Improving resolution when setting extent

[ustropics]

I am having an issue on exactly what would give me 'true' resolution of a geostationary data set (GOES in particular) while allowing for conversion to cartopy. I have provided minimal code to reproduce below, but what would give me the highest resolution when setting a more 'zoomed' in extent? Is this where I need to use native resampling or are there some attributes I'm missing?

area_def = create_area_def(
    'composite_area',  # Name of the area definition
    proj_dict,
    units='degrees',
    width=5240, 
    height=5240,
    area_extent=[lon_min, lat_min, lon_max, lat_max]
)

scn.load([recipe])
new_scn = scn.resample(area_def, resampler='nearest', cache_dir='cache/')

area = new_scn[recipe].attrs['area']
        
plt_scn = scn.resample(area)

image = get_enhanced_image(plt_scn[recipe]).data
crs = plt_scn[recipe].attrs['area'].to_cartopy_crs()

fig = plt.figure(figsize=(15,15))
ax = fig.add_subplot(1, 1, 1, projection=crs)

ax.add_feature(cfeature.COASTLINE, edgecolor=data['border_color_val'], linewidth=float(data['border_width_val']))
ax.add_feature(cfeature.BORDERS, edgecolor=data['border_color_val'], linewidth=float(data['border_width_val']))
ax.add_feature(cfeature.STATES, edgecolor=data['border_color_val'], linewidth=float(data['border_width_val']))
ax.gridlines(draw_labels=True, linewidth=0.5, color='gray', alpha=0.5, linestyle='--')

if len(plt_scn[recipe].shape) > 2:
    print("ax: ", ax)
    image.plot.imshow(vmin=0, vmax=1, add_colorbar=False, rgb='bands', ax=ax)
else:  # Single-band grayscale case
    image = np.squeeze(image)
    image.plot.imshow(vmin=0, vmax=1, add_colorbar=False, ax=ax)

plt.savefig(filename, dpi=300, bbox_inches='tight')
plt.close()

In this particular image below, I've set the extent for Florida (info below) and the recipe/composite to cimss_true_color_sunz_rayleigh:

  {
    "location": "Florida",
    "extent": [-87.634, -80.031, 24.396, 31.0],
    "satellite": "GOES-EAST (16)",
    "domain": "C",
    "projection": "Transverse Mercator",
    "central_longitude": -83.83250000000001,
    "central_latitude": 27.698,
    "standard_parallel": [24.396, 31.0]
  }

When cross-comparing this to products I've created in goes2go and to NESDIS satellite output, this appears to not match the resolution for the green/blue abi-bands (3 and 1). I'm confident this is just a lack of my understanding on how to sample properly or missing an attribute, but where am I going wrong?

My output image:

[djhoese]

Do you have an example image from those other tools? Or can you provide more details about what's signaling a lower resolution when you look at this image? I assume the size of your area is similar to the size of the images you're comparing against?

[guidocioni]

I'm replying because you use an approach that is quite similar to mine and I had this issue in the past.

1. Did you try to provide interpolation=none when calling imshow?
2. Also I think that you don't need to specify the area when resampling. You can just do

scn = satpy.Scene(**scene_inputs)
scn.load(['ash'], upper_right_corner='NE')
scn = scn.crop(ll_bbox=tuple(cust_area))
scn = scn.resample(resampler='native')

which should hopefully choose the highest possible resolution.