ETCI2021 Flood Detection#

class torchgeo.datasets.ETCI2021(root='data', split='train', transforms=None, download=False, checksum=False)[source]#

Bases: NonGeoDataset

ETCI 2021 Flood Detection dataset.

The ETCI2021 dataset is a dataset for flood detection

Dataset features:

  • 33,405 VV & VH Sentinel-1 Synthetic Aperture Radar (SAR) images

  • 2 binary masks per image representing water body & flood, respectively

  • 2 polarization band images (VV, VH) of 3 RGB channels per band

  • 3 RGB channels per band generated by the Hybrid Pluggable Processing Pipeline (hyp3)

  • Images with 5x20m per pixel resolution (256x256) px) taken in Interferometric Wide Swath acquisition mode

  • Flood events from 5 different regions

Dataset format:

  • VV band three-channel png

  • VH band three-channel png

  • water body mask single-channel png where no water body = 0, water body = 255

  • flood mask single-channel png where no flood = 0, flood = 255

Dataset classes:

  1. no flood/water

  2. flood/water

If you use this dataset in your research, please add the following to your acknowledgements section:

The authors would like to thank the NASA Earth Science Data Systems Program,
NASA Digital Transformation AI/ML thrust, and IEEE GRSS for organizing
the ETCI competition.
__init__(root='data', split='train', transforms=None, download=False, checksum=False)[source]#

Initialize a new ETCI 2021 dataset instance.

Parameters:

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

  • split (str) – one of “train”, “val”, or “test”

  • 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

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

Raises:
__getitem__(index)[source]#

Return an index within the dataset.

Parameters:

index (int) – index to return

Returns:

data and label at that index

Return type:

dict[str, Any]

__len__()[source]#

Return the number of data points in the dataset.

Returns:

length of the dataset

Return type:

int

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

Plot a sample from the dataset.

Parameters:

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

Return type:

Figure

__annotate_func__()#

The type of the None singleton.