Botteron, C.[Cyril],
Dawes, N.[Nicholas],
Leclère, J.[Jérôme],
Skaloud, J.[Jan],
Weijs, S.V.[Steven V.],
Farine, P.A.[Pierre-André],
Soil Moisture & Snow Properties Determination with GNSS in Alpine
Environments: Challenges, Status, and Perspectives,
RS(5), No. 7, 2013, pp. 3516-3543.
DOI Link
1308
BibRef
Sánchez, N.[Nilda],
Alonso-Arroyo, A.[Alberto],
Martínez-Fernández, J.[José],
Piles, M.[María],
González-Zamora, Á.[Ángel],
Camps, A.[Adriano],
Vall-llosera, M.[Mercè],
On the Synergy of Airborne GNSS-R and Landsat 8 for Soil Moisture
Estimation,
RS(7), No. 8, 2015, pp. 9954.
DOI Link
1509
BibRef
Carreno-Luengo, H.[Hugo],
Lowe, S.[Stephen],
Zuffada, C.[Cinzia],
Esterhuizen, S.[Stephan],
Oveisgharan, S.[Shadi],
Spaceborne GNSS-R from the SMAP Mission: First Assessment of
Polarimetric Scatterometry over Land and Cryosphere,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link
1705
BibRef
Han, M.[Mutian],
Zhu, Y.L.[Yun-Long],
Yang, D.K.[Dong-Kai],
Hong, X.B.[Xue-Bao],
Song, S.H.[Shu-Hui],
A Semi-Empirical SNR Model for Soil Moisture Retrieval Using GNSS SNR
Data,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Eroglu, O.[Orhan],
Kurum, M.[Mehmet],
Boyd, D.[Dylan],
Gurbuz, A.C.[Ali Cafer],
High Spatio-Temporal Resolution CYGNSS Soil Moisture Estimates Using
Artificial Neural Networks,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link
1910
BibRef
Senyurek, V.[Volkan],
Lei, F.[Fangni],
Boyd, D.[Dylan],
Kurum, M.[Mehmet],
Gurbuz, A.C.[Ali Cafer],
Moorhead, R.[Robert],
Machine Learning-Based CYGNSS Soil Moisture Estimates over ISMN sites
in CONUS,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Senyurek, V.[Volkan],
Lei, F.[Fangni],
Boyd, D.[Dylan],
Gurbuz, A.C.[Ali Cafer],
Kurum, M.[Mehmet],
Moorhead, R.[Robert],
Evaluations of Machine Learning-Based CYGNSS Soil Moisture Estimates
against SMAP Observations,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Yang, T.[Ting],
Wan, W.[Wei],
Sun, Z.G.[Zhi-Gang],
Liu, B.J.[Bao-Jian],
Li, S.[Sen],
Chen, X.W.[Xiu-Wan],
Comprehensive Evaluation of Using TechDemoSat-1 and CYGNSS Data to
Estimate Soil Moisture over Mainland China,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Jing, L.[Lili],
Yang, L.[Lei],
Yang, W.T.[Wen-Tao],
Xu, T.H.[Tian-He],
Gao, F.[Fan],
Lu, Y.L.[Yi-Lin],
Sun, B.[Bo],
Yang, D.K.[Dong-Kai],
Hong, X.B.[Xue-Bao],
Wang, N.Z.[Na-Zi],
Ruan, H.L.[Hong-Liang],
Darrozes, J.[José],
Robust Kalman Filter Soil Moisture Inversion Model Using GPS SNR
Data: A Dual-Band Data Fusion Approach,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Camps, A.[Adriano],
Vall-Llossera, M.[Mercedes],
Park, H.[Hyuk],
Portal, G.[Gerard],
Rossato, L.[Luciana],
Sensitivity of TDS-1 GNSS-R Reflectivity to Soil Moisture: Global and
Regional Differences and Impact of Different Spatial Scales,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link
1812
BibRef
Jia, Y.[Yan],
Jin, S.G.[Shuang-Gen],
Savi, P.[Patrizia],
Gao, Y.[Yun],
Tang, J.[Jing],
Chen, Y.X.[Yi-Xiang],
Li, W.[Wenmei],
GNSS-R Soil Moisture Retrieval Based on a XGboost Machine Learning
Aided Method: Performance and Validation,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link
1908
BibRef
Chang, X.[Xin],
Jin, T.Y.[Tao-Yong],
Yu, K.[Kegen],
Li, Y.W.[Yun-Wei],
Li, J.C.[Jian-Cheng],
Zhang, Q.A.[Qi-Ang],
Soil Moisture Estimation by GNSS Multipath Signal,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Calabia, A.[Andres],
Molina, I.[Iñigo],
Jin, S.G.[Shuang-Gen],
Soil Moisture Content from GNSS Reflectometry Using Dielectric
Permittivity from Fresnel Reflection Coefficients,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Wu, X.R.[Xue-Rui],
Ma, W.X.[Wen-Xiao],
Xia, J.M.[Jun-Ming],
Bai, W.H.[Wei-Hua],
Jin, S.G.[Shuang-Gen],
Calabia, A.[Andrés],
Spaceborne GNSS-R Soil Moisture Retrieval: Status, Development
Opportunities, and Challenges,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Dong, Z.[Zhounan],
Jin, S.G.[Shuang-Gen],
Evaluation of the Land GNSS-Reflected DDM Coherence on Soil Moisture
Estimation from CYGNSS Data,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Lv, J.C.[Ji-Chao],
Zhang, R.[Rui],
Tu, J.S.[Jin-Sheng],
Liao, M.J.[Ming-Jie],
Pang, J.[Jiatai],
Yu, B.[Bin],
Li, K.[Kui],
Xiang, W.[Wei],
Fu, Y.[Yin],
Liu, G.X.[Guo-Xiang],
A GNSS-IR Method for Retrieving Soil Moisture Content from Integrated
Multi-Satellite Data That Accounts for the Impact of Vegetation
Moisture Content,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Shi, Y.J.[Ya-Jie],
Ren, C.[Chao],
Yan, Z.H.[Zhi-Heng],
Lai, J.M.[Jian-Min],
High Spatial-Temporal Resolution Estimation of Ground-Based Global
Navigation Satellite System Interferometric Reflectometry (GNSS-IR)
Soil Moisture Using the Genetic Algorithm Back Propagation (GA-BP)
Neural Network,
IJGI(10), No. 9, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Munoz-Martin, J.F.[Joan Francesc],
Onrubia, R.[Raul],
Pascual, D.[Daniel],
Park, H.[Hyuk],
Pablos, M.[Miriam],
Camps, A.[Adriano],
Rüdiger, C.[Christoph],
Walker, J.[Jeffrey],
Monerris, A.[Alessandra],
Single-Pass Soil Moisture Retrieval Using GNSS-R at L1 and L5 Bands:
Results from Airborne Experiment,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Munoz-Martin, J.F.[Joan Francesc],
Llaveria, D.[David],
Herbert, C.[Christoph],
Pablos, M.[Miriam],
Park, H.[Hyuk],
Camps, A.[Adriano],
Soil Moisture Estimation Synergy Using GNSS-R and L-Band Microwave
Radiometry Data from FSSCat/FMPL-2,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Xu, H.Z.[Hong-Zhang],
Yuan, Q.Q.[Qiang-Qiang],
Li, T.W.[Tong-Wen],
Shen, H.F.[Huan-Feng],
Zhang, L.P.[Liang-Pei],
Jiang, H.T.[Hong-Tao],
Quality Improvement of Satellite Soil Moisture Products by Fusing
with In-Situ Measurements and GNSS-R Estimates in the Western
Continental U.S.,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Edokossi, K.[Komi],
Calabia, A.[Andres],
Jin, S.G.[Shuang-Gen],
Molina, I.[Iñigo],
GNSS-Reflectometry and Remote Sensing of Soil Moisture:
A Review of Measurement Techniques, Methods, and Applications,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Azemati, A.[Amir],
Melebari, A.[Amer],
Campbell, J.D.[James D.],
Walker, J.P.[Jeffrey P.],
Moghaddam, M.[Mahta],
GNSS-R Soil Moisture Retrieval for Flat Vegetated Surfaces Using a
Physics-Based Bistatic Scattering Model and Hybrid Global/Local
Optimization,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Roberts, T.M.[Thomas Maximillian],
Colwell, I.[Ian],
Chew, C.[Clara],
Lowe, S.[Stephen],
Shah, R.[Rashmi],
A Deep-Learning Approach to Soil Moisture Estimation with GNSS-R,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Chen, S.Z.[Si-Zhe],
Yan, Q.Y.[Qing-Yun],
Jin, S.G.[Shuang-Gen],
Huang, W.M.[Wei-Min],
Chen, T.X.[Tie-Xi],
Jia, Y.[Yan],
Liu, S.[Shuci],
Cao, Q.[Qing],
Soil Moisture Retrieval from the CyGNSS Data Based on a Bilinear
Regression,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Jia, Y.[Yan],
Jin, S.G.[Shuang-Gen],
Savi, P.[Patrizia],
Yan, Q.Y.[Qing-Yun],
Li, W.[Wenmei],
Modeling and Theoretical Analysis of GNSS-R Soil Moisture Retrieval
Based on the Random Forest and Support Vector Machine Learning
Approach,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Yin, C.[Cong],
Huang, F.X.[Fei-Xiong],
Xia, J.M.[Jun-Ming],
Bai, W.H.[Wei-Hua],
Sun, Y.Q.[Yue-Qiang],
Yang, G.L.[Guang-Lin],
Zhai, X.C.[Xiao-Chun],
Xu, N.[Na],
Hu, X.Q.[Xiu-Qing],
Zhang, P.[Peng],
Wang, J.S.[Jin-Song],
Du, Q.F.[Qi-Fei],
Wang, X.Y.[Xian-Yi],
Cai, Y.R.[Yue-Rong],
Soil Moisture Retrieval from Multi-GNSS Reflectometry on FY-3E
GNOS-II by Land Cover Classification,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Wang, Q.[Qi],
Sun, J.J.[Jiao-Jiao],
Chang, X.[Xin],
Jin, T.Y.[Tao-Yong],
Shang, J.G.[Jin-Guang],
Liu, Z.Y.[Zhi-Yong],
The Correction Method of Water and Fresnel Reflection Coefficient for
Soil Moisture Retrieved by CYGNSS,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link
2307
BibRef
Melebari, A.[Amer],
Campbell, J.D.[James D.],
Hodges, E.[Erik],
Moghaddam, M.[Mahta],
Improved Geometric Optics with Topography (IGOT) Model for GNSS-R
Delay-Doppler Maps Using Three-Scale Surface Roughness,
RS(15), No. 7, 2023, pp. 1880.
DOI Link
2304
Global navigation satellite system (GNSS)-reflectometry (GNSS-R)
delay-Doppler maps (DDMs)
BibRef
Munoz-Martin, J.F.[Joan Francesc],
Rodriguez-Alvarez, N.[Nereida],
Bosch-Lluis, X.[Xavier],
Oudrhiri, K.[Kamal],
Effective Surface Roughness Impact in Polarimetric GNSS-R Soil
Moisture Retrievals,
RS(15), No. 8, 2023, pp. 2013.
DOI Link
2305
BibRef
Zhang, T.L.[Tian-Long],
Yang, L.[Lei],
Nan, H.T.[Hong-Tao],
Yin, C.[Cong],
Sun, B.[Bo],
Yang, D.K.[Dong-Kai],
Hong, X.B.[Xue-Bao],
Lopez-Baeza, E.[Ernesto],
In-Situ GNSS-R and Radiometer Fusion Soil Moisture Retrieval Model
Based on LSTM,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link
2306
BibRef
Ding, Q.[Qin],
Liang, Y.[Yueji],
Liang, X.Y.[Xing-Yong],
Ren, C.[Chao],
Yan, H.B.[Hong-Bo],
Liu, Y.[Yintao],
Zhang, Y.[Yan],
Lu, X.J.[Xian-Jian],
Lai, J.M.[Jian-Min],
Hu, X.M.[Xin-Miao],
Soil Moisture Retrieval Using GNSS-IR Based on Empirical Modal
Decomposition and Cross-Correlation Satellite Selection,
RS(15), No. 13, 2023, pp. 3218.
DOI Link
2307
BibRef
Liu, Q.[Qi],
Zhang, S.C.[Shuang-Cheng],
Li, W.Q.[Wei-Qiang],
Nan, Y.[Yang],
Peng, J.[Jilun],
Ma, Z.M.[Zhong-Min],
Zhou, X.[Xin],
Using Robust Regression to Retrieve Soil Moisture from CyGNSS Data,
RS(15), No. 14, 2023, pp. 3669.
DOI Link
2307
BibRef
Hu, Q.F.[Qing-Feng],
Li, Y.F.[Yi-Fan],
Liu, W.K.[Wen-Kai],
Lu, W.Q.[Wei-Qiang],
Hai, H.X.[Hong-Xin],
He, P.P.[Pei-Pei],
Liu, X.L.[Xian-Lin],
Ma, K.F.[Kai-Feng],
Zhu, D.T.[Dan-Tong],
Wang, P.[Peng],
Kou, Y.C.[Ying-Chao],
Research on Soil Moisture Inversion Method for Canal Slope of the
Middle Route Project of the South to North Water Transfer Based on
GNSS-R and Deep Learning,
RS(15), No. 17, 2023, pp. 4340.
DOI Link
2310
BibRef
Wei, H.H.[Hao-Han],
Yang, X.F.[Xiao-Feng],
Pan, Y.W.[Yu-Wei],
Shen, F.[Fei],
GNSS-IR Soil Moisture Inversion Derived from Multi-GNSS and
Multi-Frequency Data Accounting for Vegetation Effects,
RS(15), No. 22, 2023, pp. 5381.
DOI Link
2311
BibRef
Yang, C.Z.[Chang-Zhi],
Mao, K.[Kebiao],
Guo, Z.H.[Zhong-Hua],
Shi, J.C.[Jian-Cheng],
Bateni, S.M.[Sayed M.],
Yuan, Z.J.[Zi-Jin],
Review of GNSS-R Technology for Soil Moisture Inversion,
RS(16), No. 7, 2024, pp. 1193.
DOI Link
2404
BibRef
Hou, Z.[Zhaolu],
Pu, Z.X.[Zhao-Xia],
Assessing CYGNSS Satellite Soil Moisture Data for Drought Monitoring
with Multiple Datasets and Indicators,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link
2401
BibRef
Wernicke, L.J.[Liza J.],
Chew, C.C.[Clara C.],
Small, E.E.[Eric E.],
Spatially Interpolated CYGNSS Data Improve Downscaled 3 km
SMAP/CYGNSS Soil Moisture,
RS(16), No. 16, 2024, pp. 2924.
DOI Link
2408
BibRef
Jiang, Y.[Yao],
Zhang, R.[Rui],
Sun, B.[Bo],
Wang, T.Y.[Tian-Yu],
Zhang, B.[Bo],
Tu, J.S.[Jin-Sheng],
Nie, S.[Shihai],
Jiang, H.[Hang],
Chen, K.[Kangyi],
GNSS-IR Soil Moisture Retrieval Using Multi-Satellite Data Fusion
Based on Random Forest,
RS(16), No. 18, 2024, pp. 3428.
DOI Link
2410
BibRef
Liu, Y.X.[Yi-Xiao],
Wang, Y.[Yong],
Lai, J.C.[Jing-Cheng],
Lin, Y.J.[Yun-Jie],
Shi, L.[Leyan],
Evaluation of Satellite-Based Global Navigation Satellite System
Reflectometry (GNSS-R) Soil Moisture Products in Complex Terrain: A
Case Study of the Yunnan-Guizhou Plateau,
RS(17), No. 5, 2025, pp. 887.
DOI Link
2503
BibRef
Izadgoshasb, H.[Hamed],
Santi, E.[Emanuele],
Cordari, F.[Flavio],
Guerriero, L.[Leila],
Chiavini, L.[Leonardo],
Ambrogioni, V.[Veronica],
Pierdicca, N.[Nazzareno],
Comparison of a Semiempirical Algorithm and an Artificial Neural
Network for Soil Moisture Retrieval Using CYGNSS Reflectometry Data,
RS(17), No. 21, 2025, pp. 3636.
DOI Link
2511
BibRef
Lwin, A.,
Yang, D.,
Hong, X.,
Shamsabadi, S.C.[S. Cheraghi],
Ahmed, W.A.,
Spaceborne GNSS-R Retrieving on Global Soil Moisture Approached By
Support Vector Machine Learning,
ISPRS20(B3:605-610).
DOI Link
2012
BibRef
Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Soil Moisture, Sentinel 1, 2, 3, Data .