Example dataset of EOPatches for Slovenia 2017

Official Bucket Link:


Foreword

This example dataset will help you get started with Remote Sensing data and analysis in the open-source framework of eo-learn.

To promote the use of eo-learn, we have decided to share a dataset of EOPatches for the whole region of Slovenia for the year 2017. This data can be used in remote sensing applications, such as land cover classification.

See our Land Cover Classification blog posts!

Bucket Content

The contents of this AWS S3 bucket are the following:

Content Description

The full dataset contains 293 EOPatches of the size of about 1000 x 1000 pixels at 10 m resolution, while the sample dataset contains 4 EOPatches from a 2x2 grid.

Each EOPatch is a container of EO and non-EO data. You can load an EOPatch in eo-learn with the following command:
EOPatch.load('path_to_eopatches/eopatch-0x6/')
You will obtain the EOPatch of the following structure:
EOPatch(
     data: {
      BANDS: numpy.ndarray(shape=(80, 1010, 999, 6), dtype=float32)
     }
     mask: {
      CLM: numpy.ndarray(shape=(80, 1010, 999, 1), dtype=uint8)
      IS_DATA: numpy.ndarray(shape=(80, 1010, 999, 1), dtype=uint8)
      IS_VALID: numpy.ndarray(shape=(80, 1010, 999, 1), dtype=bool)
     }
     mask_timeless: {
      LULC: numpy.ndarray(shape=(1010, 999, 1), dtype=uint8)
      VALID_COUNT: numpy.ndarray(shape=(1010, 999, 1), dtype=int64)
     }
     meta_info: {
      maxcc: 0.8
      service_type: 'wcs'
      size_x: '10m'
      size_y: '10m'
      time_difference: datetime.timedelta(-1, 86399)
      time_interval: (datetime.datetime(2017, 1, 1, 0, 0), datetime.datetime(2017, 12, 31, 0, 0))
     }
     bbox: BBox(((370230.5261411405, 5085303.344972428), (380225.31836121203, 5095400.767924464)), crs=EPSG:32633)
     timestamp: [datetime.datetime(2017, 1, 1, 10, 4, 7), ..., datetime.datetime(2017, 12, 25, 10, 15, 32)], length=80
    )
It is possible to then access various EOPatch content via calls like:
eopatch.timestamp
eopatch.mask['LULC']
eopatch.data['CLM'][0]
eopatch.data['BANDS'][5][..., [3, 2, 1]]