Ejemplo n.º 1
0
def create_scene(owner, prefix, landsat_id, config, datasource):
    logger.info('Creating scene for landsat id {}'.format(landsat_id))
    gcs_prefix = io.gcs_path_for_landsat_id(landsat_id)
    metadata_resp = requests.get(io.make_path_for_mtl(gcs_prefix, landsat_id))
    if metadata_resp.status_code == 404:
        logger.error('Landsat scene %s is not available yet in GCS',
                     landsat_id)
        raise Exception('Could not find landsat scene %s', landsat_id)
    filter_metadata = extract_metadata(metadata_resp.content)
    (filename, cog_fname) = process_to_cog(prefix, gcs_prefix, landsat_id,
                                           config)
    s3_location = upload_file(owner, filename, cog_fname)
    logger.info('Creating image')
    ingest_location = 's3://{}/{}'.format(data_bucket,
                                          urllib.quote(s3_location))
    scene = Scene('PRIVATE', [],
                  datasource, {},
                  landsat_id,
                  'SUCCESS',
                  'SUCCESS',
                  'INGESTED', [io.make_path_for_mtl(gcs_prefix, landsat_id)],
                  ingestLocation=ingest_location,
                  cloudCover=filter_metadata['cloud_cover'],
                  acquisitionDate=filter_metadata['acquisition_date'],
                  sceneType='COG',
                  owner=owner)
    image = create_geotiff_image(
        filename,
        ingest_location,
        filename=cog_fname,
        owner=owner,
        scene=scene.id,
        band_create_function=lambda x: config.bands.values())
    scene.images = [image]
    return scene
Ejemplo n.º 2
0
def create_scene(owner, prefix, landsat_id, config, datasource):
    logger.info('Creating scene for landsat id {}'.format(landsat_id))
    gcs_prefix = io.gcs_path_for_landsat_id(landsat_id)
    metadata_resp = requests.get(io.make_path_for_mtl(gcs_prefix, landsat_id))
    if metadata_resp.status_code == 404:
        logger.error('Landsat scene %s is not available yet in GCS',
                     landsat_id)
        raise Exception('Could not find landsat scene %s', landsat_id)
    filter_metadata = extract_metadata(metadata_resp.content)
    (filename, cog_fname) = process_to_cog(prefix, gcs_prefix, landsat_id, config)
    s3_location = upload_file(owner, filename, cog_fname)
    logger.info('Creating image')
    ingest_location = 's3://{}/{}'.format(data_bucket,
                                          urllib.quote(s3_location))
    scene = Scene(
        'PRIVATE', [],
        datasource, {},
        landsat_id,
        'SUCCESS',
        'SUCCESS',
        'INGESTED', [io.make_path_for_mtl(gcs_prefix, landsat_id)],
        ingestLocation=ingest_location,
        cloudCover=filter_metadata['cloud_cover'],
        acquisitionDate=filter_metadata['acquisition_date'],
        sceneType='COG',
        owner=owner)
    image = create_geotiff_image(
        filename,
        ingest_location,
        filename=cog_fname,
        owner=owner,
        scene=scene.id,
        band_create_function=lambda x: config.bands.values())
    scene.images = [image]
    return scene
Ejemplo n.º 3
0
def create_scene(hdf_url, temp_directory, user_id, datasource):
    """Create a MODIS scene

    Args:
        hdf_url (str): URL for MODIS scene to download
        temp_directory (str): directory to use as scratch space when creating scene
        user_id (str): ID of owner for new MODIS scene
        datasource (str): ID of datasource for new MODIS scene
    """
    config = modis_configs[datasource]
    granule_parts = os.path.basename(hdf_url).split('.')

    acquisition_datetime = datetime.strptime(granule_parts[1][1:], '%Y%j')
    name = '.'.join(granule_parts[:-1])
    id = str(uuid.uuid4())

    scene = Scene(0,
                  Visibility.PRIVATE, [],
                  datasource, {},
                  name,
                  JobStatus.SUCCESS,
                  JobStatus.SUCCESS,
                  IngestStatus.INGESTED, [],
                  owner=user_id,
                  id=id,
                  acquisitionDate=acquisition_datetime.isoformat() + 'Z',
                  cloudCover=0)

    hdf_directory = os.path.join(temp_directory, 'hdf')
    os.mkdir(hdf_directory)
    hdf_filepath = download_hdf(hdf_url, hdf_directory)

    tiff_directory = os.path.join(temp_directory, 'tiffs')
    os.mkdir(tiff_directory)
    tifs = create_geotiffs(hdf_filepath, tiff_directory)

    s3_uris = upload_tifs(tifs, user_id, scene.id)

    images = []
    get_band_func = partial(get_image_band, modis_config=config)
    for local_path, remote_path in zip(tifs, s3_uris):

        image = create_geotiff_image(local_path,
                                     remote_path,
                                     scene=scene.id,
                                     owner=user_id,
                                     band_create_function=get_band_func)
        images.append(image)
    scene.images = images
    scene.ingestLocation = s3_uris[0]
    scene.sceneType = 'COG'

    return scene
Ejemplo n.º 4
0
def create_scene(owner, prefix, landsat_id, config, datasource):
    logger.info('Creating scene for landsat id {}'.format(landsat_id))
    gcs_prefix = io.gcs_path_for_landsat_id(landsat_id)
    logger.info('Fetching all bands')
    for band in config.bands.keys():
        fetch_band(prefix, gcs_prefix, band, landsat_id)
    filter_metadata = extract_metadata(
        requests.get(io.make_path_for_mtl(gcs_prefix, landsat_id)).content)
    cog_fname = '{}_COG.tif'.format(landsat_id)
    stacked_fname = '{}_STACKED.tif'.format(landsat_id)
    filenames = {
        'COG': os.path.join(prefix, cog_fname),
        'STACKED': os.path.join(prefix, stacked_fname)
    }
    convert_to_cog(prefix, filenames['STACKED'], filenames['COG'], config,
                   landsat_id)
    s3_location = upload_file(owner, filenames['COG'], cog_fname)
    logger.info('Creating image')
    ingest_location = 's3://{}/{}'.format(data_bucket,
                                          urllib.quote(s3_location))
    scene = Scene(0,
                  'PRIVATE', [],
                  datasource, {},
                  landsat_id,
                  'SUCCESS',
                  'SUCCESS',
                  'INGESTED', [io.make_path_for_mtl(gcs_prefix, landsat_id)],
                  ingestLocation=ingest_location,
                  cloudCover=filter_metadata['cloud_cover'],
                  acquisitionDate=filter_metadata['acquisition_date'],
                  sceneType='COG',
                  owner=owner)
    image = create_geotiff_image(
        filenames['COG'],
        ingest_location,
        filename=cog_fname,
        owner=owner,
        scene=scene.id,
        band_create_function=lambda x: config.bands.values())
    scene.images = [image]
    return scene
Ejemplo n.º 5
0
def create_scene(hdf_url, temp_directory, user_id, datasource):
    """Create a MODIS scene

    Args:
        hdf_url (str): URL for MODIS scene to download
        temp_directory (str): directory to use as scratch space when creating scene
        user_id (str): ID of owner for new MODIS scene
        datasource (str): ID of datasource for new MODIS scene
    """
    config = modis_configs[datasource]
    granule_parts = os.path.basename(hdf_url).split('.')

    acquisition_datetime = datetime.strptime(granule_parts[1][1:], '%Y%j')
    name = '.'.join(granule_parts[:-1])
    id = str(uuid.uuid4())

    scene = Scene(Visibility.PRIVATE, [], datasource, {}, name,
                  JobStatus.SUCCESS, JobStatus.SUCCESS, IngestStatus.INGESTED, [], owner=user_id, id=id,
                  acquisitionDate=acquisition_datetime.isoformat() + 'Z', cloudCover=0)

    hdf_filepath = download_hdf(hdf_url, temp_directory)

    tifs = create_geotiffs(hdf_filepath, temp_directory)

    s3_uris = upload_tifs(tifs, user_id, scene.id)

    images = []
    get_band_func = partial(get_image_band, modis_config=config)
    for local_path, remote_path in zip(tifs, s3_uris):

        image = create_geotiff_image(local_path, urllib.unquote(s3_uris[0]),
                                     scene=scene.id, owner=user_id, band_create_function=get_band_func)
        images.append(image)
    scene.images = images
    scene.ingestLocation = s3_uris[0]
    scene.sceneType = 'COG'

    return scene