To automate the generation of sea ice information from satellite imagery we use a Convolutional Neural Network (CNN) designed for prediction of sea ice in Greenland waters. Automating the process on SAR data alone is challenging. SAR images show patterns related to ice formations, but backscatter intensities can be ambiguous, which complicates the discrimination between ice and open water, e.g. at high wind speeds. Our CNN model tackles the challenges by fusing Sentinel-1 active microwave (SAR) data with Microwave Radiometer (MWR) data from AMSR2 to exploit the advantages of both instruments. While SAR data has ambiguities, it has a very high spatial resolution, whereas MWR data has good contrast between open water and ice. However, the coarse resolution of the AMSR2 MWR observations introduces a new set of obstacles, e.g. land spill-over, which can lead to erroneous sea ice predictions along the coastline adjacent to open water. The CNN model has been trained with a large dataset of 461 ice charts manually produced by the ice analysts in the DMI Greenland Ice Service based on Sentinel-1 imagery. The dataset also contains the
corresponding AMSR2 swath co-located with the ice charts and Sentinel-1 images. The sea ice training dataset (https://doi.org/10.11583/DTU.13011134.v2) has been co-produced in the ASIP and AI4Arctic (ESA) projects. We will present the results of merging active and passive microwave data from Sentinel-1 and AMSR2 as input to a CNN and show how the input from the passive microwave data has a positive effect on the CNN performance. Furthermore, we will discuss the benefits and improvements that can be expected with the higher resolution CIMR observations and give inputs to the requirements for simulated CIMR test data in the context of CNN development. The CNN model is in production at DMI and its ice products have been tested with users in the Fall of 2020.
|Number of pages||2|
|Publication status||Published - 2021|
|Event||From Science to Operations for the Copernicus Imaging Microwave Radiometer (CIMR) Mission - Online event, Noordwijk, Netherlands|
Duration: 15 Apr 2020 → 17 Apr 2020
|Seminar||From Science to Operations for the Copernicus Imaging Microwave Radiometer (CIMR) Mission|
|Period||15/04/2020 → 17/04/2020|