Python 3.8.5 : Get Sentinel-3 satellite data from Eutelsat.

The tutorial for today is about Eutelsat satellites.
I used Sentinel-3 with these features:

• Instrument: SLSTR;
• Mode: EO;
• Satellite: Sentinel-3

You need to install xarray and netcdf4 python packages:

[mythcat@desk TLauncher]$ pip install xarray
...
[mythcat@desk ~]$ pip install netcdf4

Defaulting to user installation because normal site-packages is not writeable
Collecting netcdf4
  Downloading netCDF4-1.5.4-cp38-cp38-manylinux1_x86_64.whl (4.3 MB)
     |████████████████████████████████| 4.3 MB 649 kB/s 
Collecting cftime
  Downloading cftime-1.2.1-cp38-cp38-manylinux1_x86_64.whl (271 kB)
     |████████████████████████████████| 271 kB 30.5 MB/s 
Requirement already satisfied: numpy>=1.9 in /usr/lib64/python3.8/site-packages (from netcdf4) (1.18.4)
Installing collected packages: cftime, netcdf4
Successfully installed cftime-1.2.1 netcdf4-1.5.4 

You need to get data from the official webpage.

After I download the nc file with all data I used this source code:

Python 3.8.5 (default, Aug 12 2020, 00:00:00) 
[GCC 10.2.1 20200723 (Red Hat 10.2.1-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import xarray as xr
>>> dir = '/home/mythcat/Downloads/'
>>> file_xr = xr.open_dataset(dir+'FRP_in.nc')
>>> file_xr
<xarray .dataset="">
Dimensions:                 (columns: 1500, fires: 23, rows: 2000)
Dimensions without coordinates: columns, fires, rows
Data variables:
    i                       (fires) int16 ...
    j                       (fires) int32 ...
    time                    (fires) datetime64[ns] ...
    latitude                (fires) float64 ...
    longitude               (fires) float64 ...
    FRP_MWIR                (fires) float64 ...
    FRP_uncertainty_MWIR    (fires) float64 ...
    transmittance_MWIR      (fires) float64 ...
    FRP_SWIR                (fires) float64 ...
    FRP_uncertainty_SWIR    (fires) float64 ...
    FLAG_SWIR_SAA           (fires) int16 ...
    transmittance_SWIR      (fires) float64 ...
    confidence              (fires) float64 ...
    classification          (fires) uint8 ...
    S7_Fire_pixel_radiance  (fires) float32 ...
    F1_Fire_pixel_radiance  (fires) float32 ...
    used_channel            (fires) uint8 ...
    Radiance_window         (fires) float32 ...
    Glint_angle             (fires) float64 ...
    IFOV_area               (fires) float64 ...
    TCWV                    (fires) float64 ...
    n_window                (fires) int16 ...
    n_water                 (fires) int16 ...
    n_cloud                 (fires) int16 ...
    n_SWIR_fire             (fires) float32 ...
    flags                   (rows, columns) uint32 ...
Attributes:
    title:                  SLSTR Level 2 Product, Fire Radiative Power measu...
    comment:                 
    netCDF_version:         4.2 of Jul  5 2012 17:07:43 $
    product_name:           S3B_SL_2_FRP____20200910T082906_20200910T083406_2...
    institution:            MAR
    source:                 IPF-SL-2-FRP 02.00
    history:                 
    references:             S3MPC ACR FRP 003 - i1r2 - SLSTR L2 Product Data ...
    contact:                ops@eumetsat.int
    creation_time:          2020-09-10T10:38:54Z
    resolution:             [ 1000 1000 ]
    absolute_orbit_number:  12385
    start_time:             2020-09-10T08:29:06.288252Z
    stop_time:              2020-09-10T08:34:06.277355Z
    track_offset:           998
    start_offset:           14032

Let's parse size by latitude and longitude:

>>> lat = file_xr['latitude']
>>> long = file_xr['longitude']
>>> lat , long 
(<xarray.DataArray 'latitude' (fires: 23)>
array([52.992509, 52.98967 , 48.447335, 44.00415 , 48.443263, 48.439204,
       48.438141, 48.434069, 48.430012, 48.430012, 43.99905 , 43.993966,
       43.996166, 43.991064, 43.991064, 43.985972, 43.986568, 43.981467,
       43.976379, 43.978613, 43.973495, 43.973495, 43.968419])
Dimensions without coordinates: fires
Attributes:
    long_name:      Latitude
    standard_name:  latitude
    units:          degrees_north
    valid_min:      -90.0
    valid_max:      90.0, 
array([38.424813, 38.441404, 29.594317, 26.774829, 29.607258, 29.620235,
       29.592402, 29.605285, 29.618236, 29.618236, 26.787083, 26.799272,
       26.77044 , 26.782656, 26.782656, 26.7949  , 26.769496, 26.781764,
       26.794036, 26.765122, 26.777358, 26.777358, 26.789596])
Dimensions without coordinates: fires
Attributes:
    long_name:      Longitude
    standard_name:  longitude
    units:          degrees_east
    valid_min:      -180.0
    valid_max:      180.0) 

Get FRP_SWIR and FRP_MWIR data from satelite:

>>> FRP_SWIR = file_xr['FRP_SWIR']
>>> FRP_SWIR 

array([-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
       -1., -1., -1., -1., -1., -1., -1., -1., -1.])
Dimensions without coordinates: fires
Attributes:
    long_name:  Fire radiative power computed from SWIR channel (S6)
    units:      MW 
>>> FRP_MWIR = file_xr['FRP_MWIR']
>>> FRP_MWIR

array([ 10.290943,  11.447042, 179.555982,  84.84376 ,  48.277547,   9.320155,
        17.840467,  38.242334,  18.615514,  18.611452,  14.36118 ,   4.440371,
         3.06999 ,   5.008403,   5.005609,   4.452938,   8.228399,   8.442025,
         5.631591,   3.531036,   3.509205,   3.507225,   2.876292])
Dimensions without coordinates: fires
Attributes:
    long_name:  Fire radiative power computed from MWIR channels (S7 and F1)
    units:      MW