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Machine Learning enabled detections of Mg-spinel bearing lithology using Moon Mineralogy Mapper (M3) global coverage

Bhatt, Megha; Mall, Urs; Dhingra, Deepak +4 more

The new feldspathic rock type bearing Mg-spinel mineral has been detected at small localised areas of a few hundred meters [1,2,3,4] using Moon Mineralogy Mapper (M3) data from the Chandrayaan-1 mission [5, 6]. We have employed a one-dimensional convolutional neural network (CNN) to systematically identify and map the global distribution of this l…

Indian Planetary Missions and Science

Bhardwaj, Anil

The planetary exploration program in India started in the new millennium with the launch of Chandrayaan-1 orbiter mission to the Moon in 2008, which was a highly successful mission since it discovered water on the Moon. The next Indian planetary mission was to Mars: the Mars Orbiter Mission (MOM), launched in November 2013 and arriving on Mars in …

Recent volcanism and tectonism in the pre-Nectarian basins Grimaldi and Crüger-Sirsalis: Shreds of evidence from LRO, Chandrayaan-1, and Kaguya

Bhatt, Megha; Bhardwaj, Anil; Srivastava, Neeraj

Datasets from remote sensing missions such as Kaguya, LRO, GRAIL, and Chandrayaan-1 have substantially improved our understanding of the geology of the Moon by revealing new details about impact cratering, volcanism, and tectonism. Most of the late-stage (< 2.8 Ga) volcanic activities on the Moon occurred in the Procellarum KREEP Terrain (PKT).…

A novel method for lunar elemental abundance estimation using Chandrayaan-2 class and Chandrayaan-1 M3 data

Bhatt, Megha; Bhardwaj, Anil; Narendranath, Shyama +3 more

We report the first employment of the Chandryaan-2 Large Area Soft X-ray Spectrometer (CLASS) data [1] from Chandrayaan-2 mission as ground truth to estimate SiO2, Al2O3, and MgO for understanding the petrological characteristics of the Moon. The algorithm uses multivariate regression between CLASS derived elemental abundances from selected region…