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Example to compute image cross spectrum between different looks within a WV Sentinel-1 SLC product

in WV images (20 km X 20 km) there is only one burst (thus no overlapping area).

[1]:
import xsar
import warnings
import logging
from importlib import reload
reload(logging)
logging.basicConfig(level=logging.INFO)
logging.info('go')
# warnings.simplefilter(action='ignore', category=FutureWarning)
warnings.filterwarnings("ignore")
#tmp = xsar.get_test_file('S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_Z010.SAFE')
tmp = xsar.get_test_file('S1A_WV_SLC__1SSV_20191005T100804_20191005T101314_029322_035533_0597.SAFE') # very small product
# print(tmp)
# tmp = '/home/datawork-cersat-public/cache/project/mpc-sentinel1/data/esa/sentinel-1a/L2/WV/S1A_WV_OCN__2S/2016/131/S1A_WV_OCN__2SSV_20160510T101603_20160510T102143_011195_010EA1_F972.SAFE'
# tmp = '/home/datawork-cersat-public/cache/project/mpc-sentinel1/data/esa/sentinel-1a/L1/WV/S1A_WV_SLC__1S/2016/131/S1A_WV_SLC__1SSV_20160510T101603_20160510T102143_011195_010EA1_7038.SAFE'
# tmp = '/home/datawork-cersat-public/cache/project/mpc-sentinel1/data/esa/sentinel-1a/L1/WV/S1A_WV_SLC__1S/2023/014/S1A_WV_SLC__1SSV_20230114T130811_20230114T133351_046780_059BC5_FED5.SAFE'

strwv = 'SENTINEL1_DS:'+tmp+':WV_017'
print(strwv)
xsar_instance = xsar.Sentinel1Dataset(strwv)
xsar_instance

INFO:root:go
SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsardata/S1A_WV_SLC__1SSV_20191005T100804_20191005T101314_029322_035533_0597.SAFE:WV_017
[1]:
<Sentinel1Dataset full coverage object>
[2]:
xsar_instance.dataset
[2]:
<xarray.Dataset>
Dimensions:         (line: 4923, sample: 5681, pol: 1)
Coordinates:
  * line            (line) int64 0 1 2 3 4 5 6 ... 4917 4918 4919 4920 4921 4922
  * sample          (sample) int64 0 1 2 3 4 5 ... 5675 5676 5677 5678 5679 5680
  * pol             (pol) object 'VV'
Data variables:
    digital_number  (pol, line, sample) complex64 dask.array<chunksize=(1, 4923, 5000), meta=np.ndarray>
    time            (line) datetime64[ns] 2019-10-05T10:11:58.450274048 ... 2...
    sampleSpacing   float64 1.498
    lineSpacing     float64 4.133
Attributes: (12/15)
    name:              SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync/xsar...
    short_name:        SENTINEL1_DS:S1A_WV_SLC__1SSV_20191005T100804_20191005...
    product:           SLC
    safe:              S1A_WV_SLC__1SSV_20191005T100804_20191005T101314_02932...
    swath:             WV
    multidataset:      False
    ...                ...
    start_date:        2019-10-05 10:11:58.450260
    stop_date:         2019-10-05 10:12:01.432986
    footprint:         POLYGON ((-61.07570128124852 28.34141558287481, -61.28...
    coverage:          20km * 20km (line * sample )
    orbit_pass:        Descending
    platform_heading:  -167.4153352100693
[3]:
xsar_instance.dataset.digital_number.values[0:10,0:10]
[3]:
array([[[   0.  +0.j,    0.  +0.j,    0.  +0.j, ...,    0.  +0.j,
            0.  +0.j,    0.  +0.j],
        [   0.  +0.j,    0.  +0.j,    0.  +0.j, ...,    0.  +0.j,
            0.  +0.j,    0.  +0.j],
        [   0.  +0.j,    0.  +0.j,    0.  +0.j, ...,   14. +15.j,
           64. -30.j,   43. -46.j],
        ...,
        [ -12.+243.j,  -69. -81.j,   13. -53.j, ...,   82. +53.j,
          190.  +4.j,  108.-126.j],
        [  87. -29.j, -120. -67.j,   83. +82.j, ...,  123.+140.j,
          232.  -8.j, -123.-134.j],
        [ -29. +21.j,  -34.  -6.j,  -44. +99.j, ...,  213. +40.j,
          325.+204.j,   99. -20.j]]], dtype=complex64)

display digital numbers

[4]:
import holoviews as hv
import numpy as np
from holoviews.operation.datashader import datashade,rasterize
hv.extension('bokeh')
[5]:
tmp = abs(xsar_instance.dataset['digital_number'].sel(pol='VV'))
DN = tmp.rolling({"sample":10,"line":10}).mean()
DN
[5]:
<xarray.DataArray 'digital_number' (line: 4923, sample: 5681)>
dask.array<truediv, shape=(4923, 5681), dtype=float32, chunksize=(4923, 5009), chunktype=numpy.ndarray>
Coordinates:
  * line     (line) int64 0 1 2 3 4 5 6 7 ... 4916 4917 4918 4919 4920 4921 4922
  * sample   (sample) int64 0 1 2 3 4 5 6 ... 5674 5675 5676 5677 5678 5679 5680
    pol      <U2 'VV'
Attributes:
    comment:  denoised digital number, read at full resolution
    history:  digital_number: measurement/s1a-wv1-slc-vv-20191005t101158-2019...
[6]:
rasterize(hv.Image(DN.values).opts(width=800,height=700,cmap='Greys',colorbar=True))# clim=(0,40)
[6]:

compute the periodograms and the looks inside the periodograms to get a cross spectra

[7]:
from xsarslc.processing.xspectra import compute_WV_intraburst_xspectra
import time
t0 = time.time()
xs0 = compute_WV_intraburst_xspectra(dt=xsar_instance.datatree,
                                          polarization='VV',periodo_width={"line":2000,"sample":2000},
                                          periodo_overlap={"line":1000,"sample":1000})
print('time to compute x-spectra on WV :%1.1f sec'%(time.time()-t0))
xs0
time to compute x-spectra on WV :236.2 sec
[7]:
<xarray.Dataset>
Dimensions:                   (bt_thresh: 5, 0tau: 3, freq_line: 97,
                               freq_sample: 274, 1tau: 2, 2tau: 1, c_sample: 2,
                               c_line: 2, k_gp: 4, phi_hf: 5,
                               lambda_range_max_macs: 10)
Coordinates:
    pol                       <U2 'VV'
  * bt_thresh                 (bt_thresh) int64 5 50 100 150 200
    k_rg                      (freq_sample) float64 0.0 0.003143 ... 0.858
    k_az                      (freq_line) float64 -0.1505 -0.1473 ... 0.1505
    line                      int64 2461
    sample                    int64 2840
    longitude                 float64 -61.2
    latitude                  float64 28.27
  * k_gp                      (k_gp) int64 1 2 3 4
  * phi_hf                    (phi_hf) int64 1 2 3 4 5
  * lambda_range_max_macs     (lambda_range_max_macs) float64 50.0 ... 275.0
Dimensions without coordinates: 0tau, freq_line, freq_sample, 1tau, 2tau,
                                c_sample, c_line
Data variables: (12/26)
    incidence                 float64 24.19
    ground_heading            float64 -168.5
    sensing_time              datetime64[ns] 2019-10-05T10:11:59.941637632
    sigma0                    float64 0.1942
    nesz                      float64 0.001677
    bright_targets_histogram  (bt_thresh) int64 54 0 0 0 0
    ...                        ...
    corner_line               (c_line) int64 25 4897
    corner_sample             (c_sample) int64 25 5655
    burst_corner_longitude    (c_sample, c_line) float64 -61.08 ... -61.32
    burst_corner_latitude     (c_sample, c_line) float64 28.34 28.16 28.38 28.2
    cwave_params              (k_gp, phi_hf, 2tau) float64 4.855 ... -0.334
    macs                      (lambda_range_max_macs, 2tau) complex128 (0.167...
Attributes: (12/21)
    name:                   SENTINEL1_DS:/home1/scratch/agrouaze/xsardatasync...
    short_name:             SENTINEL1_DS:S1A_WV_SLC__1SSV_20191005T100804_201...
    product:                SLC
    safe:                   S1A_WV_SLC__1SSV_20191005T100804_20191005T101314_...
    swath:                  WV
    multidataset:           False
    ...                     ...
    radar_frequency:        5405000704.0
    azimuth_time_interval:  0.0006059988896297211
    tile_width_line:        20138.934607
    tile_width_sample:      <xarray.DataArray 'cumulative ground length' ()>\...
    tile_overlap_sample:    0.0
    tile_overlap_line:      0.0