Unsupervised Machine Learning on Domes in the Lunar Gardner Region: Implications for Dome Classification and Local Magmatic Activities on the Moon

Yuchao Chen,Xiangyun Hu,Jiannan Zhao,Qian Huang

doi:10.3390/rs13050845

Abstract

Lunar volcanic domes are essential windows into the local magmatic activities on the Moon. Classification of domes is a useful way to figure out the relationship between dome appearances and formation processes. Previous studies of dome classification were manually or semi-automatically carried out either qualitatively or quantitively. We applied an unsupervised machine-learning method to domes that are annularly or radially distributed around Gardner, a unique central-vent volcano located in the northern part of the Mare Tranquillitatis. High-resolution lunar imaging and spectral data were used to extract morphometric and spectral properties of domes in both the Gardner volcano and its surrounding region in the Mare Tranquillitatis. An integrated robust Fuzzy C-Means clustering algorithm was performed on 120 combinations of five morphometric (diameter, area, height, surface volume, and slope) and two elemental features (FeO and TiO2 contents) to find the optimum combination. Rheological features of domes and their dike formation parameters were calculated for dome-forming lava explanations. Results show that diameter, area, surface volume, and slope are the selected optimum features for dome clustering. 54 studied domes can be grouped into four dome clusters (DC1 to DC4). DC1 domes are relatively small, steep, and close to the Gardner volcano, with forming lavas of high viscosities and low effusion rates, representing the latest Eratosthenian dome formation stage of the Gardner volcano. Domes of DC2 to DC4 are relatively large, smooth, and widely distributed, with forming lavas of low viscosities and high effusion rates, representing magmatic activities varying from Imbrian to Eratosthenian in the northern Mare Tranquillitatis. The integrated algorithm provides a new and independent way to figure out the representative properties of lunar domes and helps us further clarify the relationship between dome clusters and local magma activities of the Moon.

Highlights

Lunar domes are low volcanic edifices that are similar to small and low shield volcanoes on the Earth and Mars
DC2 to DC4 domes are relatively large, smooth, and widely distributed, with forming lavas of relatively low viscosities and high effusion rates, representing magmatic activities varying from Imbrian to Eratosthenian in the northern Mare Tranquillitatis
Our study shows that D, A, surface volume (SV), and Slope are four optimum morphologic features for lunar domes clustering

Summary

Introduction

Lunar domes are low volcanic edifices that are similar to small and low shield volcanoes on the Earth and Mars. Mayer region), and on volcanic complexes such as Marius hills and Rümker hills in Oceanus Procellarum (e.g., [1,2,3,6,7,8,9,10,11]). Morphometric, spectral, and rheological studies of lunar domes have been carried out with lunar remote-sensing datasets (e.g., [1,2,3,6,9,10,11]). Morphological and rheological knowledge of domes, such as diameters and slopes of domes, and Remote Sens.

Results

Discussion

Conclusion