Retrieval of Sediment Fill Factor by Inversion of a Modified Hapke Model Applied to Sampled HCRF from Airborne and Satellite Imagery

Abstract

The physical properties of a medium such as density, grain size and surface roughness all influence the angular dependence of spectral signatures. Radiative transfer models, such as the one developed by Hapke, can relate the angular dependence of the reflectance to these geophysical variables. This paper focuses on extracting geophysical parameters, fill factor (decreasing porosity) and the single scattering albedo (SSA), through the inversion of a modified version of the Hapke model of airborne and space-borne imagery. The inversion methodology was validated through controlled experiments within a laboratory setting, where a good correlation (R 2 = 0.72) between the retrieved fill factor and the measured density was obtained. Using the same approach, we also retrieved the sediment fill factor and SSA from airborne data collected by the NASA G-LiHT system, and space-borne data observed by the NOAA GOES imager. The results from these studies provide a mechanism to understand geophysical characteristics of the terrain and may potentially be used for long-term monitoring of the dynamic dunes system.

Retrieval of Sediment Filling Factor in a Salt Panne from Multi-View Hyperspectral Imagery

“…This multi-stage optimization procedure also optimized other model parameters such as those parameterizing the phase function, and opposition effect. Eon, Bachmann, and Gerace [9] built on this approach extending it to multi-view hyperspectral imagery of the Algodones Dunes obtained by the NASA G-LiHT hyperspectral imaging (HSI) system [13]. Since roughly one-third of of the land surface on Earth is either desert or a similar arid environment [14], where granular sediments predominate, radiative transfer models that describe surfaces with significant granular content can play an important role in remote sensing analysis and in the inversion of surface parameters.…”

“…Radiative transfer models have been a centerpiece of these studies with the Hapke model [1] having been among the more frequently used models in past studies. Hapke's Isotropic Multiple Scattering Approximation (IMSA) [1] model and his later Modified IMSA (MIMSA) [1,5] have been widely used, especially to model the interaction of light with granular sediments [6][7][8][9]. Jacquemoud et al [6] investigated laboratory spectral data for 26 different soil samples of varying soil type by inverting an an early version of IMSA predating Hapke's adjustment of the model for the effects of porosity [10].…”

“…Our recent work has investigated ways to improve both the optimization of the inversion of this complex radiative transfer model as well as to develop incremental improvements [8,9] to overcome limitations, such as the assumption of isotropic multiple scatter, which underlie Hapke's Isotropic Multiple Scattering Approximation (IMSA) [1,2].…”

“…In our earlier laboratory studies [8,9], we showed that our modified Hapke model solution could more robustly be inverted to retrieve the sediment filling factor, especially in wavelength ranges, such as the short-wave infra-red (SWIR) where signal-to-noise ratio (SNR) is typically lower [8]. Sediment filling factor φ has been defined as the fractional volume occupied by particles [1,[8][9][10]27]:…”

“…In past work, we have developed methods to invert both the Hapke model and a modified form of the Hapke model that we developed [8,9] in order to specifically retrieve the sediment filling factor from multi-view hyperspectral data. Initially, we had focused on laboratory studies, using hyperspectral bi-conical reflectance factor (BCRF) [35][36][37][38] data derived from the Goniometer of the Rochester Institute of Technology-Two (GRIT-T) [8,39] to demonstrate the feasibility of the approach.…”