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| 1 | +"""Wrapper of s1etad module to read S1-ETAD products.""" |
| 2 | +import datetime |
| 3 | +import glob |
| 4 | +import os |
| 5 | + |
| 6 | +import numpy as np |
| 7 | +from matplotlib import pyplot as plt |
| 8 | +from scipy.interpolate import RectBivariateSpline |
| 9 | + |
| 10 | +try: |
| 11 | + import s1etad |
| 12 | +except ImportError: |
| 13 | + raise ImportError('Can NOT import s1etad (https://gitlab.com/s1-etad/s1-etad)!') |
| 14 | + |
| 15 | + |
| 16 | + |
| 17 | +def get_eta_correction_from_slc_burst(slc_burst, eta_dir, corr_type='sum', include_tropo=True, |
| 18 | + resample=True, plot=False, verbose=True, unit='second'): |
| 19 | + """Get the ETAD correction for one S1 burst. |
| 20 | +
|
| 21 | + Parameters |
| 22 | + ---------- |
| 23 | + slc_burst: Sentinel1BurstSlc |
| 24 | + Sentinel-1 burst object from sentinel1_reader |
| 25 | + eta_dir: str |
| 26 | + Sentinel-1 ETAD product directory |
| 27 | + corr_type: (list of) str |
| 28 | + Sentinel-1 ETAD correction type: |
| 29 | + sar, atm, sum, bistatic, doppler, fmrate, geodetic, ionospheric, tropospheric |
| 30 | + where sar = bistatic + doppler + fmrate |
| 31 | + atm = ionospheric + tropospheric |
| 32 | + sum = sar + atm + geodetic |
| 33 | + resample: bool |
| 34 | + resample the low resolution ETA to the full resample SLC size |
| 35 | + unit: str |
| 36 | + output ETA correction unit: |
| 37 | + pixel, second (meter is not recommended, as time info is more consistent and universal in SAR) |
| 38 | +
|
| 39 | + Returns: |
| 40 | + ---------- |
| 41 | + slc_rg_corr: np.ndarray in float32 in size of (lines, samples) |
| 42 | + S1 ETAD correction in range direction in the unit of meter or second |
| 43 | + slc_az_corr: np.ndarray in float32 in size of (lines, samples) |
| 44 | + S1 ETAD correction in azimuth direction in the unit of meter or second |
| 45 | + """ |
| 46 | + vprint = print if verbose else lambda *args, **kwargs: None |
| 47 | + if unit not in ['second', 'meter', 'pixel']: |
| 48 | + raise ValueError(f'Un-recognized input unit={unit}!') |
| 49 | + meter = (unit == 'meter') |
| 50 | + # When True, read s1etad product in meters |
| 51 | + # When False, read s1etad product in seconds [recommended] |
| 52 | + |
| 53 | + # locate / read ETA burst |
| 54 | + eta_burst, eta = get_eta_burst_from_slc_burst(slc_burst, eta_dir, verbose=verbose) |
| 55 | + |
| 56 | + # read ETA correction data |
| 57 | + corr_type = corr_type.lower() |
| 58 | + if isinstance(corr_type, list): |
| 59 | + corr_types = list(corr_type) |
| 60 | + elif corr_type == 'sar': |
| 61 | + corr_types = ['bistatic', 'doppler', 'fmrate'] |
| 62 | + elif corr_type == 'atm': |
| 63 | + corr_types = ['ionospheric', 'tropospheric'] |
| 64 | + else: |
| 65 | + corr_types = [corr_type] |
| 66 | + vprint(f'read correction data with type: {corr_type}') |
| 67 | + |
| 68 | + eta_rg_corr = np.zeros((eta_burst.lines, eta_burst.samples), dtype=np.float32) |
| 69 | + eta_az_corr = np.zeros((eta_burst.lines, eta_burst.samples), dtype=np.float32) |
| 70 | + for corr_type in corr_types: |
| 71 | + correction = eta_burst.get_correction(corr_type, meter=meter) |
| 72 | + |
| 73 | + if 'x' in correction.keys(): |
| 74 | + scale = slc_burst.range_sampling_rate if unit == 'pixel' else 1.0 |
| 75 | + eta_rg_corr += correction['x'] * scale |
| 76 | + |
| 77 | + if 'y' in correction.keys(): |
| 78 | + scale = 1.0 / slc_burst.azimuth_time_interval if unit == 'pixel' else 1.0 |
| 79 | + eta_az_corr += correction['y'] * scale |
| 80 | + |
| 81 | + if not include_tropo and any(x in corr_types for x in ['tropospheric', 'sum']): |
| 82 | + print('excluding tropospheric component from ETAD products in X direction') |
| 83 | + correction = eta_burst.get_correction('tropospheric') |
| 84 | + scale = slc_burst.range_sampling_rate if unit == 'pixel' else 1.0 |
| 85 | + eta_rg_corr -= correction['x'] * scale |
| 86 | + |
| 87 | + if resample or plot: |
| 88 | + # calculate ETA grid |
| 89 | + eta_az_start = (eta.min_azimuth_time - slc_burst.sensing_mid).total_seconds() + eta_burst.sampling_start['y'] |
| 90 | + eta_rg_start = eta.min_range_time + eta_burst.sampling_start['x'] |
| 91 | + eta_az_ax = eta_az_start + np.arange(eta_burst.lines) * eta_burst.sampling['y'] |
| 92 | + eta_rg_ax = eta_rg_start + np.arange(eta_burst.samples) * eta_burst.sampling['x'] |
| 93 | + |
| 94 | + # calculate SLC grid |
| 95 | + slc_az_ax = np.arange(slc_burst.length) * slc_burst.azimuth_time_interval \ |
| 96 | + + (slc_burst.sensing_start - slc_burst.sensing_mid).total_seconds() |
| 97 | + slc_rg_ax = np.arange(slc_burst.width) / slc_burst.range_sampling_rate \ |
| 98 | + + slc_burst.slant_range_time |
| 99 | + |
| 100 | + if resample: |
| 101 | + # resample ETA correction data to the SLC grid |
| 102 | + vprint('resampling the ETA correction data from ETA grid to SLC grid ...') |
| 103 | + rg_interp = RectBivariateSpline(eta_az_ax, eta_rg_ax, eta_rg_corr, kx=1, ky=1) # bi-linear |
| 104 | + az_interp = RectBivariateSpline(eta_az_ax, eta_rg_ax, eta_az_corr, kx=1, ky=1) # bi-linear |
| 105 | + slc_rg_corr = rg_interp(slc_az_ax, slc_rg_ax) |
| 106 | + slc_az_corr = az_interp(slc_az_ax, slc_rg_ax) |
| 107 | + |
| 108 | + if plot: |
| 109 | + vprint('plot ETA correction data and grid') |
| 110 | + |
| 111 | + # figure 1 - ETA corrections |
| 112 | + fig, axs = plt.subplots(nrows=2, ncols=1, figsize=[12, 6], sharex=True, sharey=True) |
| 113 | + for ax, corr, title in zip(axs, [eta_rg_corr, eta_az_corr], ['x', 'y']): |
| 114 | + im = ax.imshow(corr, aspect='auto', interpolation='nearest') |
| 115 | + fig.colorbar(im, ax=ax, shrink=0.8, location='right').set_label('pixel') |
| 116 | + ax.set_title(f'correction [{title}]') |
| 117 | + ax.set_ylabel('Azimuth [pixel]') |
| 118 | + axs[1].set_xlabel('Range [pixel]') |
| 119 | + fig.tight_layout() |
| 120 | + |
| 121 | + # figure 2 - ETA & SLC grids [for comparison/checking] |
| 122 | + eta_box = np.asarray([ |
| 123 | + (eta_rg_ax[0], eta_az_ax[0]), |
| 124 | + (eta_rg_ax[0], eta_az_ax[-1]), |
| 125 | + (eta_rg_ax[-1], eta_az_ax[-1]), |
| 126 | + (eta_rg_ax[-1], eta_az_ax[0]), |
| 127 | + (eta_rg_ax[0], eta_az_ax[0]), |
| 128 | + ]) |
| 129 | + slc_box = np.asarray([ |
| 130 | + (slc_rg_ax[0], slc_az_ax[0]), |
| 131 | + (slc_rg_ax[0], slc_az_ax[-1]), |
| 132 | + (slc_rg_ax[-1], slc_az_ax[-1]), |
| 133 | + (slc_rg_ax[-1], slc_az_ax[0]), |
| 134 | + (slc_rg_ax[0], slc_az_ax[0]), |
| 135 | + ]) |
| 136 | + |
| 137 | + fig, ax = plt.subplots(figsize=[12, 3]) |
| 138 | + ax.plot(eta_box[:, 0] * 1e3, eta_box[:, 1], 'C0', label='ETA') |
| 139 | + ax.plot(slc_box[:, 0] * 1e3, slc_box[:, 1], 'C1', label='SLC') |
| 140 | + ax.set_xlabel('Range [ms]') |
| 141 | + ax.set_ylabel('Azimuth [s]') |
| 142 | + ax.set_title('grid') |
| 143 | + ax.legend() |
| 144 | + ax.grid() |
| 145 | + |
| 146 | + plt.show() |
| 147 | + |
| 148 | + if not resample: |
| 149 | + return eta_rg_corr, eta_az_corr |
| 150 | + |
| 151 | + return slc_rg_corr, slc_az_corr |
| 152 | + |
| 153 | + |
| 154 | + |
| 155 | +def get_eta_burst_from_slc_burst(slc_burst, eta_dir, verbose=True): |
| 156 | + """Read ETA burst corresponding to the input SLC burst.""" |
| 157 | + |
| 158 | + # locate ETAD file |
| 159 | + eta_file = get_eta_file_from_slc_burst(slc_burst, eta_dir, verbose=verbose) |
| 160 | + |
| 161 | + # read ETA file using s1-etad |
| 162 | + eta = s1etad.Sentinel1Etad(eta_file) |
| 163 | + |
| 164 | + # locate the ETA burst |
| 165 | + t0_query = slc_burst.sensing_start - datetime.timedelta(seconds=0.25) |
| 166 | + t1_query = slc_burst.sensing_stop + datetime.timedelta(seconds=0.25) |
| 167 | + if verbose: |
| 168 | + print(f'search ETA burst in {slc_burst.swath_name} with the following time range:') |
| 169 | + print(f'start time: {t0_query}') |
| 170 | + print(f'end time: {t1_query}') |
| 171 | + |
| 172 | + selection = eta.query_burst( |
| 173 | + swath=slc_burst.swath_name.upper(), |
| 174 | + first_time=t0_query, |
| 175 | + last_time=t1_query, |
| 176 | + ) |
| 177 | + |
| 178 | + if len(selection) == 0: |
| 179 | + raise ValueError('No ETA burst found!') |
| 180 | + elif len(selection) > 1: |
| 181 | + raise ValueError('More than 1 ETA burst found, please adjust your search/query criteria!') |
| 182 | + |
| 183 | + eta_burst = eta[slc_burst.swath_name.upper()][selection.bIndex.values[0]] |
| 184 | + |
| 185 | + return eta_burst, eta |
| 186 | + |
| 187 | + |
| 188 | +def get_eta_file_from_slc_burst(slc_burst, eta_dir, verbose=True): |
| 189 | + """Get/locate ETAD file path based on SLC burst.""" |
| 190 | + |
| 191 | + # safe filename --> ETA filename pattern |
| 192 | + fparts = os.path.basename(slc_burst.safe_filename).split('_') |
| 193 | + eta_fbase = f'{fparts[0]}_IW_ETA__*_{fparts[5]}_{fparts[6]}_{fparts[7]}_{fparts[8]}_*.SAFE' |
| 194 | + |
| 195 | + # search the ETA filename pattern |
| 196 | + eta_file = glob.glob(os.path.join(eta_dir, eta_fbase))[0] |
| 197 | + if verbose: |
| 198 | + print(f'search ETA file with pattern: {eta_fbase}') |
| 199 | + print(f'locate ETA file: {eta_file}') |
| 200 | + |
| 201 | + return eta_file |
| 202 | + |
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