Characterization of higher-order scattering from vegetation with SMAP measurements

Vegetation cover absorbs and scatters L-band microwave emission measured by SMOS and SMAP satellites. Misrepresentation of this phenomena results in uncertainties when inferring, for instance, surface soil moisture in retrieval algorithms that commonly utilize the tau-omega model which is most appli...

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Bibliographic Details
Main Authors: Feldman, Andrew F (Author), Akbar, Ruzbeh (Author), Entekhabi, Dara (Author)
Other Authors: Massachusetts Institute of Technology. Department of Civil and Environmental Engineering (Contributor)
Format: Article
Language:English
Published: Elsevier BV, 2020-06-05T18:27:53Z.
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Online Access:Get fulltext
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042 |a dc 
100 1 0 |a Feldman, Andrew F  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Civil and Environmental Engineering  |e contributor 
700 1 0 |a Akbar, Ruzbeh  |e author 
700 1 0 |a Entekhabi, Dara  |e author 
245 0 0 |a Characterization of higher-order scattering from vegetation with SMAP measurements 
260 |b Elsevier BV,   |c 2020-06-05T18:27:53Z. 
856 |z Get fulltext  |u https://hdl.handle.net/1721.1/125694 
520 |a Vegetation cover absorbs and scatters L-band microwave emission measured by SMOS and SMAP satellites. Misrepresentation of this phenomena results in uncertainties when inferring, for instance, surface soil moisture in retrieval algorithms that commonly utilize the tau-omega model which is most applicable for a weakly scattering medium. In this study, we investigate the degree to which multiple-scattering is prevalent over a range of land cover classifications (from lightly vegetated grasslands to dense forests) at the satellite scale by explicitly accounting for multiple-scattering in a first-order radiative transfer model, developed here. Even though the tau-omega model with effective parameters can possibly capture higher-order scattering contributions, deliberately partitioning scattering into different components is required to estimate multiple-scattering properties. Specifically, we aim to determine how one can partition between zeroth and first-order radiative transfer terms within a retrieval algorithm without ancillary information, determine whether this method can detect first-order scattering at the SMAP measurement scale without ancillary information, and quantify the magnitude of detected scattering. A simplified first-order radiative transfer model which characterizes single interactions of microwaves with a scattering medium is developed for implementation within retrieval algorithms. This new emission model is implemented within a recently developed retrieval algorithm, the multi-temporal dual channel algorithm (MT-DCA), which does not require ancillary land use information. Scattering parameters as well as SM and vegetation optical depth (τ) are retrieved simultaneously in Africa and South America using the first year of SMAP brightness temperature measurements on a 36 km grid. Specifically, an introduced time invariant first-order scattering coefficient (ω1) is retrieved representing microwave emission interaction with the canopy. We find that ω1 is typically zero in lightly vegetated biomes and non-zero (~0.06) in 74% of the forest pixels. In forest-dominated pixels, the median first-order emissivity is 0.04, or about 4.3% of a given SMAP radiometer brightness temperature measurement. Additionally, explicitly accounting for first-order scattering terms in the radiative transfer model tends to increase SM and τ retrievals by a median of 0.02 m3/m3 and 0.1, respectively, only in forested regions. This study demonstrates the first attempt to explicitly partition higher-order scattering terms in a retrieval algorithm at a satellite scale and ultimately provides a fundamental understanding and quantification of multiple-scattering from grasslands to forests. Keywords: soil moisture; passive microwave radiometry; SMAP; multiple-scattering 
520 |a NASA Subcontract No. 1510842 
546 |a en 
655 7 |a Article 
773 |t Remote Sensing of Environment