jhamman

In [7]: import satsearch
In [8]: results = satsearch.Search.search(
   ...:     collection='landsat-8-l1',
   ...:     bbox=[43.16, -11.32, 43.54, -11.96],
   ...:     sort=['<datetime'], #earliest scene first
   ...:     property=["landsat:tier=T1"])
   ...:
In [9]: catalog = intake.open_stac_item_collection(results.items())
In [10]: catalog
<satstac.itemcollection.ItemCollection at 0x7f96efe16828>

jhamman

In [4]: tif = cat['Houston-East-20170831-103f-100d-0f4f-RGB']['thumbnail']
In [5]: tiff_da = tif.to_dask()
Out[5]: 
<xarray.DataArray (y: 552, x: 549, channel: 3)>
dask.array<xarray-<this-array>, shape=(552, 549, 3), dtype=uint8, chunksize=(552, 549, 3), chunktype=numpy.ndarray>
Coordinates:
  * y        (y) int64 0 1 2 3 4 5 6 7 8 ... 543 544 545 546 547 548 549 550 551
  * x        (x) int64 0 1 2 3 4 5 6 7 8 ... 540 541 542 543 544 545 546 547 548
  * channel  (channel) int64 0 1 2
In [6]: tiff_da.plot.imshow(rgb='channel')

jhamman

In [1]: import intake
In [2]: catalog = intake.open_stac_catalog(
   ...:     'https://storage.googleapis.com/pdd-stac/disasters/catalog.json',
   ...:     name='planet-disaster-data')
   ...:
In [3]: list(catalog)
Out[3]:
['20170831_172754_101c',
'2017831_195552_SS02',
'20170831_195425_SS02',

jhamman

store = zarr.RedisStore(port=args.port)
root = zarr.group(store=store, overwrite=True)
t = 0
while True:
    arr = root.zeros(f"{t}", shape=grid.shape, chunks=(25, 25))  # create a new array for this timestep
    arr[…] = grid # write data to zarr array
    
    t += 1  # increment the time counter
    time.sleep(update_interval)
    grid = update(grid, N)  # evolve the model one time step

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