22.2.14.3 Soil Moisture, Radar, SAR, X-Band

Chapter Contents (Back)
Soil Moisture. Moisture. SAR Analysis. General radar analysis.
See also Soil Moisture, Sentinel 1, 2, 3, Data.

Kseneman, M.[Matej], Gleich, D.[Dušan], Potocnik, B.[Božidar],
Soil-moisture estimation from TerraSAR-X data using neural networks,
MVA(23), No. 5, September 2012, pp. 937-952.
WWW Link. 1208
BibRef

Gleich, D.[Dusan],
SAR patch scene categorization,
WSSIP14(31-34) 1406
Continuous wavelet transforms BibRef

Kseneman, M.[Matej], Gleich, D.[Dušan],
Soil-Moisture Estimation From X-Band Data Using Tikhonov Regularization and Neural Net,
GeoRS(51), No. 7, 2013, pp. 3885-3898.
IEEE DOI BibRef 1300
Earlier:
Soil Moisture Estimation with TerraSAR-X: With Dubois Empirical Model,
WSSIP09(1-4).
IEEE DOI 0906
Soil measurements; neural network 1307
BibRef

Morrison, K., Bennett, J.C., Nolan, M.,
Using DInSAR to Separate Surface and Subsurface Features,
GeoRS(51), No. 6, 2013, pp. 3424-3430.
IEEE DOI radar interferometry; moisture content; ground-penetrating radar 1307
BibRef

Jacome, A.[Andres], Bernier, M.[Monique], Chokmani, K.[Karem], Gauthier, Y.[Yves], Poulin, J.[Jimmy], de Sčve, D.[Danielle],
Monitoring Volumetric Surface Soil Moisture Content at the La Grande Basin Boreal Wetland by Radar Multi Polarization Data,
RS(5), No. 10, 2013, pp. 4919-4941.
DOI Link 1311
BibRef

Tran, A.P.[Anh Phuong], Andre, F., Lambot, S.,
Validation of Near-Field Ground-Penetrating Radar Modeling Using Full-Wave Inversion for Soil Moisture Estimation,
GeoRS(52), No. 9, Sept 2014, pp. 5483-5497.
IEEE DOI 1407
ground penetrating radar BibRef

Ouellette, J.D., Johnson, J.T., Kim, S., van Zyl, J.J., Moghaddam, M., Spencer, M.W., Tsang, L., Entekhabi, D.,
A Simulation Study of Compact Polarimetry for Radar Retrieval of Soil Moisture,
GeoRS(52), No. 9, Sept 2014, pp. 5966-5973.
IEEE DOI 1407
moisture BibRef

de Zan, F., Parizzi, A., Prats-Iraola, P., Lopez-Dekker, P.,
A SAR Interferometric Model for Soil Moisture,
GeoRS(52), No. 1, January 2014, pp. 418-425.
IEEE DOI 1402
dielectric properties BibRef

Dostálová, A.[Alena], Doubková, M.[Marcela], Sabel, D.[Daniel], Bauer-Marschallinger, B.[Bernhard], Wagner, W.[Wolfgang],
Seven Years of Advanced Synthetic Aperture Radar (ASAR) Global Monitoring (GM) of Surface Soil Moisture over Africa,
RS(6), No. 8, 2014, pp. 7683-7707.
DOI Link 1410
BibRef

Song, X.N.[Xiao-Ning], Ma, J.W.[Jian-Wei], Li, X.T.[Xiao-Tao], Leng, P.[Pei], Zhou, F.C.[Fang-Cheng], Li, S.A.[Shu-Ang],
First Results of Estimating Surface Soil Moisture in the Vegetated Areas Using ASAR and Hyperion Data: The Chinese Heihe River Basin Case Study,
RS(6), No. 12, 2014, pp. 12055-12069.
DOI Link 1412
BibRef

Tabatabaeenejad, A., Burgin, M., Duan, X.[Xueyang], Moghaddam, M.,
P-Band Radar Retrieval of Subsurface Soil Moisture Profile as a Second-Order Polynomial: First AirMOSS Results,
GeoRS(53), No. 2, February 2015, pp. 645-658.
IEEE DOI 1411
hydrological techniques BibRef

He, B.B.[Bin-Bin], Xing, M.F.[Min-Feng], Bai, X.J.[Xiao-Jing],
A Synergistic Methodology for Soil Moisture Estimation in an Alpine Prairie Using Radar and Optical Satellite Data,
RS(6), No. 11, 2014, pp. 10966-10985.
DOI Link 1412
BibRef

Truong-Lol, M.L.[My-Linh], Saatchi, S., Jaruwatanadilok, S.,
Soil Moisture Estimation Under Tropical Forests Using UHF Radar Polarimetry,
GeoRS(53), No. 4, April 2015, pp. 1718-1727.
IEEE DOI 1502
environmental monitoring (geophysics) BibRef

Chai, X.[Xun], Zhang, T.T.[Ting-Ting], Shao, Y.[Yun], Gong, H.[Huaze], Liu, L.[Long], Xie, K.X.[Kai-Xin],
Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery,
RS(7), No. 2, 2015, pp. 1279-1299.
DOI Link 1503
BibRef

Du, J.[Jinyang], Kimball, J.S.[John S.], Moghaddam, M.[Mahta],
Theoretical Modeling and Analysis of L- and P-band Radar Backscatter Sensitivity to Soil Active Layer Dielectric Variations,
RS(7), No. 7, 2015, pp. 9450.
DOI Link 1506
BibRef

Gorrab, A.[Azza], Zribi, M.[Mehrez], Baghdadi, N.[Nicolas], Mougenot, B.[Bernard], Chabaane, Z.L.[Zohra Lili],
Potential of X-Band TerraSAR-X and COSMO-SkyMed SAR Data for the Assessment of Physical Soil Parameters,
RS(7), No. 1, 2015, pp. 747-766.
DOI Link 1502
BibRef

Gorrab, A.[Azza], Zribi, M.[Mehrez], Baghdadi, N.[Nicolas], Mougenot, B.[Bernard], Fanise, P.[Pascal], Chabaane, Z.L.[Zohra Lili],
Retrieval of Both Soil Moisture and Texture Using TerraSAR-X Images,
RS(7), No. 8, 2015, pp. 10098.
DOI Link 1509
BibRef

Hosseini, R.[Reza], Newlands, N.K.[Nathaniel K.], Dean, C.B.[Charmaine B.], Takemura, A.[Akimichi],
Statistical Modeling of Soil Moisture, Integrating Satellite Remote-Sensing (SAR) and Ground-Based Data,
RS(7), No. 3, 2015, pp. 2752-2780.
DOI Link 1504
BibRef

Zwieback, S.[Simon], Hensley, S.[Scott], Hajnsek, I.[Irena],
A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence,
RS(7), No. 6, 2015, pp. 7571.
DOI Link 1507
BibRef

Tomer, S.K.[Sat Kumar], Bitar, A.A.[Ahmad Al], Sekhar, M.[Muddu], Zribi, M.[Mehrez], Bandyopadhyay, S., Sreelash, K., Sharma, A.K., Corgne, S.[Samuel], Kerr, Y.[Yann],
Retrieval and Multi-scale Validation of Soil Moisture from Multi-temporal SAR Data in a Semi-Arid Tropical Region,
RS(7), No. 6, 2015, pp. 8128.
DOI Link 1507
BibRef

Zhang, X.[Xiang], Chen, B.Z.[Bao-Zhang], Fan, H.D.[Hong-Dong], Huang, J.[Jilei], Zhao, H.[Hui],
The Potential Use of Multi-Band SAR Data for Soil Moisture Retrieval over Bare Agricultural Areas: Hebei, China,
RS(8), No. 1, 2016, pp. 7.
DOI Link 1602
BibRef

Bai, X., He, B., Li, X.,
Optimum Surface Roughness to Parameterize Advanced Integral Equation Model for Soil Moisture Retrieval in Prairie Area Using Radarsat-2 Data,
GeoRS(54), No. 4, April 2016, pp. 2437-2449.
IEEE DOI 1604
Mathematical model BibRef

Ponnurangam, G.G., Jagdhuber, T., Hajnsek, I., Rao, Y.S.,
Soil Moisture Estimation Using Hybrid Polarimetric SAR Data of RISAT-1,
GeoRS(54), No. 4, April 2016, pp. 2033-2049.
IEEE DOI 1604
Agriculture BibRef

di Martino, G., Iodice, A., Natale, A., Riccio, D.,
Polarimetric Two-Scale Two-Component Model for the Retrieval of Soil Moisture Under Moderate Vegetation via L-Band SAR Data,
GeoRS(54), No. 4, April 2016, pp. 2470-2491.
IEEE DOI 1604
Scattering BibRef

He, L., Panciera, R., Tanase, M.A., Walker, J.P., Qin, Q.,
Soil Moisture Retrieval in Agricultural Fields Using Adaptive Model-Based Polarimetric Decomposition of SAR Data,
GeoRS(54), No. 8, August 2016, pp. 4445-4460.
IEEE DOI 1608
moisture BibRef

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

Fatras, C.[Christophe], Borderies, P.[Pierre], Frappart, F.[Frédéric], Mougin, E.[Eric], Blumstein, D.[Denis], Nińo, F.[Fernando],
Impact of Surface Soil Moisture Variations on Radar Altimetry Echoes at Ku and Ka Bands in Semi-Arid Areas,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
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

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.[Jingchuan],
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.[Liguo], 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


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 30, 2021 at 22:19:38