Synthetic-Aperture Radar (SAR) based Ice types/Ice edge dataset for deep learning analysis

• Main Authors: Khaleghian, Salman, Lohse, Johannes Philipp, Kræmer, Thomas
• Format: Other/Unknown Material
• Language: English
• Published: DataverseNO 2020
• Subjects: Computer and Information Science; Earth and Environmental Sciences; Engineering; Physics; Deep Learning; Remote Sensing; Ice types; Ice Edge; Synthetic-aperture radar; Pancake; Svalbard
• Online Access: https://doi.org/10.18710/QAYI4O

This dataset has been prepared for Ice types/Ice edge analysis based on deep neural networks. The dataset has been created based on 31 scenes in north of Svalbard based on labeled polygons. The dataset contains six classes including OpenWater, Leads with water, Brash/Pancake Ice, Thin Ice, Thick Ice-Flat and Thick Ice-Ridged. The data records, called patches, extracted all from inside of each polygon with stride 10 in different sizes, 10x10, 20x20, 32x32, 36x36, 46x46 pixels for each class