Developed by Cole Speed and Yiran Shen, The University of Texas at Austin
This repository contains all necessary files and documentation for automated Martian dune field classification using deep learning. A convolutional neural network-based (Unet) model is developed in order to classify pixels in satellite images that do and do not capture Martian dune fields. Training and validation data consist of high-resolution satellite imagery acquired by the The Thermal Emission Imaging System (THEMIS) on the Mars Reconnaissance Oribiter. Labels for training are hand-mapped dune field polygons obtained from The Mars Global Digital Dune Database (USGS).