Speaker
Description
The searching for ephemeral liquid water on Mars is an ongoing activity. After the recession of the seasonal polar ice cap on Mars, small water ice patches may be left behind in shady places due to the low thermal conductivity of the Martian surface and atmosphere. During the southern summer, these patches may be exposed to direct sunlight and warm up rapidly enough for the liquid phase to emerge.
A manual analysis on the screen was conducted on 110 images captured by the High Resolution Imaging Science Experiment (HiRISE) camera onboard the Mars Reconnaissance Orbiter space mission. Out of these, 37 images were identified with smaller ice patches, which were distinguishable by their brightness, colour and strong connection to local topographic shading. The seasonal occurrence of these patches range between 140° and 200° solar longitude, in geographical location in the latitude band between -40° and -60°, with having diameters ranging from 1.5-300 meters.
In this study, a convolutional neural network (CNN) is applied to find further images with potential water ice patches in the given latitude band. Previously analysed HiRISE images are used to train the model, each chunked into hundreds of pieces, significantly expanding the dataset. Using a CNN model makes it realistic to analyse all available surface images, aiding us in selecting areas for further investigation.
