Phase 2024 012_023790_IW1 VV 20x4 3 #3
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| # n+1, n+2, n+3 pairs for a given burst + year | |
| name: InSAR_Timeseries | |
| run-name: Phase ${{ inputs.year }} ${{ inputs.burstId }} ${{ inputs.polarization }} ${{ inputs.looks }} ${{ inputs.npairs }} | |
| on: | |
| workflow_dispatch: | |
| inputs: | |
| burstId: | |
| type: string | |
| required: true | |
| description: ESA Burst Identifier (RelativeObit, ID, Subswath) | |
| default: '012_023790_IW1' | |
| polarization: | |
| type: choice | |
| required: true | |
| description: Polarization | |
| default: 'VV' | |
| options: ['VV', 'VH', 'HH'] | |
| looks: | |
| type: choice | |
| required: true | |
| description: Range x Azimuth Looks | |
| default: '20x4' | |
| options: ['20x4','10x2','5x1'] | |
| year: | |
| type: string | |
| required: true | |
| description: Year | |
| default: '2024' | |
| npairs: | |
| type: choice | |
| required: true | |
| description: Number of Pairs per Reference | |
| default: '3' | |
| options: ['3','2','1'] | |
| # Must duplicate inputs for workflow_call (https://github.com/orgs/community/discussions/39357) | |
| workflow_call: | |
| inputs: | |
| burstId: | |
| type: string | |
| required: true | |
| polarization: | |
| type: string | |
| required: true | |
| year: | |
| type: string | |
| required: true | |
| looks: | |
| type: string | |
| required: true | |
| npairs: | |
| type: string | |
| required: true | |
| # Convert inputs to environment variables for all job steps | |
| env: | |
| burstId: ${{ inputs.burstId }} | |
| Year: ${{ inputs.year }} | |
| Polarization: ${{ inputs.polarization }} | |
| Looks: ${{ inputs.looks }} | |
| NPairs: ${{ inputs.npairs }} | |
| jobs: | |
| searchASF: | |
| runs-on: ubuntu-latest | |
| # Map a step output to a job output | |
| outputs: | |
| BURST_IDS: ${{ steps.asf-search.outputs.BURST_IDS }} | |
| MATRIX: ${{ steps.asf-search.outputs.MATRIX_PARAMS_COMBINATIONS }} | |
| defaults: | |
| run: | |
| shell: bash -el {0} | |
| steps: | |
| - name: Checkout Repository | |
| uses: actions/checkout@v4 | |
| - name: Install Conda environment with Micromamba | |
| uses: mamba-org/setup-micromamba@v1 | |
| with: | |
| cache-environment: true | |
| environment-file: environment.yml | |
| # https://words.yuvi.in/post/python-in-github-actions/ | |
| - name: Search ASF for bursts | |
| id: asf-search | |
| shell: bash -el -c "python -u {0}" | |
| run: | | |
| import asf_search as asf | |
| import fsspec | |
| import geopandas as gpd | |
| import json | |
| import os | |
| # Parse Workflow inputs from environment variables | |
| START = int(os.environ['Year']) | |
| END = START+1 | |
| POL = os.environ['Polarization'] | |
| FULLBURSTID = os.environ['burstId'] | |
| RELORB,BURSTID,SUBSWATH = FULLBURSTID.split('_') | |
| print(RELORB,BURSTID,SUBSWATH) | |
| # Get centroid of burst from database | |
| url = 'https://github.com/relativeorbit/s1burstids/raw/main/burst_map_IW_000001_375887_brotli.parquet' | |
| with fsspec.open(url) as file: | |
| gfb = gpd.read_parquet(file, | |
| filters=[('burst_id', '=', int(BURSTID)), | |
| ('subswath_name', '=', SUBSWATH)] | |
| ) | |
| print(gfb) | |
| # Search for SLCs | |
| results = asf.search(platform=[asf.PLATFORM.SENTINEL1], | |
| processingLevel=asf.PRODUCT_TYPE.SLC, | |
| beamMode=asf.BEAMMODE.IW, | |
| intersectsWith=gfb.iloc[0].geometry.centroid.wkt, | |
| relativeOrbit=int(RELORB), | |
| start=f"{START}-01-01", | |
| end=f"{END}-03-01", #march to ensure we get some overlapping coverage for each year | |
| ) | |
| gf = gpd.GeoDataFrame.from_features(results.geojson(), crs=4326) | |
| print('Results:', len(gf)) | |
| # For case of frame overlap, ensure SLCs contain full burst | |
| def get_overlap_area(gf, gfREF): | |
| frame_area = gfREF.iloc[0].geometry.area | |
| overlaps = gf.geometry.map(lambda x: x.intersection(gfREF.geometry.iloc[0]).area/frame_area) | |
| return overlaps | |
| gf['overlap'] = get_overlap_area(gf, gfb) | |
| gf = gf.query('overlap >= 0.80').reset_index(drop=True) | |
| # Sort chronological ascending | |
| gf['datetime'] = gpd.pd.to_datetime(gf.startTime) | |
| gf = gf.sort_values(by='datetime', ignore_index=True) | |
| print('Number of Acquisitions: ', len(gf)) | |
| burstIDs = gf.sceneName.to_list() | |
| print('\n'.join(burstIDs)) | |
| # Create Matrix Job Mapping (JSON Array) | |
| idx_end_of_year = gf.index[gf.datetime.dt.year == START][-1] | |
| pairs = [] | |
| for r in range(idx_end_of_year + 1): | |
| for s in range(1, ${{ inputs.npairs }} + 1 ): | |
| try: | |
| ref = burstIDs[r] | |
| sec = burstIDs[r+s] | |
| shortname = f'{ref[17:25]}_{sec[17:25]}' | |
| pairs.append({'reference': ref, 'secondary': sec, 'name':shortname}) | |
| except IndexError as e: | |
| print(f'ASF Search did not return a n+{s} pair for {ref}') | |
| matrixJSON = f'{{"include":{json.dumps(pairs)}}}' | |
| print(f'Number of Interferograms: {len(pairs)}') | |
| print(matrixJSON) | |
| with open(os.environ['GITHUB_OUTPUT'], 'a') as f: | |
| print(f'BURST_IDS={burstIDs}', file=f) | |
| print(f'MATRIX_PARAMS_COMBINATIONS={matrixJSON}', file=f) | |
| hyp3-isce2: | |
| needs: searchASF | |
| strategy: | |
| matrix: ${{ fromJson(needs.searchASF.outputs.MATRIX) }} | |
| uses: ./.github/workflows/insar_pair.yml | |
| with: | |
| reference: ${{ matrix.reference }} | |
| secondary: ${{ matrix.secondary }} | |
| burstId: ${{ inputs.burstId }} | |
| year: ${{ matrix.year }} | |
| polarization: ${{ inputs.polarization }} | |
| looks: ${{ inputs.looks }} | |
| jobname: ${{ matrix.name }} | |
| secrets: inherit |