Dataset for Cloud Identification in Mars Daily Global Maps with Deep Learning

<p><strong>Overview:</strong></p> <p>This repository stores cloud masks and MDGMS for Martian Years (MYs) 28-33. MDGMs were obtained from&nbsp;Harvard Dataverse (<a href="https://doi.org/10.7910/DVN/U3766S">https://doi.org/10.7910/DVN/U3766S</a>), and cloud masks were created using the cloudmask model (<a href="https://github.com/03kalven/cloudmask">https://github.com/03kalven/cloudmask</a>). The cloud masks contained in the binary folders have already been binarized using the threshold of 0.912. This dataset is considerably smaller in size than the floating-point cloud mask dataset and is suited for researchers that prefer to use the default threshold of 0.912.</p> <p>&nbsp;</p> <p><strong>Quick breakdown of the files and folders:</strong></p> <ul> <li>phase folders contain the complete set of MDGMs and cloud masks for Mars Reconnaisance Orbiter mission phases P, B, G, D, F, and J (MYs 28-33)</li> <li>phase_binary folders contain the complete set of binary MDGMs and cloud masks for Mars Reconnaisance Orbiter mission phases P, B, G, D, F, and J (MYs 28-33)</li> <li>view_masks.ipynb has a few handy methods to plot cloud masks and MDGMs</li> </ul> <p>&nbsp;</p> <p><strong>Phase folders:</strong></p> <p>Each folder is organized based on phase (P, B, G, D, F, J) and subphase (_01 to _23). In each subphase, there are cloudmasks and mdgms folders, as well as a .txt file with MY and solar longitude (Ls) data for each day.</p> <p>&nbsp;</p> <p><strong>MDGM and cloud mask formats:</strong></p> <ul> <li>mdgm: JPEG, 3600x1801</li> <li>cloudmask: (NETCDF4_CLASSIC data model, file format HDF5): <ul> <li>dimensions(sizes): x(3600), y(1801)</li> <li>variables(dimensions): float32 longitude(x), float32 latitude(y), float32/int16 cloudmask(y, x)</li> </ul> </li> </ul> <p>The cloud masks&#39; values for any pixel are -999 for NaN and a float from 0 to 1 reporting the model&#39;s confidence in that pixel being a cloud. The cloud masks can be binarized using get_cloudmask()&nbsp;included in view_masks.ipynb. A binarized mask would report -999 for NaN, 0 for no cloud, and 1 for cloud. The default threshold is 0.912, but this value can be adjusted if desired. The cloud masks&#39; (0,0) coordinate is the lower left corner of the map, so it may be needed to flip the cloudmask vertically before plotting on a Martian map. The cloud mask NetCDF files are constructed the same way as&nbsp;Wang and Gonz&aacute;lez Abad&#39;s (<a href="https://doi.org/10.7910/DVN/WU6VZ8">https://doi.org/10.7910/DVN/WU6VZ8</a>).</p>