L8 Biome

class torchgeo.datasets.L8Biome(paths, crs=None, res=None, bands=('B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B9', 'B10', 'B11'), transforms=None, cache=True, download=False, checksum=False, time_series=False)

Bases: IntersectionDataset

L8 Biome dataset.

The L8 Biome dataset is a validation dataset for cloud cover assessment algorithms, consisting of Pre-Collection Landsat 8 Operational Land Imager (OLI) Thermal Infrared Sensor (TIRS) terrain-corrected (Level-1T) scenes.

Dataset features:

• Images evenly divided between 8 unique biomes

• 96 scenes from Landsat 8 OLI/TIRS sensors

• Imagery from global tiles between April 2013–October 2014

• 11 Level-1 spectral bands with 30 m per pixel resolution

Dataset format:

• Images are composed of single multiband geotiffs

• Labels are multiclass, stored in single geotiffs

• Quality assurance bands, stored in single geotiffs

• Level-1 metadata (MTL.txt file)

• Landsat 8 OLI/TIRS bands: (B1, B2, B3, B4, B5, B6, B7, B8, B9, B10, B11)

Dataset classes:

0. Fill

1. Cloud Shadow

2. Clear

3. Thin Cloud

4. Cloud

If you use this dataset in your research, please cite the following:

• https://doi.org/10.5066/F7251GDH

• https://doi.org/10.1016/j.rse.2017.03.026

Added in version 0.5.

__init__(paths, crs=None, res=None, bands=('B1', 'B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B8', 'B9', 'B10', 'B11'), transforms=None, cache=True, download=False, checksum=False, time_series=False)

Initialize a new L8Biome instance.

Parameters:

• paths (str | PathLike[str] | Iterable[str | PathLike[str]]) – one or more root directories to search or files to load

• crs (CRS | None) – coordinate reference system (CRS) to warp to (defaults to EPSG:3857)

• res (float | tuple[float, float] | None) – resolution of the dataset in units of CRS in (xres, yres) format. If a single float is provided, it is used for both the x and y resolution. (defaults to the resolution of the first file found)

• bands (Sequence[str]) – bands to return (defaults to all bands)

• transforms (Callable[[dict[str, Any]], dict[str, Any]] | None) – a function/transform that takes an input sample and returns a transformed version

• cache (bool) – if True, cache file handle to speed up repeated sampling

• download (bool) – if True, download dataset and store it in the root directory

• checksum (bool) – if True, check the MD5 of the downloaded files (may be slow)

• time_series (bool) – if True, stack data along the time series dimension [T, C, H, W]. If False, merge data into a [C, H, W] mosaic.

Raises:

DatasetNotFoundError – If dataset is not found and download is False.

Added in version 0.9: The time_series parameter.

plot(sample, show_titles=True, suptitle=None)

Plot a sample from the dataset.

Parameters:

• sample (dict[str, Any]) – a sample returned by RasterDataset.__getitem__()

• show_titles (bool) – flag indicating whether to show titles above each panel

• suptitle (str | None) – optional string to use as a suptitle

Returns:

a matplotlib Figure with the rendered sample

Raises:

RGBBandsMissingError – If bands does not include all RGB bands.

Return type:

Figure

__annotate_func__()

The type of the None singleton.