Although early Mars was likely periodically warm and wet, colder environments have dominated for most of its geologic history. Ice and glaciation in
particular have been major geologic agents throughout the later Hesperian and Amazonian eras and persist today, evidenced by widespread geomorphic
features such as glacier-like forms (GLFs) and polygonal ground. On Earth, cold climates can drive chemical weathering through alteration at the glacial
substrate as well as through more widespread periglacial freeze-thaw cycling and snowmelt. If glacial or periglacial melting was also significant on Mars,
we should expect to see substantiating mineralogical evidence preserved in the geologic record. However, spectroscopic investigations of mineralogy
associated with Amazonian glacial geomorphologies have been limited. To address this knowledge gap, this project will conduct a spectral survey of
GLFs on Mars using the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). For this project, the student will learn to use remote
sensing software packages such as JMARS and ENVI to: (1) import and combine existing databases of GLFs and global mineralogy, (2) produce a map
of global co-located detections of ice-related secondary mineralogy, and (3) down-select regions of interest (ROIs) and map individual glacial features
and mineral detections to better understand local context. The student will gain an understanding of planetary glaciological and geological processes,
gain an understanding of spectroscopy, and build skills in remote sensing techniques that can be applied to a variety of scientific questions.

The student will learn to use remote sensing software packages such as JMARS and ENVI to: (1) import and combine existing databases of GLFs and
global mineralogy, (2) produce a map of global co-located detections of ice-related secondary mineralogy, and (3) down-select regions of interest (ROIs)
and map individual glacial features and mineral detections to better understand local context. Task 1 is estimated to take 2 months of work at ~10
hours/week. The first four weeks will be spent learning to use the necessary software: doing initial trainings (pre-recorded and with the advisor on hand
for questions), running tutorials, practicing manipulating existing datasets, etc. The second four weeks will be spent sourcing, importing, and cleaning up
the existing datasets from previously published work, then running a subroutine to detect regions of overlap and exporting a new database of co-located
data. The advisor will support this work closely. Task 2 is estimated to take an additional month at 10 hours/week/ The goal of this task is to turn the colocation database into a viewable and useful map, supported by the advisor. The result of Task 2 will be a publishable figure, to be used in the student’s
submitted work. Task 3 is estimated to take 3-4 months in total. The student will select three regions of interest (ROIs) from the map produced in Task 2
for further analysis. ROI #1 analysis will be done over ~2 months at 10 hours/week, closely supervised by the advisor. This analysis will include
geomorphic mapping using published planetary mapping standards, as well as compositional mapping using spectral detections. This will result in a
publishable figure, to be used as part of the student’s final submitted work. Once the student is comfortable with this detailed mapping, they will map two
further ROIs, ideally resulting in two more publishable figures.

The student will ideally submit an abstract as first author to a conference in their second semester, such as the Lunar and Planetary Science Conference,
using their produced maps and figures as the basis for an abstract. The advisor will support them in the preparation of this abstract and in their final
presentation to the Space Grant Consortium. The student, if they are interested, will also help submit the database generated in Task 1 to the CASSIS
camera team to assist in targeting features of interest on Mars for future mapping.