L-Band Passive and Active Signatures of Vegetated Soil: Simulations With a Unified Model

Abstract

The synergistic exploitation of L-band active and passive measurements has received increasing interest. In this paper, both theoretical simulations and experimental data are employed to get a deeper insight into the relations between the backscattering coefficient and the emissivity. An active/passive discrete model is used to simulate the backscattering coefficient and the emissivity of bare soil, maize crop of various heights, and deciduous forests of various biomass values. Volumetric soil moisture is varied in a 5-40% range. Simulations confirm the already known effects of soil moisture (whose increase produces a decrease in emissivity e and an increase in backscattering coefficient σ 0 ) and the effects of vegetation growth that yields an increase in both σ 0 and e. Experimental data collected by four airborne campaigns and spaceborne active/passive instruments, together with ground measurements, are also reported. Simulated data are used to investigate the sensitivity of active and passive measurements to soil moisture variations under different vegetation covers, and to estimate the coefficient of a linear relation between backscattering coefficient and emissivity.

Sensitivity of CyGNSS Bistatic Reflectivity and SMAP Microwave Radiometry Brightness Temperature to Geophysical Parameters Over Land Surfaces

“…An inverse relationship was found between CyGNSS and SMAP passive observations with SMC, which in turns reflects the expected sensitivity to changes in the dielectric constant of the soil [67]. This functional relationship between both types of sensors is different from that associated with previous SAR-based studies [61], [68]. The tau-omega model (14) under the assumption T S ≈ T v ≈ α, where α is the coefficient of regression, was used to fit the scatter plots of Γ rl versus T I /2 (see Figs.…”

Relationship Between Vegetation Microwave Optical Depth and Cross-Polarized Backscatter From Multiyear Aquarius Observations

“…In some cases this leads to the inclusion of some observations in multiple grid cells (this accounts for less than 1% of the observations), while observations that are not within this distance to a grid point are excluded from the study. More detailed information on the gridding scheme can be found in Konings et al [25], McColl et al [35], and Piles et al [34].…”

“…However, although multisensor techniques gain more and more importance, few studies have compared active and passive microwave vegetation parameters at the global scale using space-borne data. Guerriero et al [35] compared L-band backscattering coefficients and emissivity from theoretical simulations and airborne and space-borne experiments in the presence of different vegetation covers. Konings et al [25] compared VOD to HV-backscattering and to the radar vegetation index (RVI) using three years of global Aquarius observations and found more scatter in the relationship between VOD and RVI than between VOD and the HV backscattering coefficient.…”

Soil moisture estimation by synergetic use of aquarius active and passive L-brand microwave observations

“…Physical interpretation of simultaneous active and passive microwave signals has been pursued by investigators (e.g. Chauhan et al, 1994;Ferrazzoli et al, 1989;Guerriero et al, 2016;Dente et al, 2014;Wang et al, 2018]) as well. Chauhan et al (1994) demonstrated that a discrete scatter approach can be used to predict both L-band radar and radiometer observations.…”

“…Dente et al (2014) investigated a discrete electromagnetic model for simulating C-band Advanced Microwave Scanning Radiometer for EOS (AMSR-E) brightness temperature (T b ) and ASCAT backscattering coefficient ( ) in the Maqu area and proved its applicability to satellite observations. Guerriero et al (2016) applied a discrete electromagnetic model to reproduce the active and passive observations simultaneously collected in airborne field campaigns at L band.…”