A Critical Study of the Radiative Transfer Approach for the Remote Sensing of Layered Random Media

2013 ◽  
Author(s):  
Saba Mudaliar
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Random Media ◽  
Critical Study

Active remote sensing of random media

1980 ◽  
Vol 51 (1) ◽  
pp. 74-79 ◽  
Author(s):  
M. Zuniga ◽  
J. A. Kong
Keyword(s):  
Remote Sensing ◽  
Random Media

Soil moisture and vegetation effects on the ASCAT backscatter-incidence angle dependence

2021 ◽  
Author(s):  
Isabella Pfeil ◽  
Wolfgang Wagner ◽  
Sebastian Hahn ◽  
Raphael Quast ◽  
Susan Steele-Dunne ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Radiative Transfer ◽  
Incidence Angle ◽  
Transfer Model ◽  
Study Region ◽  
Vegetation Effects ◽  
First Order ◽  
Vegetation Parameters ◽  
Low Incidence

<div> <p>Soil moisture (SM) datasets retrieved from the advanced scatterometer (ASCAT) sensor are well established and widely used for various hydro-meteorological, agricultural, and climate monitoring applications. Besides SM, ASCAT is sensitive to vegetation structure and vegetation water content, enabling the retrieval of vegetation optical depth (VOD; 1). The challenge in the retrieval of SM and vegetation products from ASCAT observations is to separate the two effects. As described by Wagner et al. (2), SM and vegetation affect the relation between backscatter and incidence angle differently.  At high incidence angles, the response from bare soil and thus the sensitivity to SM conditions is significantly weaker than at low incidence angles, leading to decreasing backscatter with increasing incidence angle. The presence of vegetation on the other hand decreases the backscatter dependence on the incidence angle. The dependence of backscatter on the incidence angle can be described by a second-order Taylor polynomial based on a slope and a curvature coefficient. It was found empirically that SM conditions have no significant effect on the steepness of the slope, and that therefore, SM and vegetation effects can be separated using the slope (2).  This is a major assumption in the TU Wien soil moisture retrieval algorithm used in several operational soil moisture products. However, recent findings by Quast et al. (3) using a first-order radiative transfer model for the inversion of soil and vegetation parameters from scatterometer observations indicate that SM may influence the slope, as the SM-induced backscatter increase is more pronounced at low incidence angles. </p> </div><div> <div> <p>The aim of this analysis is to revisit the assumption that SM does not affect the slope of the backscatter incidence angle relations by investigating if short-term variability, observed in ASCAT slope timeseries on top of the seasonal vegetation cycle, is caused by SM. We therefore compare timeseries and anomalies of the ASCAT slope to air temperature, rainfall and SM from the ERA5-Land dataset. We carry out the analysis in a humid continental climate (Austria) and a Mediterranean climate study region (Portugal). First results show significant negative correlations between slope and SM anomalies. However, correlations between temperature and slope anomalies are of a similar magnitude, albeit positive, which may reflect temperature-induced vegetation dynamics. The fact that temperature and SM are strongly correlated with each other complicates the interpretation of the results. Thus, our second approach is to investigate daily slope values and their change between dry and wet days. The results of this study shall help to quantify the uncertainties in ASCAT SM products caused by the potentially inadequate assumption of a SM-independent slope. </p> </div> <div> <p> </p> </div> <div> <p>(1) Vreugdenhil, Mariette, et al. "Analyzing the vegetation parameterization in the TU-Wien ASCAT soil moisture retrieval." IEEE Transactions on Geoscience and Remote Sensing 54.6 (2016): 3513-3531.</p> <p><span>(2) Wagner, Wolfgang, et al. "Monitoring soil moisture over the Canadian Prairies with the ERS scatterometer." IEEE Transactions on Geoscience and Remote Sensing 37.1 (1999): 206-216. </span></p> </div> <div> <p>(3) Quast, Raphael, et al. "A Generic First-Order Radiative Transfer Modelling Approach for the Inversion of Soil and Vegetation Parameters from Scatterometer Observations." Remote Sensing 11.3 (2019): 285.</p> </div> </div>

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