Source code for torchgeo.datasets.landsat
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
"""Landsat datasets."""
import abc
from typing import Any, Callable, Dict, List, Optional, Sequence
import matplotlib.pyplot as plt
from rasterio.crs import CRS
from .geo import RasterDataset
[docs]class Landsat(RasterDataset, abc.ABC):
"""Abstract base class for all Landsat datasets.
`Landsat <https://landsat.gsfc.nasa.gov/>`__ is a joint NASA/USGS program,
providing the longest continuous space-based record of Earth's land in existence.
If you use this dataset in your research, please cite it using the following format:
* https://www.usgs.gov/centers/eros/data-citation
If you use any of the following Level-2 products, there may be additional citation
requirements, including papers you can cite. See the "Citation Information" section
of the following pages:
* `Surface Temperature <https://www.usgs.gov/landsat-missions/landsat-collection-2-surface-temperature>`_
* `Surface Reflectance <https://www.usgs.gov/landsat-missions/landsat-collection-2-surface-reflectance>`_
* `U.S. Analysis Ready Data <https://www.usgs.gov/landsat-missions/landsat-collection-2-us-analysis-ready-data>`_
""" # noqa: E501
# https://www.usgs.gov/landsat-missions/landsat-collection-2
filename_regex = r"""
^L
(?P<sensor>[COTEM])
(?P<satellite>\d{2})
_(?P<processing_correction_level>[A-Z0-9]{4})
_(?P<wrs_path>\d{3})
(?P<wrs_row>\d{3})
_(?P<date>\d{8})
_(?P<processing_date>\d{8})
_(?P<collection_number>\d{2})
_(?P<collection_category>[A-Z0-9]{2})
_(?P<band>[A-Z0-9_]+)
\.
"""
separate_files = True
@property
@abc.abstractmethod
def default_bands(self) -> List[str]:
"""Bands to load by default."""
[docs] def __init__(
self,
root: str = "data",
crs: Optional[CRS] = None,
res: Optional[float] = None,
bands: Optional[Sequence[str]] = None,
transforms: Optional[Callable[[Dict[str, Any]], Dict[str, Any]]] = None,
cache: bool = True,
) -> None:
"""Initialize a new Dataset instance.
Args:
root: root directory where dataset can be found
crs: :term:`coordinate reference system (CRS)` to warp to
(defaults to the CRS of the first file found)
res: resolution of the dataset in units of CRS
(defaults to the resolution of the first file found)
bands: bands to return (defaults to all bands)
transforms: a function/transform that takes an input sample
and returns a transformed version
cache: if True, cache file handle to speed up repeated sampling
Raises:
FileNotFoundError: if no files are found in ``root``
"""
bands = bands or self.default_bands
self.filename_glob = self.filename_glob.format(bands[0])
super().__init__(root, crs, res, bands, transforms, cache)
[docs] def plot(
self,
sample: Dict[str, Any],
show_titles: bool = True,
suptitle: Optional[str] = None,
) -> plt.Figure:
"""Plot a sample from the dataset.
Args:
sample: a sample returned by :meth:`RasterDataset.__getitem__`
show_titles: flag indicating whether to show titles above each panel
suptitle: optional string to use as a suptitle
Returns:
a matplotlib Figure with the rendered sample
Raises:
ValueError: if the RGB bands are not included in ``self.bands``
.. versionchanged:: 0.3
Method now takes a sample dict, not a Tensor. Additionally, possible to
show subplot titles and/or use a custom suptitle.
"""
rgb_indices = []
for band in self.rgb_bands:
if band in self.bands:
rgb_indices.append(self.bands.index(band))
else:
raise ValueError("Dataset doesn't contain some of the RGB bands")
image = sample["image"][rgb_indices].permute(1, 2, 0).float()
# Stretch to the full range
image = (image - image.min()) / (image.max() - image.min())
fig, ax = plt.subplots(1, 1, figsize=(4, 4))
ax.imshow(image)
ax.axis("off")
if show_titles:
ax.set_title("Image")
if suptitle is not None:
plt.suptitle(suptitle)
return fig
[docs]class Landsat1(Landsat):
"""Landsat 1 Multispectral Scanner (MSS)."""
filename_glob = "LM01_*_{}.*"
default_bands = ["B4", "B5", "B6", "B7"]
rgb_bands = ["B6", "B5", "B4"]
[docs]class Landsat2(Landsat1):
"""Landsat 2 Multispectral Scanner (MSS)."""
filename_glob = "LM02_*_{}.*"
[docs]class Landsat3(Landsat1):
"""Landsat 3 Multispectral Scanner (MSS)."""
filename_glob = "LM03_*_{}.*"
[docs]class Landsat4MSS(Landsat):
"""Landsat 4 Multispectral Scanner (MSS)."""
filename_glob = "LM04_*_{}.*"
default_bands = ["B1", "B2", "B3", "B4"]
rgb_bands = ["B3", "B2", "B1"]
[docs]class Landsat4TM(Landsat):
"""Landsat 4 Thematic Mapper (TM)."""
filename_glob = "LT04_*_{}.*"
default_bands = ["SR_B1", "SR_B2", "SR_B3", "SR_B4", "SR_B5", "SR_B6", "SR_B7"]
rgb_bands = ["SR_B3", "SR_B2", "SR_B1"]
[docs]class Landsat5MSS(Landsat4MSS):
"""Landsat 4 Multispectral Scanner (MSS)."""
filename_glob = "LM04_*_{}.*"
[docs]class Landsat5TM(Landsat4TM):
"""Landsat 5 Thematic Mapper (TM)."""
filename_glob = "LT05_*_{}.*"
[docs]class Landsat7(Landsat):
"""Landsat 7 Enhanced Thematic Mapper Plus (ETM+)."""
filename_glob = "LE07_*_{}.*"
default_bands = ["SR_B1", "SR_B2", "SR_B3", "SR_B4", "SR_B5", "SR_B6", "SR_B7"]
rgb_bands = ["SR_B3", "SR_B2", "SR_B1"]
[docs]class Landsat8(Landsat):
"""Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS)."""
filename_glob = "LC08_*_{}.*"
default_bands = ["SR_B1", "SR_B2", "SR_B3", "SR_B4", "SR_B5", "SR_B6", "SR_B7"]
rgb_bands = ["SR_B4", "SR_B3", "SR_B2"]
[docs]class Landsat9(Landsat8):
"""Landsat 9 Operational Land Imager (OLI-2) and Thermal Infrared Sensor (TIRS-2).""" # noqa: E501
filename_glob = "LC09_*_{}.*"
