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darts_acquisition.planet

PLANET related data loading. Should be used temporary and maybe moved to the acquisition package.

logger module-attribute 

logger = logging.getLogger(
    __name__.replace("darts_", "darts.")
)

_is_valid_date 

_is_valid_date(date_str: str, format: str) -> bool
Source code in darts-acquisition/src/darts_acquisition/planet.py 
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def _is_valid_date(date_str: str, format: str) -> bool:
    try:
        datetime.strptime(date_str, format)
        return True
    except ValueError:
        return False

get_planet_geometry 

get_planet_geometry(
    fpath: str | pathlib.Path,
) -> odc.geo.Geometry

Get the geometry of a Planet scene.

Parameters:

  • fpath (str | pathlib.Path) –

    The file path to the Planet scene from which to derive the geometry.

Returns:

  • odc.geo.Geometry –

    odc.geo.Geometry: The geometry of the Planet scene.

Raises:

Source code in darts-acquisition/src/darts_acquisition/planet.py 
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def get_planet_geometry(fpath: str | Path) -> odc.geo.Geometry:
    """Get the geometry of a Planet scene.

    Args:
        fpath (str | Path): The file path to the Planet scene from which to derive the geometry.

    Returns:
        odc.geo.Geometry: The geometry of the Planet scene.

    Raises:
        FileNotFoundError: If no matching TIFF file is found in the specified path.

    """
    # Convert to Path object if a string is provided
    fpath = fpath if isinstance(fpath, Path) else Path(fpath)
    # Get imagepath
    ps_image = next(fpath.glob("*_SR.tif"), None)
    if not ps_image:
        ps_image = next(fpath.glob("*_SR_clip.tif"), None)
    if not ps_image:
        raise FileNotFoundError(f"No matching TIFF files found in {fpath.resolve()} (.glob('*_SR.tif'))")

    planet_raster = rasterio.open(ps_image)
    return odc.geo.Geometry(planet_raster.bounds, crs=planet_raster.crs)

load_planet_masks 

load_planet_masks(
    fpath: str | pathlib.Path,
) -> xarray.Dataset

Load quality and validity masks from a PlanetScope scene's UDM-2 data.

This function extracts data quality information from the PlanetScope Usable Data Mask (UDM-2) to create simplified quality masks for filtering and analysis.

Parameters:

  • fpath (str | pathlib.Path) –

    Path to the directory containing the PlanetScope scene data. Must contain _udm2.tif (or _udm2_clip.tif) file.

Returns:

  • xarray.Dataset –

    xr.Dataset: Dataset containing quality mask information with the following data variables: - quality_data_mask (uint8): Combined quality indicator * 0 = Invalid (no data) * 1 = Low quality (clouds, shadows, haze, snow, or other artifacts) * 2 = High quality (clear, usable data) Attributes: data_source="planet", long_name="Quality data mask", description="0 = Invalid, 1 = Low Quality, 2 = High Quality" - planet_udm (uint8): Raw UDM-2 bands (8 bands) Attributes: data_source="planet", long_name="Planet UDM", description="Usable Data Mask"

Raises:

Note

Quality mask derivation logic: - Invalid: UDM band 8 (no data) is set - Low quality: Any of UDM bands 2-6 (clouds, shadows, haze, snow, or artifacts) is set - High quality: Neither invalid nor low quality

UDM-2 band definitions: 1. Clear - 2. Snow - 3. Shadow - 4. Light Haze - 5. Heavy Haze 6. Cloud - 7. Confidence - 8. No Data

Example

Load and apply quality masks:

from darts_acquisition import load_planet_scene, load_planet_masks

# Load scene and masks
scene = load_planet_scene("/data/planet/20230615_123045_1234")
masks = load_planet_masks("/data/planet/20230615_123045_1234")

# Filter to high quality pixels only
scene_filtered = scene.where(masks.quality_data_mask == 2)

# Count quality distribution
import numpy as np
unique, counts = np.unique(
    masks.quality_data_mask.values,
    return_counts=True
)
print(dict(zip(unique, counts)))
Source code in darts-acquisition/src/darts_acquisition/planet.py 
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@stopwatch.f("Loading Planet masks", printer=logger.debug)
def load_planet_masks(fpath: str | Path) -> xr.Dataset:
    """Load quality and validity masks from a PlanetScope scene's UDM-2 data.

    This function extracts data quality information from the PlanetScope Usable Data Mask
    (UDM-2) to create simplified quality masks for filtering and analysis.

    Args:
        fpath (str | Path): Path to the directory containing the PlanetScope scene data.
            Must contain *_udm2.tif (or *_udm2_clip.tif) file.

    Returns:
        xr.Dataset: Dataset containing quality mask information with the following data variables:
            - quality_data_mask (uint8): Combined quality indicator
                * 0 = Invalid (no data)
                * 1 = Low quality (clouds, shadows, haze, snow, or other artifacts)
                * 2 = High quality (clear, usable data)
              Attributes: data_source="planet", long_name="Quality data mask",
              description="0 = Invalid, 1 = Low Quality, 2 = High Quality"
            - planet_udm (uint8): Raw UDM-2 bands (8 bands)
              Attributes: data_source="planet", long_name="Planet UDM",
              description="Usable Data Mask"

    Raises:
        FileNotFoundError: If the UDM-2 TIFF file is not found in the directory.

    Note:
        Quality mask derivation logic:
        - Invalid: UDM band 8 (no data) is set
        - Low quality: Any of UDM bands 2-6 (clouds, shadows, haze, snow, or artifacts) is set
        - High quality: Neither invalid nor low quality

        UDM-2 band definitions:
        1. Clear - 2. Snow - 3. Shadow - 4. Light Haze - 5. Heavy Haze
        6. Cloud - 7. Confidence - 8. No Data

    Example:
        Load and apply quality masks:

        ```python
        from darts_acquisition import load_planet_scene, load_planet_masks

        # Load scene and masks
        scene = load_planet_scene("/data/planet/20230615_123045_1234")
        masks = load_planet_masks("/data/planet/20230615_123045_1234")

        # Filter to high quality pixels only
        scene_filtered = scene.where(masks.quality_data_mask == 2)

        # Count quality distribution
        import numpy as np
        unique, counts = np.unique(
            masks.quality_data_mask.values,
            return_counts=True
        )
        print(dict(zip(unique, counts)))
        ```

    """
    # Convert to Path object if a string is provided
    fpath = fpath if isinstance(fpath, Path) else Path(fpath)

    logger.debug(f"Loading data masks from {fpath.resolve()}")

    # Get imagepath
    udm_path = next(fpath.glob("*_udm2.tif"), None)
    if not udm_path:
        udm_path = next(fpath.glob("*_udm2_clip.tif"), None)
    if not udm_path:
        raise FileNotFoundError(f"No matching UDM-2 TIFF files found in {fpath.resolve()} (.glob('*_udm2.tif'))")

    # See udm classes here: https://developers.planet.com/docs/data/udm-2/
    da_udm = xr.open_dataarray(udm_path).astype("uint8")
    invalids = da_udm.sel(band=8).fillna(0) != 0
    low_quality = da_udm.sel(band=[2, 3, 4, 5, 6]).max(axis=0) == 1
    high_quality = ~low_quality & ~invalids
    qa_ds = (
        xr.where(high_quality, 2, 0)
        .where(~low_quality, 1)
        .where(~invalids, 0)
        .astype("uint8")
        .to_dataset(name="quality_data_mask")
        .drop_vars("band")
    )
    qa_ds["planet_udm"] = da_udm

    qa_ds["quality_data_mask"].attrs = {
        "data_source": "planet",
        "long_name": "Quality data mask",
        "description": "0 = Invalid, 1 = Low Quality, 2 = High Quality",
    }
    qa_ds["planet_udm"].attrs = {
        "data_source": "planet",
        "long_name": "Planet UDM",
        "description": "Usable Data Mask",
    }

    return qa_ds

load_planet_scene 

load_planet_scene(
    fpath: str | pathlib.Path,
) -> xarray.Dataset

Load a PlanetScope satellite scene from GeoTIFF files.

This function loads PlanetScope surface reflectance data (PSScene or PSOrthoTile) from a directory containing TIFF files and metadata. The scene type is automatically detected from the directory name format.

Parameters:

  • fpath (str | pathlib.Path) –

    Path to the directory containing the PlanetScope scene data. The directory must follow PlanetScope naming conventions: - Scene: YYYYMMDD_HHMMSS_NN_XXXX or YYYYMMDD_HHMMSS_XXXX - Orthotile: NNNNNNN_NNNNNNN_YYYY-MM-DD_XXXX Must contain _SR.tif (or _SR_clip.tif) and *_metadata.json files.

Returns:

  • xarray.Dataset –

    xr.Dataset: The loaded PlanetScope dataset with the following data variables: - blue (float32): Blue band surface reflectance [0-1] - green (float32): Green band surface reflectance [0-1] - red (float32): Red band surface reflectance [0-1] - nir (float32): Near-infrared band surface reflectance [0-1]

    Each variable has attributes: - long_name: "PLANET {Band}" - units: "Reflectance" - data_source: "planet" - planet_type: "scene" or "orthotile"

    Dataset-level attributes: - azimuth (float): Solar azimuth angle in degrees - elevation (float): Solar elevation angle in degrees - tile_id (str): Unique identifier for the scene - planet_scene_id (str): Scene identifier (for scenes) or scene portion (for orthotiles) - planet_orthotile_id (str): Orthotile identifier (only for orthotiles)

Raises:

  • FileNotFoundError –

    If required TIFF or metadata files are not found in the directory.

Note
  • Input DN values are divided by 10000 to convert to reflectance [0-1].
  • The scene type (PSScene vs PSOrthoTile) is automatically detected from the directory name.
  • Solar geometry is extracted from the metadata JSON file.
Example

Load a PlanetScope scene:

from darts_acquisition import load_planet_scene

# Load scene data
planet_ds = load_planet_scene("/data/planet/20230615_123045_1234")

# Access bands
ndvi = (planet_ds.nir - planet_ds.red) / (planet_ds.nir + planet_ds.red)

# Check solar geometry
print(f"Solar azimuth: {planet_ds.azimuth}")
print(f"Solar elevation: {planet_ds.elevation}")
Source code in darts-acquisition/src/darts_acquisition/planet.py 
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@stopwatch.f("Loading Planet scene", printer=logger.debug)
def load_planet_scene(fpath: str | Path) -> xr.Dataset:
    """Load a PlanetScope satellite scene from GeoTIFF files.

    This function loads PlanetScope surface reflectance data (PSScene or PSOrthoTile) from
    a directory containing TIFF files and metadata. The scene type is automatically detected
    from the directory name format.

    Args:
        fpath (str | Path): Path to the directory containing the PlanetScope scene data.
            The directory must follow PlanetScope naming conventions:
            - Scene: YYYYMMDD_HHMMSS_NN_XXXX or YYYYMMDD_HHMMSS_XXXX
            - Orthotile: NNNNNNN_NNNNNNN_YYYY-MM-DD_XXXX
            Must contain *_SR.tif (or *_SR_clip.tif) and *_metadata.json files.

    Returns:
        xr.Dataset: The loaded PlanetScope dataset with the following data variables:
            - blue (float32): Blue band surface reflectance [0-1]
            - green (float32): Green band surface reflectance [0-1]
            - red (float32): Red band surface reflectance [0-1]
            - nir (float32): Near-infrared band surface reflectance [0-1]

            Each variable has attributes:
            - long_name: "PLANET {Band}"
            - units: "Reflectance"
            - data_source: "planet"
            - planet_type: "scene" or "orthotile"

            Dataset-level attributes:
            - azimuth (float): Solar azimuth angle in degrees
            - elevation (float): Solar elevation angle in degrees
            - tile_id (str): Unique identifier for the scene
            - planet_scene_id (str): Scene identifier (for scenes) or scene portion (for orthotiles)
            - planet_orthotile_id (str): Orthotile identifier (only for orthotiles)

    Raises:
        FileNotFoundError: If required TIFF or metadata files are not found in the directory.

    Note:
        - Input DN values are divided by 10000 to convert to reflectance [0-1].
        - The scene type (PSScene vs PSOrthoTile) is automatically detected from the directory name.
        - Solar geometry is extracted from the metadata JSON file.

    Example:
        Load a PlanetScope scene:

        ```python
        from darts_acquisition import load_planet_scene

        # Load scene data
        planet_ds = load_planet_scene("/data/planet/20230615_123045_1234")

        # Access bands
        ndvi = (planet_ds.nir - planet_ds.red) / (planet_ds.nir + planet_ds.red)

        # Check solar geometry
        print(f"Solar azimuth: {planet_ds.azimuth}")
        print(f"Solar elevation: {planet_ds.elevation}")
        ```

    """
    # Convert to Path object if a string is provided
    fpath = fpath if isinstance(fpath, Path) else Path(fpath)

    # Check if the directory contains a PSOrthoTile or PSScene
    planet_type = parse_planet_type(fpath)
    logger.debug(f"Loading Planet PS {planet_type.capitalize()} from {fpath.resolve()}")

    # Get imagepath
    ps_image = next(fpath.glob("*_SR.tif"), None)
    if not ps_image:
        ps_image = next(fpath.glob("*_SR_clip.tif"), None)
    if not ps_image:
        raise FileNotFoundError(f"No matching TIFF files found in {fpath.resolve()} (.glob('*_SR.tif'))")

    ps_meta = next(fpath.glob("*_metadata.json"), None)
    if not ps_meta:
        raise FileNotFoundError(
            f"No matching metadata JSON files found in {fpath.resolve()} (.glob('*_metadata.json'))"
        )
    metadata = json.load(ps_meta.open())

    # Define band names and corresponding indices
    planet_da = xr.open_dataarray(ps_image)

    # Divide by 10000 to get reflectance between 0 and 1
    planet_da = planet_da.astype("float32") / 10000.0

    # Create a dataset with the bands
    bands = ["blue", "green", "red", "nir"]
    ds_planet = planet_da.assign_coords({"band": bands}).to_dataset(dim="band")
    for var in bands:
        ds_planet[var].attrs["long_name"] = f"PLANET {var.capitalize()}"
        ds_planet[var].attrs["units"] = "Reflectance"

    for var in ds_planet.data_vars:
        ds_planet[var].attrs["data_source"] = "planet"
        ds_planet[var].attrs["planet_type"] = planet_type

    # Add sun and elevation from metadata
    ds_planet.attrs["azimuth"] = metadata.get("sun_azimuth", float("nan"))
    ds_planet.attrs["elevation"] = metadata.get("sun_elevation", float("nan"))

    if planet_type == "scene":
        ds_planet.attrs["tile_id"] = fpath.stem
        ds_planet.attrs["planet_scene_id"] = fpath.stem
    elif planet_type == "orthotile":
        ds_planet.attrs["tile_id"] = f"{fpath.parent.stem}-{fpath.stem}"
        ds_planet.attrs["planet_orthotile_id"] = fpath.parent.stem
        ds_planet.attrs["planet_scene_id"] = fpath.stem

    return ds_planet

parse_planet_type 

parse_planet_type(
    fpath: pathlib.Path,
) -> typing.Literal["orthotile", "scene"]

Parse the type of Planet data from the directory path.

Parameters:

  • fpath (pathlib.Path) –

    The directory path to the Planet data.

Returns:

  • typing.Literal['orthotile', 'scene'] –

    Literal["orthotile", "scene"]: The type of Planet data.

Raises:

  • ValueError –

    If the Planet data type cannot be parsed from the file path.

Source code in darts-acquisition/src/darts_acquisition/planet.py 
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def parse_planet_type(fpath: Path) -> Literal["orthotile", "scene"]:
    """Parse the type of Planet data from the directory path.

    Args:
        fpath (Path): The directory path to the Planet data.

    Returns:
        Literal["orthotile", "scene"]: The type of Planet data.

    Raises:
        ValueError: If the Planet data type cannot be parsed from the file path.

    """
    # Cases for Scenes:
    # - YYYYMMDD_HHMMSS_NN_XXXX
    # - YYYYMMDD_HHMMSS_XXXX

    # Cases for Orthotiles:
    # NNNNNNN/NNNNNNN_NNNNNNN_YYYY-MM-DD_XXXX
    # NNNNNNN_NNNNNNN_YYYY-MM-DD_XXXX

    assert fpath.is_dir(), "fpath must be the parent directory!"

    ps_name_parts = fpath.stem.split("_")

    if len(ps_name_parts) == 3:
        # Must be scene or invalid
        date, time, ident = ps_name_parts
        if _is_valid_date(date, "%Y%m%d") and _is_valid_date(time, "%H%M%S") and len(ident) == 4:
            return "scene"

    if len(ps_name_parts) == 4:
        # Assume scene
        date, time, n, ident = ps_name_parts
        if _is_valid_date(date, "%Y%m%d") and _is_valid_date(time, "%H%M%S") and n.isdigit() and len(ident) == 4:
            return "scene"
        # Is not scene, assume orthotile
        chunkid, tileid, date, ident = ps_name_parts
        if chunkid.isdigit() and tileid.isdigit() and _is_valid_date(date, "%Y-%m-%d") and len(ident) == 4:
            return "orthotile"

    raise ValueError(
        f"Could not parse Planet data type from {fpath}."
        f"Expected a format of YYYYMMDD_HHMMSS_NN_XXXX or YYYYMMDD_HHMMSS_XXXX for scene, "
        "or NNNNNNN/NNNNNNN_NNNNNNN_YYYY-MM-DD_XXXX or NNNNNNN_NNNNNNN_YYYY-MM-DD_XXXX for orthotile."
        f"Got {fpath.stem} instead."
        "Please ensure that the parent directory of the file is used, instead of the file itself."
    )