Soil Moisture, GNSS-R, CYGNSS

Chapter Contents (Back)
Moisture. GNSS. Cygnss is a different system. Cyclone GNSS.
See also Soil Moisture, Radar, SAR, X-Band.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.[Guanglin], 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

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

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

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.[Xuebao], 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

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

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

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

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

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

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

Zhou, X.[Xin], Zhang, S.C.[Shuang-Cheng], Zhang, Q.[Qin], Liu, Q.[Qi], Ma, Z.M.[Zhong-Min], Wang, T.[Tao], Tian, J.[Jing], Li, X.R.[Xin-Rui],
Research of Deformation and Soil Moisture in Loess Landslide Simultaneous Retrieved with Ground-Based GNSS,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212

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,
DOI Link 2012

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Soil Moisture, Sentinel 1, 2, 3, Data .

Last update:Jul 13, 2024 at 15:27:21