satpy | Python package for earth-observing satellite data processing
kandi X-RAY | satpy Summary
kandi X-RAY | satpy Summary
Python package for earth-observing satellite data processing
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Top functions reviewed by kandi - BETA
- Convert NTL colors to RGB colors
- Create a colormap
- Merge colormaps
- Palettize an image
- Generate available datasets
- Determine if a file type matches the file type
- Read the header
- Get available channels
- Get tile properties
- Temporarily change debug mode
- Perform db normalization
- Get area definition
- Get a single dataset
- Load a list of datasets
- Reads a GRIB file
- Yield available datasets
- Performs a resampling
- Generate tile info
- Load a dataset
- Get a dataset
- Get the satellite coordinates from the data array
- Save a dataset
- Read a netCDF file
- Get a dataset
- Perform normalization of db
- Compute the heatmap
satpy Key Features
satpy Examples and Code Snippets
Lines of Code : 5License : Strong Copyleft (CC BY-SA 4.0)
Copyscn = Scene()
scn["C13"] = resampled_goes17_scene["C13"]
... and so on for the other sensors ...
scn.load(["custom_composite"])
from pyresample import create_area_def
area_def = create_area_def("my_area_def", "+proj=eqc +datum=WGS84", resolution=2000)
from satpy import Scene
from glob import glob
from pyresample import create_area_def
arescn = Scene(filenames=files, reader='ahi_hsd',filter_parameters={'start_time': datetime(2021,5,25,2,00), 'end_time': datetime(2021,5,25,2,10)})
files = glob.glob(r'D:\ftp_h8_hsd_25Jul\*.dat')
area = scn['VIS006'].attrs['area']
col_idx, row_idx = area.get_xy_from_lonlat(lons, lats)
scn['VIS006'].values[row_idx, col_idx]
from satpy import Scene
from pyresample import create_area_def
# analyze filenames and what is in them
scn = Scene(reader='abi_l1b', filenames=abi_filenames)
# load a specific band
scn.load(['C07'])
# create a custom area that fits the Community Discussions
Trending Discussions on satpy
QUESTION
one maybe silly question. I want to load MODIS hdf data with python. The datasets are available at Earthdata. First of all a generated a list of data, which match the datestemp.
...ANSWER
Answered 2022-Apr-11 at 14:31I'll repeat my comment here so this question can be considered resolved (you'll need to select this as the accepted answer).
The error message you are getting is coming from the underlying pyhdf library and not Satpy. This suggests your HDF4 file is corrupt in some way or maybe not actually an HDF4 file. You could try running ncdump -h your_file.hdf on the command line and if it succeeds then that suggests the file is NOT corrupt.
As you commented, it seems the files from Earthdata are corrupt in some way. The same files from LAADS are fine. If you're up for it, I would recommend contacting the Earthdata group about the issues you've discovered.
QUESTION
I want to generate global weather satellite image using GOES17, EUMETSAT, and GK-2A. I want make it Plate carree coordinate. (GOES 17 netcdf file convert to Plate Carree)
First, using Satpy, I made plate carree image.
...ANSWER
Answered 2022-Feb-22 at 15:24There are some ways to do this inside Satpy, but typically people have specific ways they want the data joined together. That is a question you'll have to answer before you choose the code you want. First though you need to make a Scene for each separate satellite image you want in the final image and resample them to the same grid. A DynamicAreaDefinition (as you're using now) is not good for this overall process as each resampled Scene would be on a different final area (based on the satellite data being resampled that "froze" the DynamicAreaDefinition).
Your options for merging:
- Satpy has a
BackgroundCompositorwhere you can put one image on top of another. There is some documentation for creating a custom composite where you could make a composite like this. A series of these composites could be chained together to get the overall global composite you are looking for. You can put all the datasets in the same Scene to make things easier:
QUESTION
Sample file can download from https://noaa-goes17.s3.amazonaws.com/ABI-L1b-RadF/2021/213/00/OR_ABI-L1b-RadF-M6C13_G17_s20212130000319_e20212130009396_c20212130009445.nc
I am trying to convert a projection to a plate carree.
I loaded netcdf using Satpy.
...ANSWER
Answered 2022-Feb-22 at 12:23That documentation could definitely be improved (I'm not complaining, I'm one of the authors). For one, it should point to this documentation from pyresample on how to make a custom AreaDefinition:
https://pyresample.readthedocs.io/en/latest/geometry_utils.html
For your case of wanting to resampling to a plate carree (equirectangular) projection, you could try something like this:
QUESTION
When I use satpy to read Himawari-8 standard datas, the terminal always says " 'filenames' was provided but is empty. "
The Himawari-8 has 16 observation bands, and it take one full disk picture every 10 minutes so for one folder of observation result which contains 16 folders(one folder is one band), and each band is separated into 10 parts so in one band folder it has 10 files.
The format of Himawari-8 standard data is .dat, and the data named as
HS_aaa_yyyymmdd_hhnn_Bbb_cccc_Rjj_Skkll.DAT.
ANSWER
Answered 2022-Jan-14 at 03:47The error message means that you are passing an empty list to the Scene object. So in this line of code (you can see it in the error traceback):
QUESTION
I have a satellite image file. Loaded into dask array. I want to get pixel value (nearest) of a latitude, longitude of interest.
Satellite image is in GEOS projection. I have longitude and latitude information as 2D numpy arrays.
I have loaded it into a dask data array
...ANSWER
Answered 2021-Mar-02 at 07:17You can find the location with following:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install satpy
You can use satpy like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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