Extension of the Hapke bidirectional reflectance model to retrieve soil water content

Abstract

Abstract. Soil moisture links the hydrologic cycle and the energy budget of land surfaces by regulating latent heat fluxes. An accurate assessment of the spatial and temporal variation of soil moisture is important to the study of surface biogeophysical processes. Although remote sensing has proven to be one of the most powerful tools for obtaining land surface parameters, no effective methodology yet exists for in situ soil moisture measurement based on a Bidirectional Reflectance Distribution Function (BRDF) model, such as the Hapke model. To retrieve and analyze soil moisture, this study applied the soil water parametric (SWAP)-Hapke model, which introduced the equivalent water thickness of soil, to ground multi-angular and hyperspectral observations coupled with, Powell-Ant Colony Algorithm methods. The inverted soil moisture data resulting from our method coincided with in situ measurements (R 2 = 0.867, RMSE = 0.813) based on three selected bands (672 nm, 866 nm, 2209 nm). It proved that the extended Hapke model can be used to estimate soil moisture with high accuracy based on the field multi-angle and multispectral remote sensing data.

Modeling and intercomparison of field and laboratory hyperspectral goniometer measurements with G-LiHT imagery of the Algodones Dunes

“…[17][18][19][20][21][22][23][24][25][26] The isotropic multiple scattering approximation (IMSA) is an approximate solution to an RTE based on the Chandresekhar-Ambartsumian method of invariance. 4 In the Hapke treatment of the RTE, five orders of scattering are considered, and the single scattering contribution through the single scattering phase function is treated in an exact form; however, for multiple scattering contributions, the phase function is assumed to be isotropic.…”

An assessment of the bidirectional reflectance models basing on laboratory experiment of natural particulate surfaces

“…4, the reflectance "R" refers to the ratio of the reflected brightness of the sample to that of a Lambert reflectance surface. The choice of M-1 and M-2 is dictated by the requirement that each of them has been applied in the investigation of planetary and terrestrial surfaces [20][21][22][23][24][25][38][39][40][41][42][43]. Recently, there is a publication by Shkuratov et al [37] devotes to a systematic analysis of the adequacy of the Hapke model in a wide physical context.…”

“…The code implements either a Gauss-Newton or a Levenberg-Marquardt method depending on performance subject to fixed upper and lower bounds on the independent variables using function values alone [38]. Based on the inversion method from previous studies [15,16,21,38], two bands, such as 560nm and 670nm, were selected for estimating the model parameters. Table 1 lists the parameters of M-1 for black soil inversed basing on the method mentioned in part 4.3, the incident zenith angle is 60°.…”

“…At the same time, there were some attempts to modify the model and to suggest alternatives by other scientific workers [17][18][19] because of the shortcomings of the model. But the Hapke model is still widely used in the interpretation of photometric data obtained from natural and planetary surfaces and it is also an active research area for remote sensing applications [20][21][22][23][24][25].…”

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

“…Hapke's IMSA solution to the radiative transfer equation accounts for influences such as macroscopic surface roughness [12,26], sediment filling factor (the fraction of volume occupied by particles) [1,10], and grain size distribution [1,10,27], as well as intrinsic properties of materials such as single scattering albedo [1]. Extensions of the Hapke model also have considered methods to include the influence of pore water in sediment [28]. A central focus of this paper is the inversion of a variant of the IMSA model to retrieve the sediment filling factor.…”