MODIS Satpy scene Don't know how to open the following files: {'MOD021KM.A2017131.1325.061.2017314123114.hdf'}

[SamothKoc]

Describe the bug Hi,... A want to plot Modis of one overfly during one day and get the following error: Scene(filenames = [file_nam], reader="modis_l1b") Don't know how to open the following files: {'/home/MODIS_DATA/MOD021KM.A2017131.1325.061.2017314123114.hdf'}

import glob
import numpy as np
import os

import matplotlib.pyplot as plt
import matplotlib.colors
from matplotlib.axes import Axes

import satpy
from satpy.scene import Scene
from satpy import find_files_and_readers
import pyresample as prs

import cartopy.crs as ccrs
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
from cartopy.mpl.geoaxes import GeoAxes
GeoAxes._pcolormesh_patched = Axes.pcolormesh

import warnings
warnings.filterwarnings('ignore')
warnings.simplefilter(action = "ignore", category = RuntimeWarning)

print('Import loaded.')
##########
extend= (-19, 5, 18, 38)
modis_folder = '/home/MODIS_DATA'
save_folder = '/home/MODIS_DATA'

print('Start Plotting,... whatever.')
file_pattern = os.path.join(modis_folder, '*.hdf')
file_name = glob.glob(file_pattern)
file_name

ii=0
for file_nam in file_name:
    print('filenr: ', ii)
    print('Name of file: ',file_nam)
    try:
        scn = Scene(filenames = [file_nam],:sreader="modis_l1b")
        if ii ==0:
            scn
            scn.available_dataset_names()
            scn.available_composite_ids()
            composite_id = ['natural_color']
            scn.load(composite_id, upper_right_corner="NE")
        scn_cropped = scn.crop(ll_bbox=extend)
        #cn_cropped.show("natural_color")
        scn_cropped['natural_color'].attrs['area']
        area = scn_cropped['natural_color'].attrs['area']
        scn_resample_nc = scn.resample(area)
        #cn_resample_nc.show('natural_color')

Actual results In [57]: Scene(filenames = [file_nam], reader="modis_l1b") Don't know how to open the following files: {'/home/MODIS_DATA/MOD021KM.A2017131.1325.061.2017314123114.hdf'}

ValueError Traceback (most recent call last) Cell In[57], line 1 ----> 1 Scene(filenames = [file_nam], reader="modis_l1b")

File /shared/apps/gcc-11.4.0/miniconda/3.11/envs/satpy_env/lib/python3.8/site-packages/satpy/scene.py:133, in Scene.init(self, filenames, reader, filter_parameters, reader_kwargs) 130 if filenames: 131 filenames = convert_remote_files_to_fsspec(filenames, storage_options) --> 133 self._readers = self._create_reader_instances(filenames=filenames, 134 reader=reader, 135 reader_kwargs=cleaned_reader_kwargs) 136 self._datasets = DatasetDict() 137 self._wishlist = set()

File /shared/apps/gcc-11.4.0/miniconda/3.11/envs/satpy_env/lib/python3.8/site-packages/satpy/scene.py:154, in Scene._create_reader_instances(self, filenames, reader, reader_kwargs) 149 def _create_reader_instances(self, 150 filenames=None, 151 reader=None, 152 reader_kwargs=None): 153 """Find readers and return their instances.""" --> 154 return load_readers(filenames=filenames, 155 reader=reader, 156 reader_kwargs=reader_kwargs)

File /shared/apps/gcc-11.4.0/miniconda/3.11/envs/satpy_env/lib/python3.8/site-packages/satpy/readers/init.py:584, in load_readers(filenames, reader, reader_kwargs) 581 break 583 _check_remaining_files(remaining_filenames) --> 584 _check_reader_instances(reader_instances) 585 return reader_instances

File /shared/apps/gcc-11.4.0/miniconda/3.11/envs/satpy_env/lib/python3.8/site-packages/satpy/readers/init.py:623, in _check_reader_instances(reader_instances) 621 def _check_reader_instances(reader_instances): 622 if not reader_instances: --> 623 raise ValueError("No supported files found") 624 if not any(list(r.available_dataset_ids) for r in reader_instances.values()): 625 raise ValueError("No dataset could be loaded. Either missing " 626 "requirements (such as Epilog, Prolog) or none of the " 627 "provided files match the filter parameters.")

ValueError: No supported files found

In [58]: filenames

NameError Traceback (most recent call last) Cell In[58], line 1 ----> 1 filenames

NameError: name 'filenames' is not defined

In [59]: Scene(filenames = [file_nam],reader="modis_l1b") Don't know how to open the following files: {'/home/MODIS_DATA/MOD021KM.A2017131.1325.061.2017314123114.hdf'}

ValueError Traceback (most recent call last) Cell In[59], line 1 ----> 1 Scene(filenames = [file_nam],reader="modis_l1b")

File /shared/apps/gcc-11.4.0/miniconda/3.11/envs/satpy_env/lib/python3.8/site-packages/satpy/scene.py:133, in Scene.init(self, filenames, reader, filter_parameters, reader_kwargs) 130 if filenames: 131 filenames = convert_remote_files_to_fsspec(filenames, storage_options) --> 133 self._readers = self._create_reader_instances(filenames=filenames, 134 reader=reader, 135 reader_kwargs=cleaned_reader_kwargs) 136 self._datasets = DatasetDict() 137 self._wishlist = set()

File /shared/apps/gcc-11.4.0/miniconda/3.11/envs/satpy_env/lib/python3.8/site-packages/satpy/scene.py:154, in Scene._create_reader_instances(self, filenames, reader, reader_kwargs) 149 def _create_reader_instances(self, 150 filenames=None, 151 reader=None, 152 reader_kwargs=None): 153 """Find readers and return their instances.""" --> 154 return load_readers(filenames=filenames, 155 reader=reader, 156 reader_kwargs=reader_kwargs)

File /shared/apps/gcc-11.4.0/miniconda/3.11/envs/satpy_env/lib/python3.8/site-packages/satpy/readers/init.py:584, in load_readers(filenames, reader, reader_kwargs) 581 break 583 _check_remaining_files(remaining_filenames) --> 584 _check_reader_instances(reader_instances) 585 return reader_instances

File /shared/apps/gcc-11.4.0/miniconda/3.11/envs/satpy_env/lib/python3.8/site-packages/satpy/readers/init.py:623, in _check_reader_instances(reader_instances) 621 def _check_reader_instances(reader_instances): 622 if not reader_instances: --> 623 raise ValueError("No supported files found") 624 if not any(list(r.available_dataset_ids) for r in reader_instances.values()): 625 raise ValueError("No dataset could be loaded. Either missing " 626 "requirements (such as Epilog, Prolog) or none of the " 627 "provided files match the filter parameters.")

[simonrp84]

What happens if you change: scn = Scene(filenames = [file_nam],:sreader="modis_l1b") to: scn = Scene([file_nam],reader="modis_l1b")

Also note that you have a rogue :s in the above command. If this still doesn't work, can you check that you have the conda HDF libraries installed (pyhdf from memory).

[SamothKoc]

I downloaded the MODIS files with wget over Laads... so the first option I already checkt (corruped file) should be the problem...

Then I get: TypeError: init() got an unexpected keyword argument 'sreader'

[djhoese]

@SamothKoc That's still a typo. It should be reader not sreader.

[SamothKoc]

Finally it works :D the key problem was a missing library ... the debugger is great

Edit: Is there a (easy) way with satpy to combine multiple MODIS dataset? I want to plot the complete Track during one day over my region.

Edit 2: I tried this:

def extract_date(file_name):
    match = re.search(r"\.A(\d{7})\.", file_name)
    return match.group(1) if match else None

def group_files_by_date(file_paths):
    """
    Gruppiert eine Liste von Dateipfaden nach dem Datum in den Dateinamen.
    :param file_paths: Eine Liste von Dateipfaden.
    :return: Ein Dictionary, in dem die Schlüssel Datumsangaben sind und die Werte Listen der Dateipfade sind.
    """
    grouped_files = defaultdict(list)
    for file_path in file_paths:
        date = extract_date(file_path)
        if date:
           grouped_files[date].append(file_path)
    return grouped_files

print('Start Plotting,... whatever.')
file_pattern = os.path.join(modis_folder, '*.hdf')
file_name = glob.glob(file_pattern)
file_name

grouped_files = group_files_by_date(file_name)
ii=0

for date, files in grouped_files.items():
    print(f"Verarbeite Dateien für Datum: {date}")
    scn = Scene(filenames=files, reader='modis_l1b')
    composite_id = ['natural_color']
    scn.load(composite_id, upper_right_corner="NE")

and then:

area_id = "mecator"
description = "Mercator projection"
proj_id = "mercator"
proj_dict = {"proj": "merc", "lon_0": 0}  # Längengrad des Satelliten
width = 2000  # Anzahl der Pixel in x-Richtung
height = 2000  # Anzahl der Pixel in y-Richtung
#area_extent = (-5570248.477339261, -5567248.074173444, 5567248.074173444, 5570248.477339261)
area_def = AreaDefinition(area_id, description, proj_id, proj_dict, width, height, extend)

# Resampeln der Daten auf das definierte Zielgebiet
scn_resample_nc = scn.resample(area_def)
image = get_enhanced_image(scn_resample_nc["natural_color"]).data.data.compute().transpose(1, 2, 0)
image.shape
crs = scn_resample_nc["natural_color"].attrs["area"].to_cartopy_crs()

# Initiatie a subplot and axes with the CRS information previously defined
fig = plt.figure(figsize=(16, 10))
ax = fig.add_subplot(1, 1, 1, projection=crs)
ax.set_facecolor('white')
# Add coastline features to the plot
ax.coastlines(resolution="10m", color="white")
# Define a grid to be added to the plot
gl = ax.gridlines(draw_labels=True, linestyle='--', xlocs=range(-20,20,5), ylocs=range(0,50,5))
gl.top_labels=False
gl.right_labels=False
gl.xformatter=LONGITUDE_FORMATTER
gl.yformatter=LATITUDE_FORMATTER
gl.xlabel_style={'size':14}
gl.ylabel_style={'size':14}
countries = cfeature.NaturalEarthFeature(
        category='cultural',
        name='admin_0_countries',
        scale='50m',
        facecolor='none',
        edgecolor='white'
        )
ax.add_feature(countries)

ax.imshow(image, transform=crs, extent=crs.bounds, origin="upper")
time_tit= scn['natural_color'].attrs["start_time"].strftime("%Y-%m-%d %H:%M")
plt.title("natural_colord by MODIS at " + time_tit, fontsize=20, pad=20.0)
datetime_str_modified = time_tit.replace(" ", "_")
datetime_str_modified = time_tit.replace(":", "_")
print('Saving time: ', datetime_str_modified)
plt.savefig(save_folder+'MODIS_truecolor_plot'+datetime_str_modified+'.png', dpi=300, bbox_inches='tight', transparent=True)

and get a complete grey image :D

[djhoese]

Passing multiple granules to the Scene object should merge them together just fine. Doing them per-orbit (or half-orbit or even smaller) would be a good idea just for processing times and avoiding resampling artifacts.

Does your code produce an expected image for a single set of files (a single granule)? An all grey image sounds like your input data does not overlap/cover your area that you are resampling to.

[SamothKoc]

Hi, it works with one image :D so i said ...

x_size = 3089
y_size = 3320
area_extent = (W, E, N, S)
projection = '+proj=laea +lat_0=37.5 +lon_0=-122.0 +ellps=WGS84'
description = "area"
proj_id = 'laea_37.5_-122.0'

areadef = get_area_def(area_id, description, proj_id, projection,x_size, y_size, area_extent)

but if i have a list of hdf... that isn't the way. because i have to do it manually

[mraspaud]

If you have multiple time steps, you should process them sequentially.

[SamothKoc]

and if i only know the name... so i can crop the coordinate? Currently I have a big ? in my brain :D

there is a coord2area_def.py but even then i need the coordinate befor.

[djhoese]

I'm a little lost now. What Martin said is true and is what I was trying to say. If you have multiple orbits (multiple separate passes of the satellite) then those should really be processed separately (separate Scene objects). If they are contiguous/connected granules then that is probably fine for a couple MODIS granules to pass all those files together...although now that I say that I'm not sure I've actually ever done that.

but if i have a list of hdf... that isn't the way. because i have to do it manually

and if i only know the name... so i can crop the coordinate?

Have to do what manually? Know the "name" of what?

[SamothKoc]

Done. :D it was easier the expected .

area_id = "Points_test"
 description = "Points and overall  in Mercator-Projektion"
proj_id = "Points_test"
proj_dict = {"proj": "merc", "lat_ts": 0, 'lon_0': 0}  # Passen Sie die Projektionsparameter an

width = 800    
height = 800

llx = -50E5   # westlich Längenkoordinate
lly = -0E5   # üdlich Breitenkoordinate
 urx =  18E5   # östliche Längenkoordinate
Import loury =  47E5   # nördliche Breitenkoordinate
tarea_extent = (llx, lly, urx, ury)
area_def_westafrika = geometry.AreaDefinition(area_id, proj_id, description, proj_dict, width, height, area_extent)

mscn = MultiScene(scenes)
mscn.load(['natural_color'],resolution=1000)
mscn_res = mscn.resample(area_def_Points_test)
blended_scene = mscn_res.blend()
blended_scene.show("natural_color")

[djhoese]

Glad you got something working.

[simonrp84]

Just for reference, Dave, I have often processed multiple contiguous modis granules, up to half an orbit, and it works fine.