InSAR Product Archive

#!/usr/bin/env python3
"""
Example: Creating an Interferogram HDF5 File (Version 2.0)
Demonstrates the file structure - replace synthetic data with your actual interferograms
"""

import h5py
import numpy as np
from datetime import datetime

# Output filename
filename = 'example_interferogram.h5'

with h5py.File(filename, 'w') as f:
    
    # ============================================================
    # 1. ROOT-LEVEL METADATA (file-wide)
    # ============================================================
    f.attrs['processing_type'] = 'INTERFEROGRAM'
    f.attrs['processing_software'] = 'ISCE2 v2.6.3 + SNAPHU v2.0.5'
    f.attrs['history'] = datetime.now().isoformat()
    f.attrs['sign_convention'] = 'Positive LOS displacement corresponds to surface motion toward the sensor'
    
    # ============================================================
    # 2. CREATE TRACK
    # ============================================================
    track = f.create_group('ALOS2_073_A')
    
    # Track-level metadata (REQUIRED fields)
    track.attrs['platform'] = 'ALOS-2'
    track.attrs['relative_orbit'] = 73
    track.attrs['flight_direction'] = 'A'
    track.attrs['look_direction'] = 'R'
    track.attrs['beam_mode'] = 'WD1'
    track.attrs['beam_swath'] = 'W1'
    track.attrs['wavelength'] = 0.236
    track.attrs['scene_footprint'] = 'POLYGON((-118.5 34.0, -118.0 34.0, -118.0 34.5, -118.5 34.5, -118.5 34.0))'
    track.attrs['first_date'] = '2024-01-01'
    track.attrs['last_date'] = '2024-02-08'
    track.attrs['time_acquisition'] = '10:23'
    
    # Optional but recommended
    track.attrs['polarization'] = 'VV'
    
    # ============================================================
    # 3. LOS VECTORS (replace with your actual LOS geometry)
    # ============================================================
    # TODO: Replace this synthetic data with your actual LOS vectors
    demo_shape = (1000, 1200)  # Replace with your data dimensions
    
    # Generate synthetic LOS vectors for demonstration
    los_e_data = np.random.uniform(0.35, 0.45, demo_shape).astype(np.float32)
    los_n_data = np.random.uniform(-0.05, 0.05, demo_shape).astype(np.float32)
    los_u_data = np.random.uniform(0.75, 0.85, demo_shape).astype(np.float32)
    
    # Normalize to unit vectors
    magnitude = np.sqrt(los_e_data**2 + los_n_data**2 + los_u_data**2)
    los_e_data /= magnitude
    los_n_data /= magnitude
    los_u_data /= magnitude
    
    # Write LOS datasets with compression
    los_e = track.create_dataset('line_of_sight_e', data=los_e_data, compression='gzip')
    los_e.attrs['description'] = 'LOS unit vector - East component'
    los_e.attrs['units'] = 'dimensionless'
    
    los_n = track.create_dataset('line_of_sight_n', data=los_n_data, compression='gzip')
    los_n.attrs['description'] = 'LOS unit vector - North component'
    los_n.attrs['units'] = 'dimensionless'
    
    los_u = track.create_dataset('line_of_sight_u', data=los_u_data, compression='gzip')
    los_u.attrs['description'] = 'LOS unit vector - Up component'
    los_u.attrs['units'] = 'dimensionless'
    
    # ============================================================
    # 4. INTERFEROGRAM DATA (replace with your actual phase data)
    # ============================================================
    # Create date-pair group
    date_group = track.create_group('20240101_20240113')
    
    # Interferogram metadata
    date_group.attrs['reference_date'] = '20240101'
    date_group.attrs['secondary_date'] = '20240113'
    date_group.attrs['temporal_baseline_days'] = 12
    date_group.attrs['baseline_perp'] = 45.2
    
    # TODO: Replace this synthetic data with your actual unwrapped phase
    # Generate synthetic unwrapped interferogram for demonstration
    x = np.linspace(0, 4*np.pi, demo_shape[1])
    y = np.linspace(0, 4*np.pi, demo_shape[0])
    X, Y = np.meshgrid(x, y)
    unwrapped_data = (np.sin(X/3) * np.cos(Y/3) * 2 * np.pi).astype(np.float32)
    
    # Write unwrapped interferogram
    unwrapped = date_group.create_dataset('unwrapped_interferogram', 
                                           data=unwrapped_data, compression='gzip')
    unwrapped.attrs['description'] = 'Unwrapped interferometric phase'
    unwrapped.attrs['units'] = 'radians'
    unwrapped.attrs['unwrap_method'] = 'SNAPHU'
    
    # Create wrapped interferogram
    wrapped_data = np.angle(np.exp(1j * unwrapped_data)).astype(np.float32)
    wrapped = date_group.create_dataset('wrapped_interferogram', 
                                        data=wrapped_data, compression='gzip')
    wrapped.attrs['description'] = 'Wrapped interferometric phase'
    wrapped.attrs['units'] = 'radians'
    
    # TODO: Replace with your actual coherence data
    # Generate synthetic coherence for demonstration
    corr_data = np.random.uniform(0.5, 0.9, demo_shape).astype(np.float32)
    correlation = date_group.create_dataset('correlation', 
                                            data=corr_data, compression='gzip')
    correlation.attrs['description'] = 'Interferometric coherence'
    correlation.attrs['units'] = 'dimensionless'

print(f"✓ Created {filename}")
print(f"  Explore with: h5ls -r {filename}")
print(f"\nNOTE: This file contains synthetic demo data.")
print("Replace the data generation sections with your actual interferogram data.")

#!/usr/bin/env python3
"""
Example: Creating a Time Series HDF5 File (Version 2.0)
Demonstrates the file structure - replace synthetic data with your actual time series
"""

import h5py
import numpy as np
from datetime import datetime

# Output filename
filename = 'example_timeseries.h5'

with h5py.File(filename, 'w') as f:
    
    # ============================================================
    # 1. ROOT-LEVEL METADATA (file-wide)
    # ============================================================
    f.attrs['processing_type'] = 'DISP. TIME SERIES'
    f.attrs['processing_software'] = 'MintPy v1.5.1'
    f.attrs['history'] = datetime.now().isoformat()
    f.attrs['sign_convention'] = 'Positive LOS displacement corresponds to surface motion toward the sensor'
    
    # ============================================================
    # 2. CREATE TRACK
    # ============================================================
    track = f.create_group('ALOS2_073_A')
    
    # Track-level metadata (REQUIRED fields)
    track.attrs['platform'] = 'ALOS-2'
    track.attrs['relative_orbit'] = 73
    track.attrs['flight_direction'] = 'A'
    track.attrs['look_direction'] = 'R'
    track.attrs['beam_mode'] = 'WD1'
    track.attrs['beam_swath'] = 'W1'
    track.attrs['wavelength'] = 0.236
    track.attrs['scene_footprint'] = 'POLYGON((-118.5 34.0, -118.0 34.0, -118.0 34.5, -118.5 34.5, -118.5 34.0))'
    track.attrs['first_date'] = '2024-01-01'
    track.attrs['last_date'] = '2024-04-01'
    track.attrs['time_acquisition'] = '10:23'
    track.attrs['polarization'] = 'VV'
    
    # REQUIRED for time series: track-specific reference date
    track.attrs['reference_date'] = '20240101'
    
    # ============================================================
    # 3. LOS VECTORS (replace with your actual LOS geometry)
    # ============================================================
    # TODO: Replace with your actual LOS vectors
    demo_shape = (1000, 1200)  # Replace with your data dimensions
    
    los_e_data = np.random.uniform(0.35, 0.45, demo_shape).astype(np.float32)
    los_n_data = np.random.uniform(-0.05, 0.05, demo_shape).astype(np.float32)
    los_u_data = np.random.uniform(0.75, 0.85, demo_shape).astype(np.float32)
    
    magnitude = np.sqrt(los_e_data**2 + los_n_data**2 + los_u_data**2)
    los_e_data /= magnitude
    los_n_data /= magnitude
    los_u_data /= magnitude
    
    los_e = track.create_dataset('line_of_sight_e', data=los_e_data, 
                                 compression='gzip', compression_opts=6)
    los_e.attrs['description'] = 'LOS unit vector - East component'
    los_e.attrs['units'] = 'dimensionless'
    
    los_n = track.create_dataset('line_of_sight_n', data=los_n_data, 
                                 compression='gzip', compression_opts=6)
    los_n.attrs['description'] = 'LOS unit vector - North component'
    los_n.attrs['units'] = 'dimensionless'
    
    los_u = track.create_dataset('line_of_sight_u', data=los_u_data, 
                                 compression='gzip', compression_opts=6)
    los_u.attrs['description'] = 'LOS unit vector - Up component'
    los_u.attrs['units'] = 'dimensionless'
    
    # ============================================================
    # 4. DISPLACEMENT TIME SERIES (replace with your actual displacements)
    # ============================================================
    # List of dates in your time series
    dates = ['20240101', '20240113', '20240125', '20240208']
    
    print(f"Creating time series with {len(dates)} dates...")
    
    for idx, date_str in enumerate(dates):
        
        # TODO: Replace this synthetic data with your actual displacement
        if idx == 0:
            # Reference date: all zeros
            disp_data = np.zeros(demo_shape, dtype=np.float32)
        else:
            # Cumulative displacement in meters
            # This is synthetic - replace with your actual time series data
            disp_data = (np.random.randn(*demo_shape) * 0.01 * idx).astype(np.float32)
        
        # Create dataset: dLOS_YYYYMMDD (note: directly under track, not in subgroups)
        dataset_name = f'dLOS_{date_str}'
        dset = track.create_dataset(dataset_name, data=disp_data, 
                                     compression='gzip', compression_opts=6)
        
        # Dataset attributes
        dset.attrs['description'] = 'Cumulative LOS displacement relative to reference date'
        dset.attrs['units'] = 'meters'  # Note: meters, not radians!
        dset.attrs['acquisition_date'] = date_str
        dset.attrs['reference_date'] = '20240101'  # Should match track-level reference_date
        
        print(f"  Added dLOS_{date_str}")

print(f"\n✓ Created {filename}")
print(f"  Explore with: h5ls -r {filename}")
print(f"\nNOTE: This file contains synthetic demo data.")
print("Replace the displacement generation with your actual time series data.")

#!/usr/bin/env python3
"""
Example: Reading InSAR HDF5 Files
Demonstrates how to read different product types
"""

import h5py
import numpy as np

# Adjust to your actual filename
filename = 'example_timeseries.h5'

with h5py.File(filename, 'r') as f:
    
    # ============================================================
    # 1. READ ROOT METADATA
    # ============================================================
    proc_type = f.attrs['processing_type']
    print(f"Processing type: {proc_type}")
    print(f"Software: {f.attrs['processing_software']}")
    
    # ============================================================
    # 2. READ TRACK METADATA
    # ============================================================
    # Adjust track name to match your file
    track_name = 'ALOS2_073_A'
    track = f[track_name]
    
    print(f"\nTrack: {track_name}")
    print(f"  Platform: {track.attrs['platform']}")
    print(f"  Orbit: {track.attrs['relative_orbit']}")
    print(f"  Wavelength: {track.attrs['wavelength']:.4f} m")
    
    # ============================================================
    # 3. READ LOS VECTORS
    # ============================================================
    los_e = track['line_of_sight_e'][:]
    los_n = track['line_of_sight_n'][:]
    los_u = track['line_of_sight_u'][:]
    print(f"  LOS vectors shape: {los_e.shape}")
    
    # ============================================================
    # 4. READ DATA BASED ON PRODUCT TYPE
    # ============================================================
    if proc_type == 'INTERFEROGRAM':
        print("\nReading interferogram...")
        
        # List available interferogram date pairs
        ifgs = [key for key in track.keys() if '_' in key and len(key) == 17]
        print(f"  Found {len(ifgs)} interferogram(s): {ifgs}")
        
        # Read specific interferogram (adjust date pair to your data)
        date_pair = '20240101_20240113'
        ifg_group = track[date_pair]
        
        unwrapped = ifg_group['unwrapped_interferogram'][:]
        print(f"  Unwrapped phase shape: {unwrapped.shape}")
        print(f"  Unwrapped range: [{unwrapped.min():.2f}, {unwrapped.max():.2f}] radians")
        
        # Read coherence
        correlation = ifg_group['correlation'][:]
        print(f"  Mean coherence: {correlation.mean():.3f}")
        
    elif proc_type == 'DISP. TIME SERIES':
        print("\nReading time series...")
        
        # Get reference date (REQUIRED at track level)
        ref_date = track.attrs['reference_date']
        print(f"  Reference date: {ref_date}")
        
        # List all displacement dates
        dates = sorted([key.replace('dLOS_', '') for key in track.keys() 
                       if key.startswith('dLOS_')])
        print(f"  Found {len(dates)} date(s): {dates}")
        
        # Read specific date (adjust to your data)
        date_to_read = '20240113'
        disp = track[f'dLOS_{date_to_read}'][:]
        print(f"  Displacement shape: {disp.shape}")
        print(f"  Displacement range: [{disp.min():.4f}, {disp.max():.4f}] meters")
        
    elif proc_type == 'LOS_VELOCITY':
        print("\nReading velocity...")
        
        velocity = track['velocity'][:]
        print(f"  Velocity shape: {velocity.shape}")
        print(f"  Velocity range: [{velocity.min():.4f}, {velocity.max():.4f}] m/year")
        
        # Read uncertainty if available
        if 'velocity_std' in track:
            velocity_std = track['velocity_std'][:]
            print(f"  Mean uncertainty: {velocity_std.mean():.4f} m/year")

print("\n✓ File read successfully")

%% Example: Creating an Interferogram HDF5 File (Version 2.0)
% This script demonstrates the HDF5 format structure
% Replace demo data generation with your actual interferogram data

clear; clc;

filename = 'example_interferogram.h5';
if exist(filename, 'file'), delete(filename); end

%% 1. Root-level metadata (file-wide)
h5writeatt(filename, '/', 'processing_type', 'INTERFEROGRAM');
h5writeatt(filename, '/', 'processing_software', 'ISCE2 v2.6.3 + SNAPHU v2.0.5');
h5writeatt(filename, '/', 'history', char(datetime('now', 'Format', 'yyyy-MM-dd''T''HH:mm:ss')));
h5writeatt(filename, '/', 'sign_convention', ...
    'Positive LOS displacement corresponds to surface motion toward the sensor');

%% 2. Track-level metadata
track_path = '/ALOS2_073_A';

% REQUIRED metadata
h5writeatt(filename, track_path, 'platform', 'ALOS-2');
h5writeatt(filename, track_path, 'relative_orbit', int32(73));
h5writeatt(filename, track_path, 'flight_direction', 'A');
h5writeatt(filename, track_path, 'look_direction', 'R');
h5writeatt(filename, track_path, 'beam_mode', 'WD1');
h5writeatt(filename, track_path, 'beam_swath', 'W1');
h5writeatt(filename, track_path, 'wavelength', 0.236);
h5writeatt(filename, track_path, 'first_date', '2024-01-01');
h5writeatt(filename, track_path, 'last_date', '2024-02-08');
h5writeatt(filename, track_path, 'time_acquisition', '10:23');
h5writeatt(filename, track_path, 'scene_footprint', ...
    'POLYGON((-118.5 34.0, -118.0 34.0, -118.0 34.5, -118.5 34.5, -118.5 34.0))');

% Optional but recommended
h5writeatt(filename, track_path, 'polarization', 'VV');

%% 3. LOS vectors (replace with your actual LOS geometry)
% TODO: Replace this with your actual LOS vectors
demo_shape = [1000, 1200];  % [rows, cols] - adjust to your data size

% Generate synthetic LOS vectors for demonstration
los_e = 0.35 + 0.10 * rand(demo_shape, 'single');
los_n = -0.05 + 0.10 * rand(demo_shape, 'single');
los_u = 0.75 + 0.10 * rand(demo_shape, 'single');

% Normalize to unit vectors
magnitude = sqrt(los_e.^2 + los_n.^2 + los_u.^2);
los_e = los_e ./ magnitude;
los_n = los_n ./ magnitude;
los_u = los_u ./ magnitude;

% Write LOS datasets with compression
h5create(filename, [track_path '/line_of_sight_e'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [track_path '/line_of_sight_e'], los_e);
h5writeatt(filename, [track_path '/line_of_sight_e'], 'units', 'dimensionless');

h5create(filename, [track_path '/line_of_sight_n'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [track_path '/line_of_sight_n'], los_n);
h5writeatt(filename, [track_path '/line_of_sight_n'], 'units', 'dimensionless');

h5create(filename, [track_path '/line_of_sight_u'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [track_path '/line_of_sight_u'], los_u);
h5writeatt(filename, [track_path '/line_of_sight_u'], 'units', 'dimensionless');

%% 4. Interferogram data (replace with your actual phase data)
date_path = [track_path '/20240101_20240113'];

% Interferogram metadata
h5writeatt(filename, date_path, 'reference_date', '20240101');
h5writeatt(filename, date_path, 'secondary_date', '20240113');
h5writeatt(filename, date_path, 'temporal_baseline_days', int32(12));
h5writeatt(filename, date_path, 'baseline_perp', 45.2);

% TODO: Replace this synthetic data with your actual unwrapped interferogram
% Generate synthetic unwrapped phase for demonstration
[X, Y] = meshgrid(linspace(0, 4*pi, demo_shape(2)), linspace(0, 4*pi, demo_shape(1)));
unwrapped = single(sin(X/3) .* cos(Y/3) * 2 * pi);

h5create(filename, [date_path '/unwrapped_interferogram'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [date_path '/unwrapped_interferogram'], unwrapped);
h5writeatt(filename, [date_path '/unwrapped_interferogram'], 'units', 'radians');
h5writeatt(filename, [date_path '/unwrapped_interferogram'], 'unwrap_method', 'SNAPHU');

% Wrapped phase
wrapped = single(angle(exp(1i * unwrapped)));
h5create(filename, [date_path '/wrapped_interferogram'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [date_path '/wrapped_interferogram'], wrapped);
h5writeatt(filename, [date_path '/wrapped_interferogram'], 'units', 'radians');

% TODO: Replace with your actual coherence data
% Generate synthetic coherence for demonstration
coherence = single(0.5 + 0.4 * rand(demo_shape));
h5create(filename, [date_path '/correlation'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [date_path '/correlation'], coherence);
h5writeatt(filename, [date_path '/correlation'], 'units', 'dimensionless');

fprintf('✓ Created %s\n', filename);
fprintf('  Explore with: h5disp(''%s'')\n\n', filename);
fprintf('NOTE: This file contains synthetic demo data.\n');
fprintf('Replace the data generation sections with your actual interferogram data.\n');

%% Example: Creating a Time Series HDF5 File (Version 2.0)
% This script demonstrates the time series format structure
% Replace demo data with your actual time series displacements

clear; clc;

filename = 'example_timeseries.h5';
if exist(filename, 'file'), delete(filename); end

%% 1. Root-level metadata
h5writeatt(filename, '/', 'processing_type', 'DISP. TIME SERIES');
h5writeatt(filename, '/', 'processing_software', 'MintPy v1.5.1');
h5writeatt(filename, '/', 'history', char(datetime('now', 'Format', 'yyyy-MM-dd''T''HH:mm:ss')));
h5writeatt(filename, '/', 'sign_convention', ...
    'Positive LOS displacement corresponds to surface motion toward the sensor');

%% 2. Track-level metadata
track_path = '/ALOS2_073_A';

% REQUIRED metadata
h5writeatt(filename, track_path, 'platform', 'ALOS-2');
h5writeatt(filename, track_path, 'relative_orbit', int32(73));
h5writeatt(filename, track_path, 'flight_direction', 'A');
h5writeatt(filename, track_path, 'look_direction', 'R');
h5writeatt(filename, track_path, 'beam_mode', 'WD1');
h5writeatt(filename, track_path, 'beam_swath', 'W1');
h5writeatt(filename, track_path, 'wavelength', 0.236);
h5writeatt(filename, track_path, 'first_date', '2024-01-01');
h5writeatt(filename, track_path, 'last_date', '2024-04-01');
h5writeatt(filename, track_path, 'time_acquisition', '10:23');

% REQUIRED for time series: track-specific reference date
h5writeatt(filename, track_path, 'reference_date', '20240101');

% Optional
h5writeatt(filename, track_path, 'polarization', 'VV');

%% 3. LOS vectors (replace with your actual LOS geometry)
% TODO: Replace with your actual LOS vectors
demo_shape = [1000, 1200];  % [rows, cols] - adjust to your data size

los_e = 0.35 + 0.10 * rand(demo_shape, 'single');
los_n = -0.05 + 0.10 * rand(demo_shape, 'single');
los_u = 0.75 + 0.10 * rand(demo_shape, 'single');

magnitude = sqrt(los_e.^2 + los_n.^2 + los_u.^2);
los_e = los_e ./ magnitude;
los_n = los_n ./ magnitude;
los_u = los_u ./ magnitude;

h5create(filename, [track_path '/line_of_sight_e'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [track_path '/line_of_sight_e'], los_e);
h5writeatt(filename, [track_path '/line_of_sight_e'], 'units', 'dimensionless');

h5create(filename, [track_path '/line_of_sight_n'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [track_path '/line_of_sight_n'], los_n);
h5writeatt(filename, [track_path '/line_of_sight_n'], 'units', 'dimensionless');

h5create(filename, [track_path '/line_of_sight_u'], demo_shape, ...
    'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
h5write(filename, [track_path '/line_of_sight_u'], los_u);
h5writeatt(filename, [track_path '/line_of_sight_u'], 'units', 'dimensionless');

%% 4. Displacement time series (replace with your actual displacements)
dates = {'20240101', '20240113', '20240125', '20240208'};

fprintf('Creating time series with %d dates...\n', length(dates));

for i = 1:length(dates)
    date_str = dates{i};
    
    % TODO: Replace this synthetic data with your actual displacement data
    if i == 1
        % Reference date: all zeros
        disp_data = zeros(demo_shape, 'single');
    else
        % Cumulative displacement in meters
        % This is synthetic - replace with your actual time series data
        disp_data = single(randn(demo_shape) * 0.01 * (i-1));
    end
    
    % Write dataset: dLOS_YYYYMMDD (note: directly under track, not in subgroups)
    dataset_path = [track_path '/dLOS_' date_str];
    h5create(filename, dataset_path, demo_shape, ...
        'Datatype', 'single', 'ChunkSize', [100 100], 'Deflate', 6);
    h5write(filename, dataset_path, disp_data);
    
    % Dataset attributes
    h5writeatt(filename, dataset_path, 'units', 'meters');  % Note: meters, not radians!
    h5writeatt(filename, dataset_path, 'acquisition_date', date_str);
    h5writeatt(filename, dataset_path, 'reference_date', '20240101');
    
    fprintf('  Added dLOS_%s\n', date_str);
end

fprintf('\n✓ Created %s\n', filename);
fprintf('  Explore with: h5disp(''%s'')\n\n', filename);
fprintf('NOTE: This file contains synthetic demo data.\n');
fprintf('Replace the displacement generation with your actual time series data.\n');

%% Example: Reading InSAR HDF5 Files
% Demonstrates how to read different product types

clear; clc;

% Adjust to your actual filename
filename = 'example_timeseries.h5';

%% 1. Read root metadata
proc_type = h5readatt(filename, '/', 'processing_type');
fprintf('Processing type: %s\n', proc_type);

%% 2. Read track metadata
track = 'ALOS2_073_A';  % Adjust to your track name
platform = h5readatt(filename, ['/' track], 'platform');
wavelength = h5readatt(filename, ['/' track], 'wavelength');
fprintf('Platform: %s, Wavelength: %.4f m\n', platform, wavelength);

%% 3. Read LOS vectors
los_e = h5read(filename, ['/' track '/line_of_sight_e']);
los_n = h5read(filename, ['/' track '/line_of_sight_n']);
los_u = h5read(filename, ['/' track '/line_of_sight_u']);
fprintf('LOS vectors size: %s\n', mat2str(size(los_e)));

%% 4. Read data based on product type
if strcmp(proc_type, 'INTERFEROGRAM')
    fprintf('\nReading interferogram...\n');
    
    % Read specific interferogram (adjust dates to your data)
    date_pair = '20240101_20240113';
    unwrapped = h5read(filename, ['/' track '/' date_pair '/unwrapped_interferogram']);
    fprintf('  Unwrapped phase range: [%.2f, %.2f] radians\n', ...
        min(unwrapped(:)), max(unwrapped(:)));
    
    % Visualize
    figure;
    imagesc(unwrapped);
    colorbar;
    title('Unwrapped Phase (radians)');
    axis equal tight;
    
elseif strcmp(proc_type, 'DISP. TIME SERIES')
    fprintf('\nReading time series...\n');
    
    % Get reference date (REQUIRED at track level)
    ref_date = h5readatt(filename, ['/' track], 'reference_date');
    fprintf('  Reference date: %s\n', ref_date);
    
    % Read specific date (adjust to your data)
    date_to_read = '20240113';
    disp_data = h5read(filename, ['/' track '/dLOS_' date_to_read]);
    fprintf('  Displacement range: [%.4f, %.4f] m\n', ...
        min(disp_data(:)), max(disp_data(:)));
    
    % Visualize
    figure;
    imagesc(disp_data);
    colorbar;
    title(sprintf('LOS Displacement: %s (meters)', date_to_read));
    axis equal tight;
    
elseif strcmp(proc_type, 'LOS_VELOCITY')
    fprintf('\nReading velocity...\n');
    
    velocity = h5read(filename, ['/' track '/velocity']);
    fprintf('  Velocity range: [%.4f, %.4f] m/year\n', ...
        min(velocity(:)), max(velocity(:)));
    
    % Visualize
    figure;
    imagesc(velocity);
    colorbar;
    title('LOS Velocity (m/year)');
    axis equal tight;
end

fprintf('\n✓ File read successfully\n');