xarray

Feature Request

Is your feature request related to a problem? Please describe.

Whenever I report a bug, I need to confirm what satpy version I am using. This is of course important, but it's also an extra step that could be semi-automated.

Describe the solution you'd like

I would like that debug_on() prints the relevant versions. When we report bugs, we anyway call `debu

https://earthenginepartners.appspot.com/science-2013-global-forest

This should be updated to use write_cog instead:

Basic analysis:

Change detection:

The docstring doesn't show it

Oops wrong tag.

Code Sample, a minimal, complete, and verifiable piece of code

from pyresample.boundary import Boundary
b = Boundary(my_lons, my_lats)
print(b.contour_poly.area())

Problem description

The above code doesn't fail if the provided lons/lats are 2D (not sure on 3D+), but the class and all functions/utilities underneath it assume 1D arrays. The end results are incor

Example for numerical weather prediction

to be added to initialised datasets

Data sources (to) implement(ed):

• GEFS https://www.ncei.noaa.gov/thredds/catalog/model-gefs-003/202008/20200831/catalog.html
• DWD https://opendata.dwd.de/weather/nwp/

relates to #600

Without thinking I put resampling="bilinear" and got an error when I called .compute()

Traceback (most recent call last):
  File "carajas.py", line 92, in <module>
    band_medianNP = band_median.compute()
  File "/home/ubuntu/anaconda3/envs/richard/lib/python3.8/site-packages/xarray/core/dataarray.py", line 899, in compute
    return new.load(**kwargs)
  File "/home/ubuntu/anaco

To do

• Climatological means of net primary productivity
• Sentinel-2 / Landsat example
• Integration with geemap
• Temporal smoothing (#31)

Complete

• Downloading MODIS imagery
• [Visualizing fire progressions from GOES-R hotspots](https://wxee.readthedocs.io/en/latest/

https://forum.image.sc/t/imsave-tifffile-imwrite-returns-tiff-files-of-wrong-shape-in-imagej-cellprofiler/65332/9?u=jacksonmaxfield

The dim_order parameter should be used as the parameter to aicsimageio.transforms.reshape_data with TCZYX as the return order (optional S)

Would be good to clean up these warnings

WARNING: [numpydoc] Validation warnings while processing docstring for 'cf_xarray.bounds_to_vertices':
  SS06: Summary should fit in a single line
  PR03: Wrong parameters order. Actual: ('bounds', 'bounds_dim', 'core_dims', 'order'). Documented: ('bounds', 'bounds_dim', 'order', 'core_dims')
  SA01: See Also section not found
  EX01: No examples 

Looping over the data_vars in fit/predict/transform/... should be done with parallel.

It's really impressive how much pyomeca has progressed! Have you ever considered including some form of simple 3D marker visualization?