Planetary mapping
- Hyperspectral Python (HypPy) is a software package written in Python for the processing of hyperspectral data, developed in ITC’s Department of Earth Systems Analysis. See: http://hyppy.is-great.org/
- Suggested elective course:
- Python Solutions, or any basic course in Python programming would be recommended.
Hyperspectral images are, amongst others, used for mineral mapping of drill cores, mapping hydrothermal alteration zones, and searching for mineralogic indications of past and present water on Mars. The data volumes involved are huge. The challenge is to develop algorithms that can efficiently map and quantify the mineralogy. Methods that could be applied include pre-classification methods such as wavelength mapping, methods similar to the ones applied in spectral analysts as available in ENVI and TSG, applying decision trees, or methods applying pure classifiers like SVM.
For this research topic the following main research question(s) could be considered:
- Develop a method for mapping minerals or interesting features on a planet, moon, asteroid or comet of choice.
- Develop a method for assessing the validity of your result.
The method could be tested using the following:
- Hyperspectral image data from solar system probes (such as from Mars, the Moon, Ceres, or Comet 67P).
- Image data from other sources such as radar, panchromatic and thermal images.
- Data from other sources such as neutron spectrometer data.
The method could be implemented using standard software tools, or developed using open-source software, such as HypPy (see Additional Remarks below).