Environment and Agrifood

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Browsing Environment and Agrifood by Subject "'Aerial photography'"

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    Very high resolution aerial photography and annotated land cover data of the Peak District National Park
    (Cranfield University, 2023-11-06 17:08) van der Plas, Thijs; Geikie, Simon; Alexander, David; Simms, Daniel
    License Contents of compressed file (zip) from Van der Plas, Geikie, Alexander and Simms, upcoming publication titled Multi-stage semantic segmentation quantifies fragmentation of small habitats at a landscape scale This data set contains the RGB image data and human land cover annotation for 1027 patches of 512 pixels x 512 pixels ( 64 m x 64 m spatial resolution). For more information on how the data can be used, the land cover schema and other details, please see our paper. For code examples of how to use the data, please see the github repository at https://github.com/pdnpa/cnn-land-cover The data is given in two formats: python and tiff. The Python format can be directly loaded by the code in the repository into Pytorch DataLoaders. The tiff format is independent of progamming language and application. This data is released under the CC BY 4.0 license, which means if you use this data set, we ask you to cite along with our paper above.If you use the RGB images, you must acknowledge the following copyright: "Aerial Photography for Great Britain, © Bluesky International Limited and Getmapping Plc [2022]" - README land cover patch data.txt - lc_label_names.json contains mapping from land cover label (integer) to land cover class name - python_format - images_python_all all (train and test) RGB images in .npy format (each of shape (3, 512, 512)) - masks_python_all all (train and test) land cover masks in .npy format (each of shape (512, 512)) - train_test_split_80tiles_2023-03-22-2131.json train/test split in json format - train_test_split_80tiles_2023-03-22-2131.pkl train/test split in pickle format (to be used with the data class in the repository) - tiff_format - images_masks_tiff_train train set only patches, containing both the RGB image (first 3 bands) and the land cover annotation (4th band) (each of shape (4, 512, 512)) - images_masks_tiff_test test set only patches, containing both the RGB image (first 3 bands) and the land cover annotation (4th band) (each of shape (4, 512, 512))