Photometric characterization of the Asal-Ghoubbet rift (Republic of Djibouti) by massive inversion of the Hapke model

Numerous research projects have successfully exploited remote sensing data to analyze Earth and planetary surfaces. The use of radiative transfer models simulating the interaction between electromagnetic radiation and bare soils, such as the Hapke model, is becoming increasingly widespread. However, the in- version of these models is relatively uncommon due to a number of difficulties. To address these issues, our team has collected relevant field and satellite data from the Asal-Ghoubbet rift (Republic of Djibouti) and developed a comprehensive framework for analyzing these data. This site was chosen for the diversity of its terrains, characterized by varied albedo and surface roughness, which are well preserved due to the desert climate. It also has the advantage of being easily accessible (Labarre et al., 2019).

To carry out our study, we used images from the Pleiades-1B satellite captured in video mode over the Asal-Ghoubbet rift on January 26, 2013, during the in-flight commissioning of the satellite. This unique four-minute flyby produced 21 images at viewing angles ranging from from -56.7° to +52.6°. The images were corrected for atmospheric effects, which modify the photometric response of surfaces.  To achieve this, experts from CNES applied a variant of the MACCS ATCOR Joint Algorithm (MAJA), using auxiliary data to take into account the water vapor content and aerosol optical thickness (Hagolle et al., 2015). In addition, to validate the results of the Hapke model inversion, a field experiment was conducted in February 2016 in the Asal-Ghoubbet rift to collect soil samples and acquire data (ground truth).

To meet the challenge of limited geometric observation configurations, essential for constraining model parameters, our global approach tackled the known coupling effect between parameters. We also had to take into account the prohibitive computation time required to process millions of pixels over multiple spectral bands, which was a major obstacle to generating the Hapke parameter map. We applied the fast Bayesian inversion method developed by Kugler et al. (2022), which offers an efficient solution to overcome this problem. In parallel, a geometrical correction was applied using a previously constructed digital elevation model (DEM) of the rift that used the same data set. In the end, with each spectral band, we obtained four maps of Hapke model parameters corresponding to the single scattering albedo w, the photometric roughness θ, the asymmetry b and backscattering c parameters of the phase function. The areas of low reconstruction error (less than 1.5%) represents 70% of the entire region. The remainder can be attributed to areas with extremely steep slopes and heterogeneous terrains along slopes such as mass wasting deposits, or areas hindered by clouds and their associated shadows on the ground. The correlation between the parameters and the geological map, the analysis of the soil samples of each terrain units will be presented and discussed.