Conference Agenda

Introduction: The Lunar South Pole is characterised by extreme topography creating many Permanently Shadowed Regions (PSRs) which remain beyond the reach of optical imagery, making it difficult to fully explore the surface. The Indian Space Research Organisation’s (ISRO) Chandrayaan-2 mission carries a Dual Frequency SAR (DFSAR) with the capabilities to generate Fully Polarimetric L-band and S-band products, with L-band data being particularly advantageous due to the expected penetration depth of up to 5m in dry, low loss soils [1]. Polarimetric analysis of the imaged surface can provide extensive information about the scattering mechanisms present on both the surface and within the subsurface. With the presence and distribution of water-ice a central objective of NASA’s Artemis III mission, Chandrayaan-2’s high resolution SAR datasets can provide an opportunity to enhance our understanding of water-ice deposits at the Lunar South Pole.

A new, novel way of assessing the spatial distribution of water-ice desposits using radar data is by adapting the Water Cloud model (WCM) for use on the Lunar surface [2]. The model, which is traditionally used in Terrestrial applications to separate surface and volume scattering components, is edited and reinterpreted to consider volume under surface and evaluate the expected volumetric scattering signature from subsurface water-ice.

Methodology: We represent the scattering matrix as a Pauli vector and generate the 4x4 Coherency [T] matrix [3] which allows us to visualize the products of the Pauli Decomposition and perform the Claude-Pottier decomposition in Slant Range geometry. Work is currently being completed on geometrically projecting the products for better visualization and analysis. The Pauli vector k allows us to differentiate between surface scattering, dihedral structure scattering, and oriented dihedral or volumetric scattering.

The Claude-Pottier decomposition using the 4x4 Coherency matrix allows us to identify the thermal noise component, which can then be removed from the data [3]. Thermal noise removal significantly improved the polarimetric interpretation, since the SNR of the images was particularly low (corrupting polarimetric information). After noise removal, specific parameters such as H (entropy), which provides information on the disorder of scattering, and α (alpha angle) which indicates if the scattering is dominated by either surface, double-bounce or volumetric interactions, are useful indicators to better understand the properties of the surface and subsurface.

To model the distribution of water-ice, backscatter coefficients are modelled using the WCM with parameters that are expected on the Lunar surface [2]. The model coefficients A-D were optimized through least -square fitting between the observed and modelled version of backscatter, with incidence angle and dielectric constant as inputs to the model. This was then inverted using a generated look-up table (LUT) to estimate the volumetric scattering components across the localized region. Further work is being done on the WCM using FP datasets, and including novel ways to decompose scattering components as described in the POLinSAR abstract submitted by the co-author A. Marino (Testing different methodologies to decompose PolSAR data into a Focus partial target plus a Residual one (1F+R)).

Initial Results: Much of the Lunar surface at the South Pole when viewed with the Pauli decomposition exhibits surface scattering, which is to be expected. Regions around craters, such as the rims and ejecta, present strongly volumetric components, specifically in regions inside the crater walls. This is significant due to the shallow penetration depth of L-band, and the predicted subsurface water ice deposits within the PSRs. Additionally, it can be seen using H and α that these regions are completely depolarising, similar to the areas where volumetric signals are observed. We are currently applying further tests to check if this high entropy targets are indeed volumetric or a mix of close scatterers (increasing entropy, as it is in for Earth artificial targets) or geometry-induced effects in the slant-range plane. If volumetric, this would mean that the subsurface material, be it water-ice deposits or buried boulders, is distributed throughout the walls and not in specific regions.

Acknowledgments: We acknowledge the use of data from the Chandrayaan-II, second lunar mission of the Indian Space Research Organisation (ISRO), archived at the Indian Space Science Data Centre (ISSDC). UK Space Agency for funding this project; grant no. ST/Y005384/1 as part of the UK Government’s Science Bilateral Programme.

References: [1] Bhiravarasu S. S. et al. (2021) Planet. Sci. J., 2, 134. [2] Attema E. P. W. and Ulaby F. T. (1978) Radio Science, 13, 2. [3] Lee J. S. and Pottier E. (2017) CRC press.