Enhancing CYGNSS Soil Moisture Retrieval Accuracy by Considering the Lag Effect of Sun-Induced Fluorescence

The cyclone global navigation satellite system (CYGNSS) has emerged as a key focus in soil moisture (SM) retrieval research due to its high temporal resolution and quasi-global coverage. The normalized difference vegetation index is widely used for large-scale SM retrieval due to its ability to char...

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Main Authors: Jinghui Liu, Xianyun Zhang, Xiaodong Deng, Hongquan Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Online Access:https://ieeexplore.ieee.org/document/11072353/
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author Jinghui Liu
Xianyun Zhang
Xiaodong Deng
Hongquan Wang
author_facet Jinghui Liu
Xianyun Zhang
Xiaodong Deng
Hongquan Wang
author_sort Jinghui Liu
collection DOAJ
description The cyclone global navigation satellite system (CYGNSS) has emerged as a key focus in soil moisture (SM) retrieval research due to its high temporal resolution and quasi-global coverage. The normalized difference vegetation index is widely used for large-scale SM retrieval due to its ability to characterize vegetation&#x2019;s physiological status and growth. In comparison, sun-induced fluorescence (SIF) demonstrates greater sensitivity to SM variations. However, there has been limited research exploring the application of SIF in SM retrieval based on CYGNSS, and existing studies have largely overlooked the potential lag effect of SIF on SM (LESOS). To enhance the accuracy of CYGNSS-based SM retrieval, we proposed a novel SM retrieval scheme considering the LESOS. The results indicated that there was a lag effect in the response of SIF to SM, and this effect varied significantly across different regions. After accounting for LESOS, the mean root mean square error (RMSE) of the retrieved SM across the entire study area decreased from 0.0360 to 0.0355 cm<sup>3</sup>&centerdot;cm<sup>-3</sup>, while the Pearson correlation coefficient (PCC) increased from 0.5217 to 0.5358. In regions where the lag effect was entirely positive, both metrics showed more substantial improvements: RMSE decreased by 5.7% and PCC improved by 10.8% . In Hunan Province, where positive lag effects predominated, retrieval accuracy was further enhanced. Moreover, the retrieved SM in the positive delay region showed better consistency with in-situ SM. The proposed method offers a novel solution for high-precision SM retrieval using SIF based on CYGNSS.
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spelling doaj-art-752a233d65e3430f9af0466f158351e42025-08-20T03:05:42ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-0118198401985210.1109/JSTARS.2025.358665211072353Enhancing CYGNSS Soil Moisture Retrieval Accuracy by Considering the Lag Effect of Sun-Induced FluorescenceJinghui Liu0Xianyun Zhang1https://orcid.org/0009-0003-7909-0597Xiaodong Deng2https://orcid.org/0000-0003-3038-5047Hongquan Wang3https://orcid.org/0000-0002-4429-6515Institute of Mining Technology, Guizhou University, Guiyang, ChinaInstitute of Mining Technology, Guizhou University, Guiyang, ChinaInstitute of Mining Technology, Guizhou University, Guiyang, ChinaScience and Technology Branch, Agriculture and Agr-Food Canada, Ottawa, ON, CanadaThe cyclone global navigation satellite system (CYGNSS) has emerged as a key focus in soil moisture (SM) retrieval research due to its high temporal resolution and quasi-global coverage. The normalized difference vegetation index is widely used for large-scale SM retrieval due to its ability to characterize vegetation&#x2019;s physiological status and growth. In comparison, sun-induced fluorescence (SIF) demonstrates greater sensitivity to SM variations. However, there has been limited research exploring the application of SIF in SM retrieval based on CYGNSS, and existing studies have largely overlooked the potential lag effect of SIF on SM (LESOS). To enhance the accuracy of CYGNSS-based SM retrieval, we proposed a novel SM retrieval scheme considering the LESOS. The results indicated that there was a lag effect in the response of SIF to SM, and this effect varied significantly across different regions. After accounting for LESOS, the mean root mean square error (RMSE) of the retrieved SM across the entire study area decreased from 0.0360 to 0.0355 cm<sup>3</sup>&centerdot;cm<sup>-3</sup>, while the Pearson correlation coefficient (PCC) increased from 0.5217 to 0.5358. In regions where the lag effect was entirely positive, both metrics showed more substantial improvements: RMSE decreased by 5.7% and PCC improved by 10.8% . In Hunan Province, where positive lag effects predominated, retrieval accuracy was further enhanced. Moreover, the retrieved SM in the positive delay region showed better consistency with in-situ SM. The proposed method offers a novel solution for high-precision SM retrieval using SIF based on CYGNSS.https://ieeexplore.ieee.org/document/11072353/Cyclone global navigation satellite system (CYGNSS)global navigation satellite system reflectometry (GNSS-R)lag effectsoil moisture (SM)sun-induced fluorescence (SIF)windowed cross-correlation (WCC)
spellingShingle Jinghui Liu
Xianyun Zhang
Xiaodong Deng
Hongquan Wang
Enhancing CYGNSS Soil Moisture Retrieval Accuracy by Considering the Lag Effect of Sun-Induced Fluorescence
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Cyclone global navigation satellite system (CYGNSS)
global navigation satellite system reflectometry (GNSS-R)
lag effect
soil moisture (SM)
sun-induced fluorescence (SIF)
windowed cross-correlation (WCC)
title Enhancing CYGNSS Soil Moisture Retrieval Accuracy by Considering the Lag Effect of Sun-Induced Fluorescence
title_full Enhancing CYGNSS Soil Moisture Retrieval Accuracy by Considering the Lag Effect of Sun-Induced Fluorescence
title_fullStr Enhancing CYGNSS Soil Moisture Retrieval Accuracy by Considering the Lag Effect of Sun-Induced Fluorescence
title_full_unstemmed Enhancing CYGNSS Soil Moisture Retrieval Accuracy by Considering the Lag Effect of Sun-Induced Fluorescence
title_short Enhancing CYGNSS Soil Moisture Retrieval Accuracy by Considering the Lag Effect of Sun-Induced Fluorescence
title_sort enhancing cygnss soil moisture retrieval accuracy by considering the lag effect of sun induced fluorescence
topic Cyclone global navigation satellite system (CYGNSS)
global navigation satellite system reflectometry (GNSS-R)
lag effect
soil moisture (SM)
sun-induced fluorescence (SIF)
windowed cross-correlation (WCC)
url https://ieeexplore.ieee.org/document/11072353/
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AT xianyunzhang enhancingcygnsssoilmoistureretrievalaccuracybyconsideringthelageffectofsuninducedfluorescence
AT xiaodongdeng enhancingcygnsssoilmoistureretrievalaccuracybyconsideringthelageffectofsuninducedfluorescence
AT hongquanwang enhancingcygnsssoilmoistureretrievalaccuracybyconsideringthelageffectofsuninducedfluorescence