23.2.15.5 Soil Moisture, Radar, SAR, X-Band

Stamenkovic, J., Guerriero, L., Ferrazzoli, P., Notarnicola, C., Greifeneder, F., Thiran, J.P.,
Soil Moisture Estimation by SAR in Alpine Fields Using Gaussian Process Regressor Trained by Model Simulations,
GeoRS(55), No. 9, September 2017, pp. 4899-4912.
IEEE DOI 1709
Gaussian processes, remote sensing by radar, synthetic aperture radar, C-band VV-polarized Wide Swath images, Envisat Advanced SAR, Gaussian Process Regression, Mazia valley, South Tyrol, backscatter model simulations, correlation coefficient, discrete radiative transfer model, grassland alpine area, meteorological stations, BibRef

Högström, E., Bartsch, A.,
Impact of Backscatter Variations Over Water Bodies on Coarse-Scale Radar Retrieved Soil Moisture and the Potential of Correcting With Meteorological Data,
GeoRS(55), No. 1, January 2017, pp. 3-13.
IEEE DOI 1701
backscatter BibRef

Sadeghi, M.[Morteza], Tabatabaeenejad, A.[Alireza], Tuller, M.[Markus], Moghaddam, M.[Mahta], Jones, S.B.[Scott B.],
Advancing NASA's AirMOSS P-Band Radar Root Zone Soil Moisture Retrieval Algorithm via Incorporation of Richards' Equation,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Xie, Q.X.[Qiu-Xia], Meng, Q.Y.[Qing-Yan], Zhang, L.L.[Lin-Lin], Wang, C.M.[Chun-Mei], Sun, Y.X.[Yun-Xiao], Sun, Z.H.[Zhen-Hui],
A Soil Moisture Retrieval Method Based on Typical Polarization Decomposition Techniques for a Maize Field from Full-Polarization Radarsat-2 Data,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Özerdem, M.S.[Mehmet Siraç], Acar, E.[Emrullah], Ekinci, R.[Remzi],
Soil Moisture Estimation over Vegetated Agricultural Areas: Tigris Basin, Turkey from Radarsat-2 Data by Polarimetric Decomposition Models and a Generalized Regression Neural Network,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Zwieback, S., Hensley, S., Hajnsek, I.,
Soil Moisture Estimation Using Differential Radar Interferometry: Toward Separating Soil Moisture and Displacements,
GeoRS(55), No. 9, September 2017, pp. 5069-5083.
IEEE DOI 1709
estimation theory, radar interferometry, remote sensing by radar, synthetic aperture radar, Coherence, Estimation, Interferometry. Time series analysis, displacement measurement, electromagnetic scattering, estimation, measurement errors, phase noise, BibRef

Joerg, H., Pardini, M., Hajnsek, I., Papathanassiou, K.P.,
3-D Scattering Characterization of Agricultural Crops at C-Band Using SAR Tomography,
GeoRS(56), No. 7, July 2018, pp. 3976-3989.
IEEE DOI 1807
Agriculture, Scattering, Soil measurements, Soil moisture, Synthetic aperture radar, Vegetation mapping, vegetation water content (VWC) BibRef

Bauer-Marschallinger, B.[Bernhard], Paulik, C.[Christoph], Hochstöger, S.[Simon], Mistelbauer, T.[Thomas], Modanesi, S.[Sara], Ciabatta, L.[Luca], Massari, C.[Christian], Brocca, L.[Luca], Wagner, W.[Wolfgang],
Soil Moisture from Fusion of Scatterometer and SAR: Closing the Scale Gap with Temporal Filtering,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Li, J.H.[Jun-Hua], Wang, S.[Shusen],
Using SAR-Derived Vegetation Descriptors in a Water Cloud Model to Improve Soil Moisture Retrieval,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Cenci, L.[Luca], Pulvirenti, L.[Luca], Boni, G.[Giorgio], Pierdicca, N.[Nazzareno],
Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Shamir, O.[Omer], Goldshleger, N.[Naftaly], Basson, U.[Uri], Reshef, M.[Moshe],
Laboratory Measurements of Subsurface Spatial Moisture Content by Ground-Penetrating Radar (GPR) Diffraction and Reflection Imaging of Agricultural Soils,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef
Earlier:
Mapping Spatial Moisture Content Of Unsaturated Agricultural Soils With Ground-penetrating Radar,
ISPRS16(B8: 1279-1285).
DOI Link 1610
Ths 10: Spatial ecology and ecosystem services mapping using Essential Biodiversity Variables (ebvs) BibRef

Etminan, A., Tabatabaeenejad, A., Moghaddam, M.,
Retrieving Root-Zone Soil Moisture Profile From P-Band Radar via Hybrid Global and Local Optimization,
GeoRS(58), No. 8, August 2020, pp. 5400-5408.
IEEE DOI 2007
Soil moisture, Mathematical model, Optimization, Radar, Atmospheric modeling, Data models, Electromagnetic scattering, surface and subsurface properties BibRef

Tabatabaeenejad, A., Chen, R.H., Burgin, M.S., Duan, X., Cuenca, R.H., Cosh, M.H., Scott, R.L., Moghaddam, M.,
Assessment and Validation of AirMOSS P-Band Root-Zone Soil Moisture Products,
GeoRS(58), No. 9, September 2020, pp. 6181-6196.
IEEE DOI 2008
Soil moisture, Forestry, Atmospheric modeling, Synthetic aperture radar, Radar remote sensing, simulated annealing BibRef

Zribi, M.[Mehrez], Muddu, S.[Sekhar], Bousbih, S.[Safa], Bitar, A.A.[Ahmad Al], Tomer, S.K.[Sat Kumar], Baghdadi, N.[Nicolas], Bandyopadhyay, S.[Soumya],
Analysis of L-Band SAR Data for Soil Moisture Estimations over Agricultural Areas in the Tropics,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Xing, M.F.[Min-Feng], He, B.B.[Bin-Bin], Ni, X.L.[Xi-Liang], Wang, J.F.[Jin-Fei], An, G.Q.A.[Gang-Qi-Ang], Shang, J.L.[Jia-Li], Huang, X.D.[Xiao-Dong],
Retrieving Surface Soil Moisture over Wheat and Soybean Fields during Growing Season Using Modified Water Cloud Model from Radarsat-2 SAR Data,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Xing, M.F.[Min-Feng], Chen, L.[Lin], Wang, J.F.[Jin-Fei], Shang, J.L.[Jia-Li], Huang, X.D.[Xiao-Dong],
Soil Moisture Retrieval Using SAR Backscattering Ratio Method during the Crop Growing Season,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Merzouki, A.[Amine], McNairn, H.[Heather], Powers, J.[Jarrett], Friesen, M.[Matthew],
Synthetic Aperture Radar (SAR) Compact Polarimetry for Soil Moisture Retrieval,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Santi, E.[Emanuele], Dabboor, M.[Mohammed], Pettinato, S.[Simone], Paloscia, S.[Simonetta],
Combining Machine Learning and Compact Polarimetry for Estimating Soil Moisture from C-Band SAR Data,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Xu, C.Y.[Chen-Yang], Qu, J.J.[John J.], Hao, X.J.[Xian-Jun], Wu, D.[Di],
Monitoring Surface Soil Moisture Content over the Vegetated Area by Integrating Optical and SAR Satellite Observations in the Permafrost Region of Tibetan Plateau,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link 2001
BibRef

Molan, Y.E.[Yusuf Eshqi], Lu, Z.[Zhong],
Can InSAR Coherence and Closure Phase Be Used to Estimate Soil Moisture Changes?,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Eshqi Molan, Y.[Yusuf], Lu, Z.[Zhong],
Modeling InSAR Phase and SAR Intensity Changes Induced by Soil Moisture,
GeoRS(58), No. 7, July 2020, pp. 4967-4975.
IEEE DOI 2006
Soil moisture, Synthetic aperture radar, Scattering, Mathematical model, Solid modeling, Atmospheric modeling, soil moisture BibRef

Zhang, L.[Li], Lv, X.L.[Xiao-Lei], Chen, Q.[Qi], Sun, G.C.[Guang-Cai], Yao, J.C.[Jing-Chuan],
Estimation of Surface Soil Moisture during Corn Growth Stage from SAR and Optical Data Using a Combined Scattering Model,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Molan, Y.E., Lu, Z., Kim, J.W.,
Influence of the Statistical Properties of Phase and Intensity on Closure Phase,
GeoRS(58), No. 10, October 2020, pp. 7346-7354.
IEEE DOI 2009
Coherence, Dielectric constant, Soil moisture, Radar polarimetry, Synthetic aperture radar, Strain, Closure phase, coherence, single-looked pixel's intensity and phase changes Comments:
See also Comments on Influence of the Statistical Properties of Phase and Intensity on Closure Phase. BibRef

Hänsch, R., Jagdhuber, T., Fersch, B.,
Soil-Permittivity Estimation Under Grassland Using Machine-Learning and Polarimetric Decomposition Techniques,
GeoRS(59), No. 4, April 2021, pp. 2877-2887.
IEEE DOI 2104
Permittivity, Synthetic aperture radar, Maximum likelihood estimation, Soil moisture, Scattering, soil moisture BibRef

Hamze, M.[Mohamad], Baghdadi, N.[Nicolas], El Hajj, M.M.[Marcel M.], Zribi, M.[Mehrez], Bazzi, H.[Hassan], Cheviron, B.[Bruno], Faour, G.[Ghaleb],
Integration of L-Band Derived Soil Roughness into a Bare Soil Moisture Retrieval Approach from C-Band SAR Data,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

de Zan, F.[Francesco], Rocca, F.[Fabio], Ferretti, A.[Alessandro], López-Dekker, P.[Paco], Eineder, M.[Michael],
Comments on 'Influence of the Statistical Properties of Phase and Intensity on Closure Phase',
GeoRS(59), No. 7, July 2021, pp. 6277-6278.
IEEE DOI 2106
Moisture, Synthetic aperture radar, Interferometry, Scattering, Imaging, Image color analysis, Sociology, Closure phase, SAR interferometry
See also Influence of the Statistical Properties of Phase and Intensity on Closure Phase. BibRef

Gao, Y.[Ya], Gao, M.[Maofang], Wang, L.G.[Li-Guo], Rozenstein, O.[Offer],
Soil Moisture Retrieval over a Vegetation-Covered Area Using ALOS-2 L-Band Synthetic Aperture Radar Data,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Gharechelou, S.[Saeid], Tateishi, R.[Ryutaro], Sumantyo, J.T.S.[Josaphat Tetuko Sri], Johnson, B.A.[Brian Alan],
Soil Moisture Retrieval Using Polarimetric SAR Data and Experimental Observations in an Arid Environment,
IJGI(10), No. 10, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Hegazi, E.H.[Ehab H.], Yang, L.B.[Ling-Bo], Huang, J.F.[Jing-Feng],
A Convolutional Neural Network Algorithm for Soil Moisture Prediction from Sentinel-1 SAR Images,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Dann, J.[Julian], Bennett, K.E.[Katrina E.], Bolton, W.R.[W. Robert], Wilson, C.J.[Cathy J.],
Factors Controlling a Synthetic Aperture Radar (SAR) Derived Root-Zone Soil Moisture Product over The Seward Peninsula of Alaska,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Magagi, R.[Ramata], Jammali, S.[Safa], Goïta, K.[Kalifa], Wang, H.Q.[Hong-Quan], Colliander, A.[Andreas],
Potential of L- and C- Bands Polarimetric SAR Data for Monitoring Soil Moisture over Forested Sites,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Liao, T.H.[Tien-Hao], Kim, S.B.[Seung-Bum],
Dual-Frequency Retrieval of Soil Moisture from L- and S-Band Radar Data for Corn and Soybean,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Li, Z.L.[Zhi-Lian], Zeng, Z.F.[Zhao-Fa], Xiong, H.Q.[Hong-Qiang], Lu, Q.[Qi], An, B.Z.[Bai-Zhou], Yan, J.[Jiahe], Li, R.S.[Ri-Sheng], Xia, L.F.[Long-Fei], Wang, H.Y.[Hao-Yu], Liu, K.[Kexin],
Study on Rapid Inversion of Soil Water Content from Ground-Penetrating Radar Data Based on Deep Learning,
RS(15), No. 7, 2023, pp. 1906.
DOI Link 2304
BibRef

Lee, J.H.[Ju Hyoung], Lindenschmidt, K.E.[Karl-Erich],
Bias-Corrected RADARSAT-2 Soil Moisture Dynamics Reveal Discharge Hysteresis at An Agricultural Watershed,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef
And: Correction: RS(15), No. 13, 2023, pp. 3342.
DOI Link 2307
BibRef

Lu, Q.[Qi], Liu, K.[Kexin], Zeng, Z.F.[Zhao-Fa], Liu, S.X.[Si-Xin], Li, R.S.[Ri-Sheng], Xia, L.F.[Long-Fei], Guo, S.L.[Shi-Long], Li, Z.L.[Zhi-Lian],
Estimation of the Soil Water Content Using the Early Time Signal of Ground-Penetrating Radar in Heterogeneous Soil,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
BibRef

Goïta, K.[Kalifa], Magagi, R.[Ramata], Beauregard, V.[Vincent], Wang, H.Q.[Hong-Quan],
Retrieval of Surface Soil Moisture over Wheat Fields during Growing Season Using C-Band Polarimetric SAR Data,
RS(15), No. 20, 2023, pp. 4925.
DOI Link 2310
BibRef

Xu, C.B.[Chong-Bin], Liu, Q.L.[Qing-Li], Wang, Y.L.[Ying-Lin], Chen, Q.[Qian], Sun, X.M.[Xiao-Min], Zhao, H.[He], Zhao, J.H.[Jian-Hui], Li, N.[Ning],
Inversion of Farmland Soil Moisture Based on Multi-Band Synthetic Aperture Radar Data and Optical Data,
RS(16), No. 13, 2024, pp. 2296.
DOI Link 2407
BibRef

Zakharov, I.[Igor], Kohlsmith, S.[Sarah], Hornung, J.[Jon], Charbonneau, F.[François], Bobby, P.[Pradeep], Howell, M.[Mark],
Surface Soil Moisture Estimation from Time Series of RADARSAT Constellation Mission Compact Polarimetric Data for the Identification of Water-Saturated Areas,
RS(16), No. 14, 2024, pp. 2664.
DOI Link 2408
BibRef

Dinesh, D.[Dev], Kumar, S.[Shashi], Saran, S.[Sameer],
Machine Learning Modelling for Soil Moisture Retrieval from Simulated NASA-ISRO SAR (NISAR) L-Band Data,
RS(16), No. 18, 2024, pp. 3539.
DOI Link 2410
BibRef

Gorrab, A., Simonneaux, V., Zribi, M., Saadi, S., Baghdadi, N., Lili-Chabaane, Z.,
The potential use of high resolution X-band SAR moisture products for the calibration of a water balance model over bare agricultural soils (Tunisia),
ISIVC16(185-190)
IEEE DOI 1704
Calibration BibRef

Mahrooghy, M.[Majid], Aanstoos, J.V.[James V.], Hasan, K.[Khaled], Prasad, S.[Saurabh], Younan, N.H.[Nicolas H.],
Effect of vegetation height and volume scattering on soil moisture classification using synthetic aperture radar (SAR) images,
AIPR11(1-5).
IEEE DOI 1204

See also Unsupervised classification of SAR imagery using polarimetric decomposition to preserve scattering characteristics. BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Soil Moisture, Evaluations and Comparisions of Different Methods .

Last update:Nov 26, 2024 at 16:40:19