Tools to detect and track deformation features (leads and pressure ridges) in sea-ice deformation data.

A good description how to install python is given by N. Koldunov in: https://github.com/koldunovn/python_for_geosciences

After installing a miniconda you need to install to additional packages with:

conda install scipy.ndimage skimage

RGPS data in Lagrangian and Eulerian format need to be downloaded from Ron Kwok's homepage: https://rkwok.jpl.nasa.gov/radarsat/index.html

RGPS data needs to be unzip. The data needs to be orgnaized in a seperate directory for each winter that are named w9798, w9899, ...

Use gen_dataset.py to generate LKF data-sets, which performs three steps for each year:

• run the LKF detection on RGPS deformation data
• interpolate Lagrangian drift data to Eulerian grid
• run the LKF tracking algorithm

An in-depth description of the algorithm can be found here:

Hutter, N., Zampieri, L., and Losch, M.: Leads and ridges in Arctic sea ice from RGPS data and a new tracking algorithm, The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-207, accepted for publication, 2018. 

Nils Hutter [email protected]

GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007