Document Type


Source of Publication

Frontiers in Environmental Science

Publication Date



In the present research, we carried out detailed chronological and compositional analyses along with detailed spectral analysis of three unnamed craters on the surface of Mars. Knowledge on chronology/age analysis and compositional analysis of Mars’ surface is essential for future manned and unmanned missions. The study area is near the landing site of previous landed missions, which could be used for future landing. The area is interesting to be studied because of its high elevation in the northeastern side and low elevation in the southern side, consisting of three major geological boundaries, i.e., Hesperian, Noachian, and Amazonian, which are further subdivided into fourteen units. Chronological investigations were carried out using the active machine learning approach and Craterstats 2.0 software, which revealed the age plot of 3.09 ± 0.04 Ga for Amazonian, 3.63 ± 0.0 Ga for Hesperian, and 3.73 ± 0.0 Ga for Noachian geological units, stating that N(1) craters’ density corresponds to the early Amazonian, early Hesperian, and late Noachian/early Hesperian periods according to the established crater density boundaries, respectively. Compact Reconnaissance Imaging Spectrometer for Mars (CRISM)-derived browse products are used for the compositional study of the surface characteristics of Mars. A spectral investigation was performed on an unnamed crater belonging to the Amazonian period, which showed to be majorly composed of oxides as the primary mineral, indicating the spectra of hematite, boehmite, and akaganeite. A Hesperian unit-unnamed crater shows the signature of monohydrated sulfates, melilite, illite, and kaolinite minerals in the region. For the unnamed crater 3, which belongs to the Noachian period, it has diagnostic absorptions of clay minerals in their extracted spectra, indicating the sign of long-term water–rock interactions in the period. Derived chronology results and compositional studies of craters help in better understanding the geological formation units of Mars’ surface.






Life Sciences


chronology, CSFD, geological processes, machine learning, Mars, mineralogy, spectroscopy

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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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Open Access


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Gold: This publication is openly available in an open access journal/series

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Life Sciences Commons