Retrieve sea ice types from corrected Sentinel-1 SAR with convolutional neural networks.
- Start the official Tensorflow Docker container:
docker run -v $PWD:/tf --rm -it -p 8888:8888 tensorflow/tensorflow:latest-jupyter
- Open the provided URL in a browser and open the notebook "cnn_for_sea_ice_types.ipynb"
- Execute the cells
-
Build image s1denoised as explained here: https://github.com/nansencenter/sentinel1denoised/
-
Build image s1icetype using Dockerfile from this repository:
docker build . -t s1icetype -
Run thermal noise, texture noise and angular corrections
docker run --rm -it \
-v /path/to/s1/files:/data \
s1icetype \
s1_correction.py \
/data/S1B_EW_GRDM_1SDH_20200323T053203_20200323T053303_020815_027780_8729.zip \
/data/S1B_EW_GRDM_1SDH_20200323T053203.tif
- Run the ice type algorithm (mounted directory names can be anything)
docker run --rm -it \
-v /path/to/cnn/file:/cnn \
-v /path/to/s1/files:/data \
s1icetype \
get_icetype.py /cnn/cnn_weights.hdf5 \
/data/S1B_EW_GRDM_1SDH_20200323T053203.tif /data/S1B_EW_GRDM_1SDH_20200323T053203_icetype.tif
-
Create environment s1denoise for S1 correction as explained here: https://github.com/nansencenter/sentinel1denoised/
-
Activate environment s1denoise and install tensorflow 2.1.0
conda activate s1denoise
conda install tensorflow=2.1.0
- Run thermal noise, texture noise and angular corrections
s1_correction.py S1B_EW_GRDM_1SDH_20200323T053203_20200323T053303_020815_027780_8729.zip S1B_EW_GRDM_1SDH_20200323T053203.tif
- Run ice type algorithm
./get_icetype.py cnn_weights.hdf5 S1B_EW_GRDM_1SDH_20200323T053203.tif S1B_EW_GRDM_1SDH_20200323T053203_icetype.tif