opticallyshallowdeep 1.0.0

Identify optically shallow and deep waters in satellite imagery

Optically-Shallow-Deep

This python tool delineates optically shallow and deep waters in Sentinel-2 imagery. The tool uses a deep neural network that was trained on a diverse set of global images.

Supported input includes L1C SAFE files and ACOLITE-processed L2R netCDF files. The output geotiff contains probabilities of water pixels being optically shallow and deep.

Output is a 3-band geotiff:

• B1: Binary prediction (OSW/ODW)
• B2: Prediction probability of OSW (100 means most likely OSW, 0 means most likely ODW)
• B3: pixels that are masked out

Originally coded by by Galen Richardson and Anders Knudby, modified and uploaded by Yulun Wu

Installation

1 - Create a conda environment and activate it:

conda create --name opticallyshallowdeep
conda activate opticallyshallowdeep

2 - Install tensorflow

For mac OS:

conda install -c apple tensorflow-deps
python -m pip install tensorflow-macos

(Optional) To utilize GPUs on mac OS:

python -m pip install tensorflow-metal

For windows:

python3 -m pip install tensorflow

More on installing tensorflow: https://www.tensorflow.org/install

3 - Install other dependencies:

conda install -c conda-forge geopandas rasterio tifffile netCDF4 pyproj

4 - Install opticallyshallowdeep:

python3 -m pip install opticallyshallowdeep

Quick Start

import opticallyshallowdeep as osd
file_in = 'test_folder_in/S2.SAFE'
folder_out = 'folder/test_folder_out'
osd.run(file_in, file_out)