or bbox are asked in order to compute accurate mask statistics

s2_datacube = earthdaily.earthdatastore.mask.Mask(s2_datacube, intersects=geometry).scl(
    mask_statistics=True
)

s2_datacube = earthdaily.earthdatastore.mask.filter_clear_cover(
    s2_datacube, 50
)  # at least 50% of clear pixels
#
s2_datacube.ed.plot_rgb(vmin=0, vmax=0.2, col="time", col_wrap=4)