NLCD2016 Tree Canopy

torchgeo/datasets/__init__.py

@@ -74,6 +74,7 @@
 from .millionaid import MillionAID
 from .naip import NAIP
 from .nasa_marine_debris import NASAMarineDebris
+from .nlcd import NLCD2016TreeCanopy
 from .openbuildings import OpenBuildings
 from .oscd import OSCD
 from .patternnet import PatternNet
@@ -184,6 +185,7 @@
     "LoveDA",
     "MillionAID",
     "NASAMarineDebris",
+    "NLCD2016TreeCanopy",
     "OSCD",
     "PatternNet",
     "Potsdam2D",

torchgeo/datasets/nlcd.py

@@ -0,0 +1,86 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+"""National Agriculture Imagery Program (NAIP) dataset."""
+
+from typing import Any, Dict, Optional
+
+import matplotlib.pyplot as plt
+
+from .geo import RasterDataset
+
+
+class NLCD2016TreeCanopy(RasterDataset):
+    """National Land Cover Database 2016 (NLCD2016) - Tree Canopy dataset.
+
+    The `National Land Cover Database <https://www.mrlc.gov/>`_ provides 30m tree
+    canopy cover raster datasets generated by the United States Forest
+    Service (USFS). The data covers the conterminous United States, coastal Alaska,
+    Hawaii, and Puerto Rico and consists of continuous percent tree canopy estimates
+    for each pixel across all land covers. The data is derived from multi-spectral
+    Landsat imagery and other available ground and ancillary information.
+
+    If you use this dataset in your research, please cite it using the following format:
+
+    * https://doi.org/10.14358/PERS.78.7.715
+
+    .. note::
+
+       This dataset can be automatically downloaded and converted to geotiffs from the
+       ERDAS IMAGINE .img format using the following bash script:
+
+       .. code-block:: bash
+
+          wget "https://s3-us-west-2.amazonaws.com/mrlc/nlcd_2016_treecanopy_2019_08_31.zip"
+          wget "https://s3-us-west-2.amazonaws.com/mrlc/nlcd_tcc_hi_2016.zip"
+          wget "https://s3-us-west-2.amazonaws.com/mrlc/nlcd_tcc_coastalAK_2016.zip"
+          wget "https://s3-us-west-2.amazonaws.com/mrlc/nlcd_tcc_prusvi_2016.zip"
+          unzip nlcd_2016_treecanopy_2019_08_31.zip
+          unzip nlcd_tcc_hi_2016.zip
+          unzip nlcd_tcc_coastalAK_2016.zip
+          unzip nlcd_tcc_prusvi_2016.zip
+          gdal_translate -co COMPRESS=LZW -of GTiff nlcd_2016_treecanopy_2019_08_31.img nlcd_2016_treecanopy_2019_08_31.tif
+          gdal_translate -co COMPRESS=LZW -of GTiff nlcd_2016_hi_treecanopy_20191018.img nlcd_2016_hi_treecanopy_20191018.tif
+          gdal_translate -co COMPRESS=LZW -of GTiff nlcd_2016_coastal_alaska_treecanopy.img nlcd_2016_coastal_alaska_treecanopy.tif
+          gdal_translate -co COMPRESS=LZW -of GTiff nlcd_2016_prusvi_treecanopy_20191017.img nlcd_2016_prusvi_treecanopy_20191017.tif
+
+       or manually downloaded from https://www.mrlc.gov/data
+
+    .. versionadded:: 0.5
+    """  # noqa: E501
+
+    is_image = False
+    filename_glob = "nlcd_2016*.tif"
+    filename_regex = r"""
+        (?P<name>[nlcd_2016]{9})*
+    """
+
+    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
+        """
+        image = sample["mask"][0, :, :]
+
+        fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(4, 4))
+
+        ax.imshow(image, cmap="Greens")
+        ax.axis("off")
+        if show_titles:
+            ax.set_title("Mask")
+
+        if suptitle is not None:
+            plt.suptitle(suptitle)
+
+        return fig