A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture

Passive microwave remote sensing of soil moisture (SM) requires a physically based dielectric model that quantitatively converts the volumetric SM into the soil bulk dielectric constant. Mironov 2009 is the dielectric model used in the operational SM retrieval algorithms of the NASA Soil Moisture Ac...

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Published in:Remote Sensing
Main Authors: Runze Zhang, Steven Chan, Rajat Bindlish, Venkataraman Lakshmi
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Subjects:
Online Access:https://www.mdpi.com/2072-4292/15/6/1658
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author Runze Zhang
Steven Chan
Rajat Bindlish
Venkataraman Lakshmi
author_facet Runze Zhang
Steven Chan
Rajat Bindlish
Venkataraman Lakshmi
author_sort Runze Zhang
collection DOAJ
container_title Remote Sensing
description Passive microwave remote sensing of soil moisture (SM) requires a physically based dielectric model that quantitatively converts the volumetric SM into the soil bulk dielectric constant. Mironov 2009 is the dielectric model used in the operational SM retrieval algorithms of the NASA Soil Moisture Active Passive (SMAP) and the ESA Soil Moisture and Ocean Salinity (SMOS) missions. However, Mironov 2009 suffers a challenge in deriving SM over organic soils, as it does not account for the impact of soil organic matter (SOM) on the soil bulk dielectric constant. To this end, we presented a comparative performance analysis of nine advanced soil dielectric models over organic soil in Alaska, four of which incorporate SOM. In the framework of the SMAP single-channel algorithm at vertical polarization (SCA-V), SM retrievals from different dielectric models were derived using an iterative optimization scheme. The skills of the different dielectric models over organic soils were reflected by the performance of their respective SM retrievals, which was measured by four conventional statistical metrics, calculated by comparing satellite-based SM time series with in-situ benchmarks. Overall, SM retrievals of organic-soil-based dielectric models tended to overestimate, while those from mineral-soil-based models displayed dry biases. All the models showed comparable values of unbiased root-mean-square error (ubRMSE) and Pearson Correlation (R), but Mironov 2019 exhibited a slight but consistent edge over the others. An integrated consideration of the model inputs, the physical basis, and the validated accuracy indicated that the separate use of Mironov 2009 and Mironov 2019 in the SMAP SCA-V for mineral soils (SOM <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo><</mo></mrow></semantics></math></inline-formula>15%) and organic soils (SOM <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>≥</mo></mrow></semantics></math></inline-formula>15%) would be the preferred option.
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spelling doaj-art-df2b20c201be40688aab2be2bbd56be62025-08-19T22:03:46ZengMDPI AGRemote Sensing2072-42922023-03-01156165810.3390/rs15061658A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil MoistureRunze Zhang0Steven Chan1Rajat Bindlish2Venkataraman Lakshmi3Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA 22904, USANASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USANASA Goddard Space Flight Center, Greenbelt, MD 20771, USADepartment of Engineering Systems and Environment, University of Virginia, Charlottesville, VA 22904, USAPassive microwave remote sensing of soil moisture (SM) requires a physically based dielectric model that quantitatively converts the volumetric SM into the soil bulk dielectric constant. Mironov 2009 is the dielectric model used in the operational SM retrieval algorithms of the NASA Soil Moisture Active Passive (SMAP) and the ESA Soil Moisture and Ocean Salinity (SMOS) missions. However, Mironov 2009 suffers a challenge in deriving SM over organic soils, as it does not account for the impact of soil organic matter (SOM) on the soil bulk dielectric constant. To this end, we presented a comparative performance analysis of nine advanced soil dielectric models over organic soil in Alaska, four of which incorporate SOM. In the framework of the SMAP single-channel algorithm at vertical polarization (SCA-V), SM retrievals from different dielectric models were derived using an iterative optimization scheme. The skills of the different dielectric models over organic soils were reflected by the performance of their respective SM retrievals, which was measured by four conventional statistical metrics, calculated by comparing satellite-based SM time series with in-situ benchmarks. Overall, SM retrievals of organic-soil-based dielectric models tended to overestimate, while those from mineral-soil-based models displayed dry biases. All the models showed comparable values of unbiased root-mean-square error (ubRMSE) and Pearson Correlation (R), but Mironov 2019 exhibited a slight but consistent edge over the others. An integrated consideration of the model inputs, the physical basis, and the validated accuracy indicated that the separate use of Mironov 2009 and Mironov 2019 in the SMAP SCA-V for mineral soils (SOM <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo><</mo></mrow></semantics></math></inline-formula>15%) and organic soils (SOM <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>≥</mo></mrow></semantics></math></inline-formula>15%) would be the preferred option.https://www.mdpi.com/2072-4292/15/6/1658soil moisturedielectric modelsSMAPsoil organic matter
spellingShingle Runze Zhang
Steven Chan
Rajat Bindlish
Venkataraman Lakshmi
A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture
soil moisture
dielectric models
SMAP
soil organic matter
title A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture
title_full A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture
title_fullStr A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture
title_full_unstemmed A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture
title_short A Performance Analysis of Soil Dielectric Models over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture
title_sort performance analysis of soil dielectric models over organic soils in alaska for passive microwave remote sensing of soil moisture
topic soil moisture
dielectric models
SMAP
soil organic matter
url https://www.mdpi.com/2072-4292/15/6/1658
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