Subset of 300 out of 3000 Prepared Sentinel 2 Scenes for Transfer Learning and Super-sampling.

<p>This dataset contains a random subset of 300 out of 3000 Sentinel 2 scenes prepared for Transfer Learning and Super-sampling. It comes in the form of zipped NumPy arrays in the npz format. The files have are named in the following fashion:</p> <p>latutide+latitude_decimals_longitude+longitude_decimals_month_of_the_year_for_mosaic.&nbsp;</p> <p>Each file contains:</p> <p>bands.npy: The Sentinel 2 bands in 10m resolution uint10: B02, B03, B04, B08, B05, B06, B07, B8A, B11, B12. The 20m bands have been resampled using bilinear resampling.</p> <p>nir.npy: B08 Resampled to 20m using average resampling and then resampled to 10m using bilinear. Useful for training super-sampling models.</p> <p>scl.npy: The Sentinel 2 Scene Classification file. Contains information on cloud cover and land cover.</p> <p>sincos.npy: Contains the latitude, longitude, and time of capture for each pixel encoded to sine and cosine waves in the [0,1] interval. The is useful when training a model to predict where on the globe an image was captured.</p> <p>The images can be processed to patches using the buteo toolbox:&nbsp;</p> <p>`pip install buteo --upgrade</p> <p>`import buteo as beo`</p> <p>`beo.get_patches(beo.raster_to_array(&quot;path_to_bands&quot;))`</p> <p>&nbsp;</p>