pyproj.exceptions.CRSError Due to Invalid EPSG:None Projection in MODIS-13Q1-061 Dataset

[simonMadec]

I am querying products from the modis-13Q1-061 collection using platform arguments and loading them with odc-stac into xarray.

However, when I try to load the data, I encounter the following error:

File "pyproj/_crs.pyx", line 2364, in pyproj._crs._CRS.__init__
pyproj.exceptions.CRSError: Invalid projection: EPSG:None: (Internal Proj Error: proj_create: crs not found: EPSG:None)

I noticed that MODIS items in the query results do not have a proper projection assigned. The proj:code property for items is set to "EPSG:None", which causes the error

mod_items[1].properties['proj:code'] is "EPSG:None"

Here is the code I am using, which fails when loading the data:

  catalog = pystac_client.Client.open(
      "https://planetarycomputer.microsoft.com/api/stac/v1",
      modifier=planetary_computer.sign_inplace,
  )
  ## Parametre
  time_range = f'{start_date}/{end_date}'
       
  image_select = "MOD" #filtre collection 

  ##search in catalog
  search = catalog.search(
  collections=["modis-13Q1-061"], bbox=bbox, datetime=time_range)
  items = search.get_all_items()

  ## Filter search
  mod_items = list(filter(lambda x: x.id.startswith(image_select), items))
  items = pystac.ItemCollection(mod_items)

  ### dl data
  items_dict = dict()
  for i in range(len(items)):
      items_dict[i] = items[i]

  data = odc.stac.load(
      items_dict.values(),
      crs="EPSG:3857",
      bbox=bbox,
      resolution=250, ## per pixel
      bands=["250m_16_days_NDVI"],#bande to select
      nodata=-3000) 

[ghidalgo3]

Hi @simonMadec, could you please share the output of pip freeze? I was able to run your example successfully like this:

import pystac # Gustavo added added this import

# Set the date time
start_date = "2023-01-01" 
end_date = "2024-01-01"
catalog = pystac_client.Client.open(
    "https://planetarycomputer.microsoft.com/api/stac/v1",
    modifier=planetary_computer.sign_inplace,
)
## Parametre
time_range = f'{start_date}/{end_date}'
    
image_select = "MOD" #filtre collection 

##search in catalog, bbox remained the same as in the example notebook.
search = catalog.search(
collections=["modis-13Q1-061"], bbox=bbox, datetime=time_range)
items = search.get_all_items()

## Filter search
mod_items = list(filter(lambda x: x.id.startswith(image_select), items))
items = pystac.ItemCollection(mod_items)

### dl data
items_dict = dict()
for i in range(len(items)):
    items_dict[i] = items[i]

data = odc.stac.load(
    items_dict.values(),
    crs="EPSG:3857",
    bbox=bbox,
    resolution=250, ## per pixel
    bands=["250m_16_days_NDVI"],#bande to select
    nodata=-3000) 

And this is my pip freeze output:

adlfs==2024.7.0
affine==2.4.0
aiohappyeyeballs==2.4.4
aiohttp==3.11.9
aiosignal==1.3.1
annotated-types==0.7.0
appnope @ file:///home/conda/feedstock_root/build_artifacts/appnope_1733332318622/work
asciitree==0.3.3
asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1733250440834/work
async-timeout==5.0.1
attrs==24.2.0
azure-core==1.32.0
azure-datalake-store==0.0.53
azure-identity==1.19.0
azure-storage-blob==12.24.0
cachetools==5.5.1
Cartopy==0.24.1
certifi==2024.8.30
cffi==1.17.1
cfgv==3.4.0
cftime==1.6.4.post1
charset-normalizer==3.4.0
click==8.1.7
click-plugins==1.1.1
cligj==0.7.2
cloudpickle==3.1.0
comm @ file:///home/conda/feedstock_root/build_artifacts/comm_1710320294760/work
contextily==1.6.2
contourpy==1.3.1
cryptography==44.0.0
cycler==0.12.1
dask==2024.12.0
debugpy @ file:///private/var/folders/k1/30mswbxs7r1g6zwn8y4fyt500000gp/T/abs_563_nwtkoc/croot/debugpy_1690905063850/work
decorator @ file:///home/conda/feedstock_root/build_artifacts/decorator_1733236420667/work
distlib==0.3.9
distributed==2024.12.0
exceptiongroup @ file:///home/conda/feedstock_root/build_artifacts/exceptiongroup_1733208806608/work
executing @ file:///home/conda/feedstock_root/build_artifacts/executing_1725214404607/work
fasteners==0.19
filelock==3.16.1
fonttools==4.55.2
frozenlist==1.5.0
fsspec==2024.10.0
geographiclib==2.0
geopy==2.4.1
h5netcdf==1.4.1
h5py==3.12.1
identify==2.6.3
idna==3.10
importlib_metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1733223117029/work
ipykernel @ file:///Users/runner/miniforge3/conda-bld/ipykernel_1719845458456/work
ipython @ file:///home/conda/feedstock_root/build_artifacts/ipython_1732896932739/work
isodate==0.7.2
jedi @ file:///home/conda/feedstock_root/build_artifacts/jedi_1733300866624/work
Jinja2==3.1.4
joblib==1.4.2
jsonschema==4.23.0
jsonschema-specifications==2024.10.1
jupyter_client @ file:///home/conda/feedstock_root/build_artifacts/jupyter_client_1726610684920/work
jupyter_core @ file:///home/conda/feedstock_root/build_artifacts/jupyter_core_1727163409502/work
kiwisolver==1.4.7
locket==1.0.0
markdown-it-py==3.0.0
MarkupSafe==3.0.2
matplotlib==3.9.3
matplotlib-inline @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-inline_1713250518406/work
mdurl==0.1.2
mercantile==1.2.1
msal==1.31.1
msal-extensions==1.2.0
msgpack==1.1.0
multidict==6.1.0
nest_asyncio @ file:///home/conda/feedstock_root/build_artifacts/nest-asyncio_1733325553580/work
netCDF4==1.7.2
nodeenv==1.9.1
numcodecs==0.13.1
numpy==2.1.3
odc-geo==0.4.9.post0
odc-stac==0.3.11
packaging @ file:///home/conda/feedstock_root/build_artifacts/packaging_1733203243479/work
pandas==2.2.3
parso @ file:///home/conda/feedstock_root/build_artifacts/parso_1733271261340/work
partd==1.4.2
pexpect @ file:///home/conda/feedstock_root/build_artifacts/pexpect_1733301927746/work
pickleshare @ file:///home/conda/feedstock_root/build_artifacts/pickleshare_1733327343728/work
pillow==11.0.0
planetary-computer==1.0.0
platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1733232627818/work
pooch==1.8.2
portalocker==2.10.1
pre_commit==4.0.1
prompt_toolkit @ file:///home/conda/feedstock_root/build_artifacts/prompt-toolkit_1733302527033/work
propcache==0.2.1
psutil @ file:///private/var/folders/nz/j6p8yfhx1mv_0grj5xl4650h0000gp/T/abs_1310b568-21f4-4cb0-b0e3-2f3d31e39728k9coaga5/croots/recipe/psutil_1656431280844/work
ptyprocess @ file:///home/conda/feedstock_root/build_artifacts/ptyprocess_1733302279685/work/dist/ptyprocess-0.7.0-py2.py3-none-any.whl#sha256=92c32ff62b5fd8cf325bec5ab90d7be3d2a8ca8c8a3813ff487a8d2002630d1f
pure_eval @ file:///home/conda/feedstock_root/build_artifacts/pure_eval_1721585709575/work
pycparser==2.22
pydantic==2.10.3
pydantic_core==2.27.1
Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1733221634316/work
PyJWT==2.10.1
pyparsing==3.2.0
pyproj==3.7.0
pyshp==2.3.1
pystac==1.11.0
pystac-client==0.8.5
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1733215673016/work
python-dotenv==1.0.1
pytz==2024.2
PyYAML==6.0.2
pyzmq @ file:///private/var/folders/k1/30mswbxs7r1g6zwn8y4fyt500000gp/T/abs_43pxpbos3z/croot/pyzmq_1705605108344/work
rasterio==1.4.3
referencing==0.35.1
requests==2.32.3
rich==13.9.4
rioxarray==0.18.1
rpds-py==0.22.3
scipy==1.14.1
shapely==2.0.6
six @ file:///home/conda/feedstock_root/build_artifacts/six_1733380938961/work
sortedcontainers==2.4.0
stack-data @ file:///home/conda/feedstock_root/build_artifacts/stack_data_1669632077133/work
tblib==3.0.0
toolz==1.0.0
tornado @ file:///private/var/folders/k1/30mswbxs7r1g6zwn8y4fyt500000gp/T/abs_a4w03z48br/croot/tornado_1718740114858/work
traitlets @ file:///home/conda/feedstock_root/build_artifacts/traitlets_1733367359838/work
typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1733188668063/work
tzdata==2024.2
urllib3==2.2.3
uv==0.5.6
virtualenv==20.28.0
wcwidth @ file:///home/conda/feedstock_root/build_artifacts/wcwidth_1733231326287/work
xarray==2024.11.0
xyzservices==2024.9.0
yarl==1.18.3
zarr==2.18.3
zict==3.0.0
zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1732827521216/work

None of the MODIS items have a proj:epsg property, so I think something about your environment is the culprit.

[simonMadec]

Yes, but I was using docker so ...
I will force the items to have the proj:espg on my code ..