The Arctic region is estimated to have 22% of the world’s oil and natural gas reserves, and a large portion of the natural resources in the Arctic are offshore and unexplored. As a result, more industrial activities are expected in this region in the future and supporting information for safe navigation is necessary.
Sentinel-1 SAR data represents invaluable and accurate information both in bad weather conditions and during polar nights. SAR images analysis for classification of ice types and drawing of ice charts have been considerably simplified through the emergence of a number of semi-automated and automated algorithms, developed for dual-polarization C-band SAR image segmentation and ice/water classification, for retrieval of ice concentration and for classification of several ice types.
In this webinar, we will use Sentinel-1 SAR data within the RUS environment, focusing on sea ice monitoring. We will use Snappy and Jupyter Notebooks to create sea ice concentration maps. Besides, we will concentrate on the retrieval of sea ice concentration, using texture analysis in the form of Gray-Level Co-occurrence Matrices (GLCMs), and supervised classification trained with existing ice chart data.
You can replay this webinar through our RUS Copernicus Training channel available on Youtube.
You can also retrieve the corresponding training support in the Train with RUS section of the RUS portal.