Western USA Live Fuel Moisture#

class torchgeo.datasets.WesternUSALiveFuelMoisture(root='data', input_features=('slope(t)', 'elevation(t)', 'canopy_height(t)', 'forest_cover(t)', 'silt(t)', 'sand(t)', 'clay(t)', 'vv(t)', 'vh(t)', 'red(t)', 'green(t)', 'blue(t)', 'swir(t)', 'nir(t)', 'ndvi(t)', 'ndwi(t)', 'nirv(t)', 'vv_red(t)', 'vv_green(t)', 'vv_blue(t)', 'vv_swir(t)', 'vv_nir(t)', 'vv_ndvi(t)', 'vv_ndwi(t)', 'vv_nirv(t)', 'vh_red(t)', 'vh_green(t)', 'vh_blue(t)', 'vh_swir(t)', 'vh_nir(t)', 'vh_ndvi(t)', 'vh_ndwi(t)', 'vh_nirv(t)', 'vh_vv(t)', 'slope(t-1)', 'elevation(t-1)', 'canopy_height(t-1)', 'forest_cover(t-1)', 'silt(t-1)', 'sand(t-1)', 'clay(t-1)', 'vv(t-1)', 'vh(t-1)', 'red(t-1)', 'green(t-1)', 'blue(t-1)', 'swir(t-1)', 'nir(t-1)', 'ndvi(t-1)', 'ndwi(t-1)', 'nirv(t-1)', 'vv_red(t-1)', 'vv_green(t-1)', 'vv_blue(t-1)', 'vv_swir(t-1)', 'vv_nir(t-1)', 'vv_ndvi(t-1)', 'vv_ndwi(t-1)', 'vv_nirv(t-1)', 'vh_red(t-1)', 'vh_green(t-1)', 'vh_blue(t-1)', 'vh_swir(t-1)', 'vh_nir(t-1)', 'vh_ndvi(t-1)', 'vh_ndwi(t-1)', 'vh_nirv(t-1)', 'vh_vv(t-1)', 'slope(t-2)', 'elevation(t-2)', 'canopy_height(t-2)', 'forest_cover(t-2)', 'silt(t-2)', 'sand(t-2)', 'clay(t-2)', 'vv(t-2)', 'vh(t-2)', 'red(t-2)', 'green(t-2)', 'blue(t-2)', 'swir(t-2)', 'nir(t-2)', 'ndvi(t-2)', 'ndwi(t-2)', 'nirv(t-2)', 'vv_red(t-2)', 'vv_green(t-2)', 'vv_blue(t-2)', 'vv_swir(t-2)', 'vv_nir(t-2)', 'vv_ndvi(t-2)', 'vv_ndwi(t-2)', 'vv_nirv(t-2)', 'vh_red(t-2)', 'vh_green(t-2)', 'vh_blue(t-2)', 'vh_swir(t-2)', 'vh_nir(t-2)', 'vh_ndvi(t-2)', 'vh_ndwi(t-2)', 'vh_nirv(t-2)', 'vh_vv(t-2)', 'slope(t-3)', 'elevation(t-3)', 'canopy_height(t-3)', 'forest_cover(t-3)', 'silt(t-3)', 'sand(t-3)', 'clay(t-3)', 'vv(t-3)', 'vh(t-3)', 'red(t-3)', 'green(t-3)', 'blue(t-3)', 'swir(t-3)', 'nir(t-3)', 'ndvi(t-3)', 'ndwi(t-3)', 'nirv(t-3)', 'vv_red(t-3)', 'vv_green(t-3)', 'vv_blue(t-3)', 'vv_swir(t-3)', 'vv_nir(t-3)', 'vv_ndvi(t-3)', 'vv_ndwi(t-3)', 'vv_nirv(t-3)', 'vh_red(t-3)', 'vh_green(t-3)', 'vh_blue(t-3)', 'vh_swir(t-3)', 'vh_nir(t-3)', 'vh_ndvi(t-3)', 'vh_ndwi(t-3)', 'vh_nirv(t-3)', 'vh_vv(t-3)', 'lat', 'lon'), transforms=None, download=False)[source]#

Bases: NonGeoDataset

Western USA Live Fuel Moisture Dataset.

This tabular style dataset contains fuel moisture (mass of water in vegetation) and remotely sensed variables in the western United States. It contains 2615 datapoints and 138 variables. For more details see the dataset page.

Dataset Format:

  • .geojson file for each datapoint

Dataset Features:

  • 138 remote sensing derived variables, some with a time dependency

  • 2615 datapoints with regression target of predicting fuel moisture

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

Note

This dataset requires the following additional library to be installed:

  • azcopy: to download the dataset from Source Cooperative.

Added in version 0.5.

__init__(root='data', input_features=('slope(t)', 'elevation(t)', 'canopy_height(t)', 'forest_cover(t)', 'silt(t)', 'sand(t)', 'clay(t)', 'vv(t)', 'vh(t)', 'red(t)', 'green(t)', 'blue(t)', 'swir(t)', 'nir(t)', 'ndvi(t)', 'ndwi(t)', 'nirv(t)', 'vv_red(t)', 'vv_green(t)', 'vv_blue(t)', 'vv_swir(t)', 'vv_nir(t)', 'vv_ndvi(t)', 'vv_ndwi(t)', 'vv_nirv(t)', 'vh_red(t)', 'vh_green(t)', 'vh_blue(t)', 'vh_swir(t)', 'vh_nir(t)', 'vh_ndvi(t)', 'vh_ndwi(t)', 'vh_nirv(t)', 'vh_vv(t)', 'slope(t-1)', 'elevation(t-1)', 'canopy_height(t-1)', 'forest_cover(t-1)', 'silt(t-1)', 'sand(t-1)', 'clay(t-1)', 'vv(t-1)', 'vh(t-1)', 'red(t-1)', 'green(t-1)', 'blue(t-1)', 'swir(t-1)', 'nir(t-1)', 'ndvi(t-1)', 'ndwi(t-1)', 'nirv(t-1)', 'vv_red(t-1)', 'vv_green(t-1)', 'vv_blue(t-1)', 'vv_swir(t-1)', 'vv_nir(t-1)', 'vv_ndvi(t-1)', 'vv_ndwi(t-1)', 'vv_nirv(t-1)', 'vh_red(t-1)', 'vh_green(t-1)', 'vh_blue(t-1)', 'vh_swir(t-1)', 'vh_nir(t-1)', 'vh_ndvi(t-1)', 'vh_ndwi(t-1)', 'vh_nirv(t-1)', 'vh_vv(t-1)', 'slope(t-2)', 'elevation(t-2)', 'canopy_height(t-2)', 'forest_cover(t-2)', 'silt(t-2)', 'sand(t-2)', 'clay(t-2)', 'vv(t-2)', 'vh(t-2)', 'red(t-2)', 'green(t-2)', 'blue(t-2)', 'swir(t-2)', 'nir(t-2)', 'ndvi(t-2)', 'ndwi(t-2)', 'nirv(t-2)', 'vv_red(t-2)', 'vv_green(t-2)', 'vv_blue(t-2)', 'vv_swir(t-2)', 'vv_nir(t-2)', 'vv_ndvi(t-2)', 'vv_ndwi(t-2)', 'vv_nirv(t-2)', 'vh_red(t-2)', 'vh_green(t-2)', 'vh_blue(t-2)', 'vh_swir(t-2)', 'vh_nir(t-2)', 'vh_ndvi(t-2)', 'vh_ndwi(t-2)', 'vh_nirv(t-2)', 'vh_vv(t-2)', 'slope(t-3)', 'elevation(t-3)', 'canopy_height(t-3)', 'forest_cover(t-3)', 'silt(t-3)', 'sand(t-3)', 'clay(t-3)', 'vv(t-3)', 'vh(t-3)', 'red(t-3)', 'green(t-3)', 'blue(t-3)', 'swir(t-3)', 'nir(t-3)', 'ndvi(t-3)', 'ndwi(t-3)', 'nirv(t-3)', 'vv_red(t-3)', 'vv_green(t-3)', 'vv_blue(t-3)', 'vv_swir(t-3)', 'vv_nir(t-3)', 'vv_ndvi(t-3)', 'vv_ndwi(t-3)', 'vv_nirv(t-3)', 'vh_red(t-3)', 'vh_green(t-3)', 'vh_blue(t-3)', 'vh_swir(t-3)', 'vh_nir(t-3)', 'vh_ndvi(t-3)', 'vh_ndwi(t-3)', 'vh_nirv(t-3)', 'vh_vv(t-3)', 'lat', 'lon'), transforms=None, download=False)[source]#

Initialize a new Western USA Live Fuel Moisture Dataset.

Parameters:

  • root (str | PathLike[str]) – root directory where dataset can be found

  • input_features (Iterable[str]) – which input features to include

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

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

Raises:
__len__()[source]#

Return the number of data points in the dataset.

Returns:

length of the dataset

Return type:

int

__getitem__(index)[source]#

Return an index within the dataset.

Parameters:

index (int) – index to return

Returns:

input features and target at that index

Return type:

dict[str, Any]

plot(sample, variables_to_plot=None, show_titles=True, suptitle=None)[source]#

Plot a time series visualization of the LFMC sample.

Parameters:

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

  • variables_to_plot (list[str] | None) – a list of valid variable to be drawn in the plot

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

  • suptitle (str | None) – optional suptitle to use for the Figure

Returns:

a matplotlib Figure with the rendered sample

Return type:

Figure

Added in version 0.8.