22.2.15 Soil Moisture, SMAP, Soil Moisture Active Passive, Remote Sensing

Le Vine, D.M., Abraham, S.,
Faraday Rotation Correction for SMAP and Soil Moisture Retrieval,
GeoRS(56), No. 2, February 2018, pp. 655-668.
IEEE DOI 1802
Faraday effect, moisture, radiometers, remote sensing, soil, Faraday rotation correction, SMAP, frequency 1.413 GHz, radiometer, remote sensing BibRef

Hong, Y.S.[Yong-Sheng], Yu, L.[Lei], Chen, Y.Y.[Yi-Yun], Liu, Y.F.[Yan-Fang], Liu, Y.L.[Yao-Lin], Liu, Y.[Yi], Cheng, H.[Hang],
Prediction of Soil Organic Matter by VIS-NIR Spectroscopy Using Normalized Soil Moisture Index as a Proxy of Soil Moisture,
RS(10), No. 1, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Chakrabarti, S., Judge, J., Bongiovanni, T., Rangarajan, A., Ranka, S.,
Spatial Scaling Using Temporal Correlations and Ensemble Learning to Obtain High-Resolution Soil Moisture,
GeoRS(56), No. 3, March 2018, pp. 1238-1250.
IEEE DOI 1804
hydrological techniques, land surface temperature, learning (artificial intelligence), moisture, soil moisture BibRef

Sarabandi, K., Kashanianfard, M., Nashashibi, A.Y., Pierce, L.E., Hampton, R.,
A Polarimetric Active Transponder With Extremely Large RCS for Absolute Radiometric Calibration of SMAP Radar,
GeoRS(56), No. 3, March 2018, pp. 1269-1277.
IEEE DOI 1804
calibration, electromagnetic wave polarisation, geophysical techniques, horn antennas, moisture, radar antennas, transponder BibRef

Chen, Q., Zeng, J., Cui, C., Li, Z., Chen, K.S., Bai, X., Xu, J.,
Soil Moisture Retrieval From SMAP: A Validation and Error Analysis Study Using Ground-Based Observations Over the Little Washita Watershed,
GeoRS(56), No. 3, March 2018, pp. 1394-1408.
IEEE DOI 1804
error analysis, moisture, remote sensing, soil, Little Washita Watershed network, SMAP passive products, validation BibRef

Ban, W., Yu, K., Zhang, X.,
GEO-Satellite-Based Reflectometry for Soil Moisture Estimation: Signal Modeling and Algorithm Development,
GeoRS(56), No. 3, March 2018, pp. 1829-1838.
IEEE DOI 1804
Global Positioning System, geophysical signal processing, hydrology, moisture, reflectometry, remote sensing, soil, soil moisture BibRef

Jin, Y.[Yan], Ge, Y.[Yong], Wang, J.H.[Jiang-Hao], Heuvelink, G.B.M.[Gerard B. M.], Wang, L.[Le],
Geographically Weighted Area-to-Point Regression Kriging for Spatial Downscaling in Remote Sensing,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Xu, C.Y.[Chen-Yang], Qu, J.J.[John J.], Hao, X.J.[Xian-Jun], Cosh, M.H.[Michael H.], Prueger, J.H.[John H.], Zhu, Z.L.[Zhi-Liang], Gutenberg, L.[Laurel],
Downscaling of Surface Soil Moisture Retrieval by Combining MODIS/Landsat and In Situ Measurements,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Massari, C.[Christian], Camici, S.[Stefania], Ciabatta, L.[Luca], Brocca, L.[Luca],
Exploiting Satellite-Based Surface Soil Moisture for Flood Forecasting in the Mediterranean Area: State Update Versus Rainfall Correction,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Wang, Y.Q.[Yun-Qian], Yang, J.[Jing], Chen, Y.N.[Ya-Ning], Wang, A.Q.[An-Qian], de Maeyer, P.[Philippe],
The Spatiotemporal Response of Soil Moisture to Precipitation and Temperature Changes in an Arid Region, China,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Li, C.W.[Cheng-Wei], Lu, H.[Hui], Yang, K.[Kun], Han, M.L.[Meng-Lei], Wright, J.S.[Jonathon S.], Chen, Y.Y.[Ying-Ying], Yu, L.[Le], Xu, S.M.[Shi-Ming], Huang, X.M.[Xiao-Meng], Gong, W.[Wei],
The Evaluation of SMAP Enhanced Soil Moisture Products Using High-Resolution Model Simulations and In-Situ Observations on the Tibetan Plateau,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
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Gumbricht, T.[Thomas],
Detecting Trends in Wetland Extent from MODIS Derived Soil Moisture Estimates,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
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Oveisgharan, S.[Shadi], Haddad, Z.[Ziad], Turk, J.[Joe], Rodriguez, E.[Ernesto], Li, L.[Li],
Soil Moisture and Vegetation Water Content Retrieval Using QuikSCAT Data,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Petrova, I.Y.[Irina Y.], Miralles, D.G.[Diego G.], van Heerwaarden, C.C.[Chiel C.], Wouters, H.[Hendrik],
Relation between Convective Rainfall Properties and Antecedent Soil Moisture Heterogeneity Conditions in North Africa,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Zhao, W., Sánchez, N., Li, A.,
Triangle Space-Based Surface Soil Moisture Estimation by the Synergistic Use of In Situ Measurements and Optical/Thermal Infrared Remote Sensing: An Alternative to Conventional Validations,
GeoRS(56), No. 8, August 2018, pp. 4546-4558.
IEEE DOI 1808
hydrological techniques, land surface temperature, radiometry, soil, vegetation mapping, validation BibRef

Bore, T., Schwing, M., Serna, M.L.[M. Llano], Speer, J., Scheuermann, A., Wagner, N.,
A New Broadband Dielectric Model for Simultaneous Determination of Water Saturation and Porosity,
GeoRS(56), No. 8, August 2018, pp. 4702-4713.
IEEE DOI 1808
dielectric relaxation, geophysical techniques, permittivity, porosity, soil, water, porosity, relaxation model BibRef

Fang, B.[Bin], Lakshmi, V.[Venkat], Bindlish, R.[Rajat], Jackson, T.J.[Thomas J.],
AMSR2 Soil Moisture Downscaling Using Temperature and Vegetation Data,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Gao, H.[Huiran], Zhang, W.C.[Wan-Chang], Chen, H.[Hao],
An Improved Algorithm for Discriminating Soil Freezing and Thawing Using AMSR-E and AMSR2 Soil Moisture Products,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Raoult, N.[Nina], Delorme, B.[Bertrand], Ottlé, C.[Catherine], Peylin, P.[Philippe], Bastrikov, V.[Vladislav], Maugis, P.[Pascal], Polcher, J.[Jan],
Confronting Soil Moisture Dynamics from the ORCHIDEE Land Surface Model With the ESA-CCI Product: Perspectives for Data Assimilation,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Pfeil, I.[Isabella], Vreugdenhil, M.[Mariette], Hahn, S.[Sebastian], Wagner, W.[Wolfgang], Strauss, P.[Peter], Blöschl, G.[Günter],
Improving the Seasonal Representation of ASCAT Soil Moisture and Vegetation Dynamics in a Temperate Climate,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Enenkel, M.[Markus], Farah, C.[Carlos], Hain, C.[Christopher], White, A.[Andrew], Anderson, M.[Martha], You, L.Z.[Liang-Zhi], Wagner, W.[Wolfgang], Osgood, D.[Daniel],
What Rainfall Does Not Tell Us: Enhancing Financial Instruments with Satellite-Derived Soil Moisture and Evaporative Stress,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Vazquez-Cuervo, J.[Jorge], Gomez-Valdes, J.[Jose],
SMAP and CalCOFI Observe Freshening during the 2014-2016 Northeast Pacific Warm Anomaly,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Khazâal, A., Richaume, P., Cabot, F., Anterrieu, E., Mialon, A., Kerr, Y.H.,
Improving the Spatial Bias Correction Algorithm in SMOS Image Reconstruction Processor: Validation of Soil Moisture Retrievals WithIn SituData,
GeoRS(57), No. 1, January 2019, pp. 277-290.
IEEE DOI 1901
Image reconstruction, Ocean temperature, Temperature measurement, Earth, Oscillators, Antennas, Gibbs oscillations, inverse problems, synthetic aperture imaging BibRef

Yi, L.[Lu], Zhang, W.[Wanchang], Li, X.Y.[Xiang-Yang],
Assessing Hydrological Modelling Driven by Different Precipitation Datasets via the SMAP Soil Moisture Product and Gauged Streamflow Data,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Wang, S.[Sheng], Garcia, M.[Monica], Ibrom, A.[Andreas], Jakobsen, J.[Jakob], Köppl, C.J.[Christian Josef], Mallick, K.[Kaniska], Looms, M.C.[Majken C.], Bauer-Gottwein, P.[Peter],
Mapping Root-Zone Soil Moisture Using a Temperature-Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Piles, M.[Maria], Ballabrera-Poy, J.[Joaquim], Muñoz-Sabater, J.[Joaquín],
Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite,
RS(11), No. 1, 2019, pp. xx-yy.
DOI Link 1901
BibRef

Wu, M.[Mousong], Scholze, M.[Marko], Voßbeck, M.[Michael], Kaminski, T.[Thomas], Hoffmann, G.[Georg],
Simultaneous Assimilation of Remotely Sensed Soil Moisture and FAPAR for Improving Terrestrial Carbon Fluxes at Multiple Sites Using CCDAS,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Kurum, M., Deshpande, M., Joseph, A.T., O'Neill, P.E., Lang, R.H., Eroglu, O.,
SCoBi-Veg: A Generalized Bistatic Scattering Model of Reflectometry From Vegetation for Signals of Opportunity Applications,
GeoRS(57), No. 2, February 2019, pp. 1049-1068.
IEEE DOI 1901
Scattering, Biological system modeling, Mathematical model, Vegetation mapping, Soil moisture, Receiving antennas, Bistatic, vegetation BibRef

Rodríguez-Fernández, N.[Nemesio], Al Bitar, A.[Ahmad], Colliander, A.[Andreas], Zhao, T.J.[Tian-Jie],
Soil Moisture Remote Sensing across Scales,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Zeng, L.L.[Ling-Lin], Hu, S.[Shun], Xiang, D.X.[Da-Xiang], Zhang, X.[Xiang], Li, D.R.[De-Ren], Li, L.[Lin], Zhang, T.Q.[Ting-Qiang],
Multilayer Soil Moisture Mapping at a Regional Scale from Multisource Data via a Machine Learning Method,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Yuan, J.[Jing], Wang, X.[Xin], Yan, C.X.[Chang-Xiang], Wang, S.R.[Shu-Rong], Ju, X.P.[Xue-Ping], Li, Y.[Yi],
Soil Moisture Retrieval Model for Remote Sensing Using Reflected Hyperspectral Information,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Zhang, Z.[Zhi], Wang, D.G.[Da-Gang], Wang, G.L.[Gui-Ling], Qiu, J.X.[Jian-Xiu], Liao, W.L.[Wei-Lin],
Use of SMAP Soil Moisture and Fitting Methods in Improving GPM Estimation in Near Real Time,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Ayehu, G.[Getachew], Tadesse, T.[Tsegaye], Gessesse, B.[Berhan], Yigrem, Y.[Yibeltal],
Soil Moisture Monitoring Using Remote Sensing Data and a Stepwise-Cluster Prediction Model: The Case of Upper Blue Nile Basin, Ethiopia,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Deng, K.A.K.[Khidir Abdalla Kwal], Lamine, S.[Salim], Pavlides, A.[Andrew], Petropoulos, G.P.[George P.], Srivastava, P.K.[Prashant K.], Bao, Y.S.[Yan-Song], Hristopulos, D.[Dionissios], Anagnostopoulos, V.[Vasileios],
Operational Soil Moisture from ASCAT in Support of Water Resources Management,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Thi, D.N.[Dinh Ngo], Ha, N.T.T.[Nguyen Thi Thu], Dang, Q.T.[Quy Tran], Koike, K.[Katsuaki], Trong, N.M.[Nhuan Mai],
Effective Band Ratio of Landsat 8 Images Based on VNIR-SWIR Reflectance Spectra of Topsoils for Soil Moisture Mapping in a Tropical Region,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Fang, K., Pan, M., Shen, C.,
The Value of SMAP for Long-Term Soil Moisture Estimation With the Help of Deep Learning,
GeoRS(57), No. 4, April 2019, pp. 2221-2233.
IEEE DOI 1904
hydrological techniques, learning (artificial intelligence), moisture, remote sensing, sensor fusion, soil, time series, soil moisture BibRef

Lewandowski, A., Szyplowska, A., Wilczek, A., Kafarski, M., Szerement, J., Skierucha, W.,
One-Port Vector Network Analyzer Characterization of Soil Dielectric Spectrum,
GeoRS(57), No. 6, June 2019, pp. 3661-3676.
IEEE DOI 1906
Transmission line measurements, Calibration, Dielectric measurement, Soil, Dielectrics, Soil measurements, soil moisture and salinity BibRef

Usowicz, B.[Boguslaw], Lipiec, J.[Jerzy], Lukowski, M.[Mateusz],
Evaluation of Soil Moisture Variability in Poland from SMOS Satellite Observations,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Rodríguez-Fernández, N.[Nemesio], de Rosnay, P.[Patricia], Albergel, C.[Clement], Richaume, P.[Philippe], Aires, F.[Filipe], Prigent, C.[Catherine], Kerr, Y.[Yann],
SMOS Neural Network Soil Moisture Data Assimilation in a Land Surface Model and Atmospheric Impact,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Yang, H.[Han], Xiong, L.H.[Li-Hua], Ma, Q.[Qiumei], Xia, J.[Jun], Chen, J.[Jie], Xu, C.Y.[Chong-Yu],
Utilizing Satellite Surface Soil Moisture Data in Calibrating a Distributed Hydrological Model Applied in Humid Regions Through a Multi-Objective Bayesian Hierarchical Framework,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Ojha, N.[Nitu], Merlin, O.[Olivier], Molero, B.[Beatriz], Suere, C.[Christophe], Olivera-Guerra, L.[Luis], Hssaine, B.A.[Bouchra Ait], Amazirh, A.[Abdelhakim], Bitar, A.A.[Ahmad Al], Escorihuela, M.J.[Maria Jose], Er-Raki, S.[Salah],
Stepwise Disaggregation of SMAP Soil Moisture at 100 m Resolution Using Landsat-7/8 Data and a Varying Intermediate Resolution,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Ghilain, N.[Nicolas], Arboleda, A.[Alirio], Batelaan, O.[Okke], Ardö, J.[Jonas], Trigo, I.[Isabel], Barrios, J.M.[Jose-Miguel], Gellens-Meulenberghs, F.[Francoise],
A New Retrieval Algorithm for Soil Moisture Index from Thermal Infrared Sensor On-Board Geostationary Satellites over Europe and Africa and Its Validation,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Song, P., Huang, J., Mansaray, L.R., Wen, H., Wu, H., Liu, Z., Wang, X.,
An Improved Soil Moisture Retrieval Algorithm Based on the Land Parameter Retrieval Model for Water-Land Mixed Pixels Using AMSR-E Data,
GeoRS(57), No. 10, October 2019, pp. 7643-7657.
IEEE DOI 1910
data assimilation, hydrological techniques, land surface temperature, moisture, radiometers, radiometry, surface soil moisture (SSM) 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

Rodriguez-Alvarez, N.[Nereida], Misra, S.[Sidharth], Podest, E.[Erika], Morris, M.[Mary], Bosch-Lluis, X.[Xavier],
The Use of SMAP-Reflectometry in Science Applications: Calibration and Capabilities,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Walker, V.A.[Victoria A.], Hornbuckle, B.K.[Brian K.], Cosh, M.H.[Michael H.], Prueger, J.H.[John H.],
Seasonal Evaluation of SMAP Soil Moisture in the U.S. Corn Belt,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Ymeti, I.[Irena], Shrestha, D.P.[Dhruba Pikha], van der Meer, F.[Freek],
Monitoring Soil Surface Mineralogy at Different Moisture Conditions Using Visible Near-Infrared Spectroscopy Data,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Tian, Y.F.[Yi-Fei], Xiong, L.H.[Li-Hua], Xiong, B.[Bin], Zhuang, R.D.[Ruo-Dan],
A Prior Estimation of the Spatial Distribution Parameter of Soil Moisture Storage Capacity Using Satellite-Based Root-Zone Soil Moisture Data,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Zappa, L.[Luca], Forkel, M.[Matthias], Xaver, A.[Angelika], Dorigo, W.[Wouter],
Deriving Field Scale Soil Moisture from Satellite Observations and Ground Measurements in a Hilly Agricultural Region,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Xie, Q.X.[Qiu-Xia], Menenti, M.[Massimo], Jia, L.[Li],
Improving the AMSR-E/NASA Soil Moisture Data Product Using In-Situ Measurements from the Tibetan Plateau,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Zhu, X.F.[Xiu-Fang], Pan, Y.Z.[Yao-Zhong], Wang, J.X.[Jun-Xia], Liu, Y.[Ying],
A Cuboid Model for Assessing Surface Soil Moisture,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Soldo, Y.[Yan], Le Vine, D.[David], de Matthaeis, P.[Paolo],
Detection of Residual 'Hot Spots' in RFI-Filtered SMAP Data,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Tan, K.[Kai], Chen, J.[Jin], Zhang, W.G.[Wei-Guo], Liu, K.[Kunbo], Tao, P.J.[Peng-Jie], Cheng, X.J.[Xiao-Jun],
Estimation of soil surface water contents for intertidal mudflats using a near-infrared long-range terrestrial laser scanner,
PandRS(159), 2020, pp. 129-139.
Elsevier DOI 1912
Terrestrial laser scanning, Intensity correction, Mudflat, Intertidal zone, Surface soil moisture, Water content BibRef

Jin, J.L.[Jun-Ling], de Sloover, L.[Lars], Verbeurgt, J.[Jeffrey], Stal, C.[Cornelis], Deruyter, G.[Greet], Montreuil, A.L.[Anne-Lise], de Maeyer, P.[Philippe], de Wulf, A.[Alain],
Measuring Surface Moisture on a Sandy Beach based on Corrected Intensity Data of a Mobile Terrestrial LiDAR,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001
BibRef

Cui, Y.[Yaokui], Chen, X.[Xi], Xiong, W.T.[Wen-Tao], He, L.[Lian], Lv, F.[Feng], Fan, W.J.[Wen-Jie], Luo, Z.L.[Zeng-Liang], Hong, Y.[Yang],
A Soil Moisture Spatial and Temporal Resolution Improving Algorithm Based on Multi-Source Remote Sensing Data and GRNN Model,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Pellarin, T.[Thierry], Román-Cascón, C.[Carlos], Baron, C.[Christian], Bindlish, R.[Rajat], Brocca, L.[Luca], Camberlin, P.[Pierre], Fernández-Prieto, D.[Diego], Kerr, Y.H.[Yann H.], Massari, C.[Christian], Panthou, G.[Geremy], Perrimond, B.[Benoit], Philippon, N.[Nathalie], Quantin, G.[Guillaume],
The Precipitation Inferred from Soil Moisture (PrISM) Near Real-Time Rainfall Product: Evaluation and Comparison,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Zhuang, R.[Ruodan], Zeng, Y.J.[Yi-Jian], Manfreda, S.[Salvatore], Su, Z.[Zhongbo],
Quantifying Long-Term Land Surface and Root Zone Soil Moisture over Tibetan Plateau,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Liang, M.Y.[Meng-Yu], Pause, M.[Marion], Prechtel, N.[Nikolas], Schramm, M.[Matthias],
Regionalization of Coarse Scale Soil Moisture Products Using Fine-Scale Vegetation Indices: Prospects and Case Study,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Llamas, R.M.[Ricardo M.], Guevara, M.[Mario], Rorabaugh, D.[Danny], Taufer, M.[Michela], Vargas, R.[Rodrigo],
Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture Based on Geostatistical Techniques and Multiple Regression,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Rodriguez-Alvarez, N.[Nereida], Misra, S.[Sidharth], Morris, M.[Mary],
The Polarimetric Sensitivity of SMAP-Reflectometry Signals to Crop Growth in the U.S. Corn Belt,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Kovacevic, J.[Jovan], Cvijetinovic, Ž.[Željko], Stancic, N.[Nikola], Brodic, N.[Nenad], Mihajlovic, D.[Dragan],
New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004
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

Kasim, A.A.[Abba Aliyu], Carlson, T.N.[Toby Nahum], Usman, H.S.[Haruna Shehu],
Limitations in Validating Derived Soil Water Content from Thermal/Optical Measurements Using the Simplified Triangle Method,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Oozeer, Y.[Yaasiin], Fletcher, C.G.[Christopher G.], Champagne, C.[Catherine],
Evaluation of Satellite-Derived Surface Soil Moisture Products over Agricultural Regions of Canada,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Baugh, C.[Calum], de Rosnay, P.[Patricia], Lawrence, H.[Heather], Jurlina, T.[Toni], Drusch, M.[Matthias], Zsoter, E.[Ervin], Prudhomme, C.[Christel],
The Impact of SMOS Soil Moisture Data Assimilation within the Operational Global Flood Awareness System (GloFAS),
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Chaubell, M.J., Yueh, S.H., Dunbar, R.S., Colliander, A., Chen, F., Chan, S.K., Entekhabi, D., Bindlish, R., O'Neill, P.E., Asanuma, J., Berg, A.A., Bosch, D.D., Caldwell, T., Cosh, M.H., Collins, C.H.[C. Holifield], Martínez-Fernández, J., Seyfried, M., Starks, P.J., Su, Z., Thibeault, M., Walker, J.,
Improved SMAP Dual-Channel Algorithm for the Retrieval of Soil Moisture,
GeoRS(58), No. 6, June 2020, pp. 3894-3905.
IEEE DOI 2005
Dual-channel algorithm (DCA), soil moisture active passive (SMAP), vegetation optical depth (VOD) retrieval BibRef

Chew, C.[Clara], Small, E.[Eric],
Description of the UCAR/CU Soil Moisture Product,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Ju, F.[Feng], An, R.[Ru], Yang, Z.[Zhen], Huang, L.J.[Li-Jun], Sun, Y.X.[Ya-Xing],
Assimilating SMOS Brightness Temperature for Hydrologic Model Parameters and Soil Moisture Estimation with an Immune Evolutionary Strategy,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Ambadan, J.T.[Jaison Thomas], Oja, M.[Matilda], Gedalof, Z.[Ze'ev], Berg, A.A.[Aaron A.],
Satellite-Observed Soil Moisture as an Indicator of Wildfire Risk,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Oliva, R.[Roger], Martín-Neira, M.[Manuel], Corbella, I.[Ignasi], Closa, J.[Josep], Zurita, A.[Albert], Cabot, F.[François], Khazaal, A.[Ali], Richaume, P.[Philippe], Kainulainen, J.[Juha], Barbosa, J.[Jose], Lopes, G.[Gonçalo], Tenerelli, J.[Joseph], Díez-García, R.[Raul], González-Gambau, V.[Veronica], Crapolicchio, R.[Raffaele],
SMOS Third Mission Reprocessing after 10 Years in Orbit,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Rubino, R.[Roselena], Duffo, N.[Nuria], González-Gambau, V.[Verónica], Corbella, I.[Ignasi], Torres, F.[Francesc], Durán, I.[Israel], Martín-Neira, M.[Manuel],
Deriving VTEC Maps from SMOS Radiometric Data,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
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Yang, T.[Ting], Wan, W.[Wei], Sun, Z.G.[Zhi-Gang], Liu, B.J.[Bao-Jian], Li, S.[Sen], Chen, X.[Xiuwan],
Comprehensive Evaluation of Using TechDemoSat-1 and CYGNSS Data to Estimate Soil Moisture over Mainland China,
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Can We Use Satellite-Based Soil-Moisture Products at High Resolution to Investigate Land-Use Differences and Land-Atmosphere Interactions? A Case Study in the Savanna,
RS(12), No. 11, 2020, pp. xx-yy.
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Liu, Z.H.[Zhen-Hua], Zhao, L.[Li], Peng, Y.P.[Yi-Ping], Wang, G.X.[Guang-Xing], Hu, Y.M.[Yue-Ming],
Improving Estimation of Soil Moisture Content Using a Modified Soil Thermal Inertia Model,
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Tollerud, H.J.[Heather J.], Brown, J.F.[Jesslyn F.], Loveland, T.R.[Thomas R.],
Investigating the Effects of Land Use and Land Cover on the Relationship between Moisture and Reflectance Using Landsat Time Series,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link 2006
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Han, L.[Leran], Wang, C.M.[Chun-Mei], Yu, T.[Tao], Gu, X.F.[Xing-Fa], Liu, Q.Y.[Qi-Yue],
High-Precision Soil Moisture Mapping Based on Multi-Model Coupling and Background Knowledge, Over Vegetated Areas Using Chinese GF-3 and GF-1 Satellite Data,
RS(12), No. 13, 2020, pp. xx-yy.
DOI Link 2007
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Wu, X.T.[Xiao-Tao], Lu, G.H.[Gui-Hua], Wu, Z.Y.[Zhi-Yong], He, H.[Hai], Scanlon, T.[Tracy], Dorigo, W.[Wouter],
Triple Collocation-Based Assessment of Satellite Soil Moisture Products with In Situ Measurements in China: Understanding the Error Sources,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
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Liu, J.[Jing], Liu, Q.H.[Qin-Huo],
Soil Moisture Estimate Uncertainties from the Effect of Soil Texture on Dielectric Semiempirical Models,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
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Bai, X.[Xiao], Zhang, L.[Lanhui], He, C.S.[Chan-Sheng], Zhu, Y.[Yi],
Estimating Regional Soil Moisture Distribution Based on NDVI and Land Surface Temperature Time Series Data in the Upstream of the Heihe River Watershed, Northwest China,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
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Nie, Y.[Yan], Tan, Y.[Ying], Deng, Y.Q.[Yu-Qin], Yu, J.[Jing],
Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008
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Yan, R.[Ran], Bai, J.J.[Jian-Jun],
A New Approach for Soil Moisture Downscaling in the Presence of Seasonal Difference,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
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Jamei, M.[Mozhdeh], Baygi, M.M.[Mohammad Mousavi], Oskouei, E.A.[Ebrahim Asadi], Lopez-Baeza, E.[Ernesto],
Validation of the SMOS Level 1C Brightness Temperature and Level 2 Soil Moisture Data over the West and Southwest of Iran,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Yin, J.[Jifu], Zhan, X.[Xiwu], Liu, J.[Jicheng],
NOAA Satellite Soil Moisture Operational Product System (SMOPS) Version 3.0 Generates Higher Accuracy Blended Satellite Soil Moisture,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
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Yuan, L.[Lina], Li, L.[Long], Zhang, T.[Ting], Chen, L.Q.[Long-Qian], Zhao, J.L.[Jian-Lin], Hu, S.[Sai], Cheng, L.[Liang], Liu, W.Q.[Wei-Qiang],
Soil Moisture Estimation for the Chinese Loess Plateau using MODIS-derived ATI and TVDI,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
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Park, C.H.[Chang-Hwan], Jagdhuber, T.[Thomas], Colliander, A.[Andreas], Lee, J.[Johan], Berg, A.[Aaron], Cosh, M.[Michael], Kim, S.B.[Seung-Bum], Kim, Y.[Yoonjae], Wulfmeyer, V.[Volker],
Parameterization of Vegetation Scattering Albedo in the Tau-Omega Model for Soil Moisture Retrieval on Croplands,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
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van der Vliet, M.[Mendy], van der Schalie, R.[Robin], Rodriguez-Fernandez, N.[Nemesio], Colliander, A.[Andreas], de Jeu, R.[Richard], Preimesberger, W.[Wolfgang], Scanlon, T.[Tracy], Dorigo, W.[Wouter],
Reconciling Flagging Strategies for Multi-Sensor Satellite Soil Moisture Climate Data Records,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
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Bayad, M.[Mohamed], Chau, H.W.[Henry Wai], Trolove, S.[Stephen], Müller, K.[Karin], Condron, L.[Leo], Moir, J.[Jim], Yi, L.[Li],
Time series of remote sensing and water deficit to predict the occurrence of soil water repellency in New Zealand pastures,
PandRS(169), 2020, pp. 292-300.
Elsevier DOI 2011
Soil water repellency, Remote sensing, Satellite image time series, Support vector machine BibRef

Kimura, R.[Reiji], Moriyama, M.[Masao],
Use of a Satellite-Based Aridity Index to Monitor Decreased Soil Water Content and Grass Growth in Grasslands of North-East Asia,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
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Mousa, B.G., Shu, H.[Hong], Freeshah, M.[Mohamed], Tariq, A.[Aqil],
A Novel Scheme for Merging Active and Passive Satellite Soil Moisture Retrievals Based on Maximizing the Signal to Noise Ratio,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
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Gómez, B.[Breogán], Charlton-Pérez, C.L.[Cristina L.], Lewis, H.[Huw], Candy, B.[Brett],
The Met Office Operational Soil Moisture Analysis System,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Han, L.[Leran], Wang, C.M.[Chun-Mei], Liu, Q.Y.[Qi-Yue], Wang, G.K.[Geng-Ke], Yu, T.[Tao], Gu, X.F.[Xing-Fa], Zhang, Y.Z.[Yun-Zhou],
Soil Moisture Mapping Based on Multi-Source Fusion of Optical, Near-Infrared, Thermal Infrared, and Digital Elevation Model Data via the Bayesian Maximum Entropy Framework,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Zhang, W.[Wei], Yi, S.H.[Shu-Hua], Qin, Y.[Yu], Sun, Y.[Yi], Shangguan, D.H.[Dong-Hui], Meng, B.P.[Bao-Ping], Li, M.[Meng], Zhang, J.G.[Jian-Guo],
Effects of Patchiness on Surface Soil Moisture of Alpine Meadow on the Northeastern Qinghai-Tibetan Plateau: Implications for Grassland Restoration,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Jagdhuber, T., Montzka, C., Lopez-Martinez, C., Baur, M.J., Link, M., Piles, M., Das, N.N., Jonard, F.,
Estimation of Vegetation Structure Parameters From SMAP Radar Intensity Observations,
GeoRS(59), No. 1, January 2021, pp. 151-167.
IEEE DOI 2012
Vegetation mapping, Scattering, Backscatter, Synthetic aperture radar, Shape, Estimation, Discrete scatterer, vegetation structure BibRef

Gu, H.B.[Hai-Bin], Lin, Z.[Zhe], Guo, W.X.[Wen-Xuan], Deb, S.[Sanjit],
Retrieving Surface Soil Water Content Using a Soil Texture Adjusted Vegetation Index and Unmanned Aerial System Images,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Cao, Z.[Zetao], Gao, H.X.[Hong-Xia], Nan, Z.T.[Zhuo-Tong], Zhao, Y.[Yi], Yin, Z.Y.[Zi-Yun],
A Semi-Physical Approach for Downscaling Satellite Soil Moisture Data in a Typical Cold Alpine Area, Northwest China,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Borbas, E.E.[Eva E.], Menzel, P.W.[Paul W.],
Observed HIRS and Aqua MODIS Thermal Infrared Moisture Determinations in the 2000s,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Natsagdorj, E.[Enkhjargal], Renchin, T.[Tsolmon], de Maeyer, P.[Philippe], Darkhijav, B.[Bayanjargal],
Spatial Distribution of Soil Moisture in Mongolia Using SMAP and MODIS Satellite Data: A Time Series Model (2010-2025),
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Jin, J.L.[Jun-Ling], Verbeurgt, J.[Jeffrey], de Sloover, L.[Lars], Stal, C.[Cornelis], Deruyter, G.[Greet], Montreuil, A.L.[Anne-Lise], Vos, S.[Sander], de Maeyer, P.[Philippe], de Wulf, A.[Alain],
Monitoring spatiotemporal variation in beach surface moisture using a long-range terrestrial laser scanner,
PandRS(173), 2021, pp. 195-208.
Elsevier DOI 2102
Beach surface moisture, Terrestrial laser scanning, Intensity correction, Aeolian sand transport BibRef

Yuan, L.[Lina], Li, L.[Long], Zhang, T.[Ting], Chen, L.Q.[Long-Qian], Zhao, J.L.[Jian-Lin], Liu, W.Q.[Wei-Qiang], Cheng, L.[Liang], Hu, S.[Sai], Yang, L.H.[Long-Hua], Wen, M.X.[Ming-Xin],
Improving Soil Moisture Estimation by Identification of NDVI Thresholds Optimization: An Application to the Chinese Loess Plateau,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Ahmed, A.A.M.[A. A. Masrur], Deo, R.C.[Ravinesh C], Raj, N.[Nawin], Ghahramani, A.[Afshin], Feng, Q.[Qi], Yin, Z.L.[Zhen-Liang], Yang, L.S.[Lin-Shan],
Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Levy, J.S.[Joseph S.], Johnson, J.T.E.[Jessica T. E.],
Remote Soil Moisture Measurement from Drone-Borne Reflectance Spectroscopy: Applications to Hydroperiod Measurement in Desert Playas,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Stefan, V.G.[Vivien-Georgiana], Indrio, G.[Gianfranco], Escorihuela, M.J.[Maria-José], Quintana-Seguí, P.[Pere], Villar, J.M.[Josep Maria],
High-Resolution SMAP-Derived Root-Zone Soil Moisture Using an Exponential Filter Model Calibrated per Land Cover Type,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Ge, X.Y.[Xiang-Yu], Ding, J.[Jianli], Jin, X.[Xiuliang], Wang, J.Z.[Jing-Zhe], Chen, X.Y.[Xiang-Yue], Li, X.H.[Xiao-Hang], Liu, J.[Jie], Xie, B.Q.[Bo-Qiang],
Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Steele-Dunne, S.C.[Susan C.], Hahn, S.[Sebastian], Wagner, W.[Wolfgang], Vreugdenhil, M.[Mariette],
Towards Including Dynamic Vegetation Parameters in the EUMETSAT H SAF ASCAT Soil Moisture Products,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Tang, M.L.[Ming-Liang], Esmaeili, K.[Kamran],
Heap Leach Pad Surface Moisture Monitoring Using Drone-Based Aerial Images and Convolutional Neural Networks: A Case Study at the El Gallo Mine, Mexico,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Dai, E.[Eryan], Gasiewski, A.J.[Albin J.], Venkitasubramony, A.[Aravind], Stachura, M.[Maciej], Elston, J.[Jack],
High Spatial Resolution Soil Moisture Mapping Using a Lobe Differencing Correlation Radiometer on a Small Unmanned Aerial System,
GeoRS(59), No. 5, May 2021, pp. 4062-4079.
IEEE DOI 2104
Moisture, Antennas, Soil moisture, Calibration, Spatial resolution, Soil measurements, High spatial resolution soil moisture map, soil-vegetation radiative transfer (SVRT) model BibRef

Ramsauer, T.[Thomas], Weiß, T.[Thomas], Löw, A.[Alexander], Marzahn, P.[Philip],
RADOLAN_API: An Hourly Soil Moisture Data Set Based on Weather Radar, Soil Properties and Reanalysis Temperature Data,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

di Biase, V.[Valeria], Hanssen, R.F.[Ramon F.], Vos, S.E.[Sander E.],
Sensitivity of Near-Infrared Permanent Laser Scanning Intensity for Retrieving Soil Moisture on a Coastal Beach: Calibration Procedure Using In Situ Data,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Paruta, A.[Antonio], Ciraolo, G.[Giuseppe], Capodici, F.[Fulvio], Manfreda, S.[Salvatore], Sasso, S.F.D.[Silvano Fortunato Dal], Zhuang, R.[Ruodan], Romano, N.[Nunzio], Nasta, P.[Paolo], Ben-Dor, E.[Eyal], Francos, N.[Nicolas], Zeng, Y.J.[Yi-Jian], Maltese, A.[Antonino],
A Geostatistical Approach to Map Near-Surface Soil Moisture Through Hyperspatial Resolution Thermal Inertia,
GeoRS(59), No. 6, June 2021, pp. 5352-5369.
IEEE DOI 2106
Soil, Soil measurements, Spatial resolution, Thermal sensors, Microwave imaging, Microwave theory and techniques, variogram analysis BibRef

Greifeneder, F.[Felix], Notarnicola, C.[Claudia], Wagner, W.[Wolfgang],
A Machine Learning-Based Approach for Surface Soil Moisture Estimations with Google Earth Engine,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Ryu, S.[Sumin], Kwon, Y.J.[Young-Joo], Kim, G.[Goo], Hong, S.[Sungwook],
Temperature Vegetation Dryness Index-Based Soil Moisture Retrieval Algorithm Developed for Geo-KOMPSAT-2A,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Srivastava, P.K.[Prashant K.], Petropoulos, G.P.[George P.], Prasad, R.[Rajendra], Triantakonstantis, D.[Dimitris],
Random Forests with Bagging and Genetic Algorithms Coupled with Least Trimmed Squares Regression for Soil Moisture Deficit Using SMOS Satellite Soil Moisture,
IJGI(10), No. 8, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Chen, K.[Kun], Cao, X.Y.[Xin-Yun], Shen, F.[Fei], Ge, Y.L.[Yu-Long],
An Improved Method of Soil Moisture Retrieval Using Multi-Frequency SNR Data,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Shen, F.[Fei], Sui, M.M.[Ming-Ming], Zhu, Y.F.[Yi-Fan], Cao, X.Y.[Xin-Yun], Ge, Y.L.[Yu-Long], Wei, H.H.[Hao-Han],
Using BDS MEO and IGSO Satellite SNR Observations to Measure Soil Moisture Fluctuations Based on the Satellite Repeat Period,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Ma, C.F.[Chun-Feng], Wang, S.G.[Shu-Guo], Zhao, Z.B.[Ze-Bin], Ma, H.Q.[Han-Qing],
Global Sensitivity Analysis of a Water Cloud Model toward Soil Moisture Retrieval over Vegetated Agricultural Fields,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Voronovich, A.G.[Alexander G.], Lataitis, R.J.[Richard J.],
Soil Moisture Retrieval Using Reflection Coefficients: Numerical Experiments,
GeoRS(59), No. 11, November 2021, pp. 8957-8967.
IEEE DOI 2111
Soil, Soil moisture, Vegetation mapping, Satellites, Interference, Soil measurements, Moisture, Geophysical measurement techniques, soil moisture BibRef

Yin, Q.[Qiang], Li, J.L.[Jun-Lang], Ma, F.[Fei], Xiang, D.L.[De-Liang], Zhang, F.[Fan],
Dual-Channel Convolutional Neural Network for Bare Surface Soil Moisture Inversion Based on Polarimetric Scattering Models,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Sun, H.[Hao], Liu, H.[Hao], Ma, Y.H.[Yan-Hui], Xia, Q.[Qunbo],
Optical Remote Sensing Indexes of Soil Moisture: Evaluation and Improvement Based on Aircraft Experiment Observations,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhang, L.J.[Li-Jie], Zeng, Y.J.[Yi-Jian], Zhuang, R.[Ruodan], Szabó, B.[Brigitta], Manfreda, S.[Salvatore], Han, Q.Q.[Qian-Qian], Su, Z.[Zhongbo],
In Situ Observation-Constrained Global Surface Soil Moisture Using Random Forest Model,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Wang, B.Q.[Bing-Quan], Ran, Y.[Youhua],
Diversity of Remote Sensing-Based Variable Inputs Improves the Estimation of Seasonal Maximum Freezing Depth,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Piles, M.[María], Muñoz-Marí, J.[Jordi], Guerrero-Curieses, A.[Alicia], Camps-Valls, G.[Gustau], Rojo-Álvarez, J.L.[José Luis],
Autocorrelation Metrics to Estimate Soil Moisture Persistence From Satellite Time Series: Application to Semiarid Regions,
GeoRS(60), 2022, pp. 1-17.
IEEE DOI 2112
Correlation, Satellite broadcasting, Microwave radiometry, Time series analysis, Estimation, Sea measurements, Measurement, spatial-temporal BibRef

Chakhar, A.[Amal], Hernández-López, D.[David], Ballesteros, R.[Rocío], Moreno, M.A.[Miguel A.],
Improvement of the Soil Moisture Retrieval Procedure Based on the Integration of UAV Photogrammetry and Satellite Remote Sensing Information,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Carbó, E.[Ester], Juan, P.[Pablo], Añó, C.[Carlos], Chaudhuri, S.[Somnath], Diaz-Avalos, C.[Carlos], López-Baeza, E.[Ernesto],
Modeling Influence of Soil Properties in Different Gradients of Soil Moisture: The Case of the Valencia Anchor Station Validation Site, Spain,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Paolini, G.[Giovanni], Escorihuela, M.J.[Maria Jose], Bellvert, J.[Joaquim], Merlin, O.[Olivier],
Disaggregation of SMAP Soil Moisture at 20 m Resolution: Validation and Sub-Field Scale Analysis,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Rahman, A.[Azbina], Maggioni, V.[Viviana], Zhang, X.X.[Xin-Xuan], Houser, P.[Paul], Sauer, T.[Timothy], Mocko, D.M.[David M.],
The Joint Assimilation of Remotely Sensed Leaf Area Index and Surface Soil Moisture into a Land Surface Model,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Khandan, R.[Reza], Wigneron, J.P.[Jean-Pierre], Bonafoni, S.[Stefania], Biazar, A.P.[Arastoo Pour], Gholamnia, M.[Mehdi],
Assimilation of Satellite-Derived Soil Moisture and Brightness Temperature in Land Surface Models: A Review,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Zhang, Y.F.[Yu-Fang], Liang, S.L.[Shun-Lin], Zhu, Z.L.[Zhi-Liang], Ma, H.[Han], He, T.[Tao],
Soil Moisture Content Retrieval from Landsat 8 Data Using Ensemble Learning,
PandRS(185), 2022, pp. 32-47.
Elsevier DOI 2202
Soil moisture, High resolution, Landsat, ISMN, Ensemble learning BibRef

Zhang, H.Y.[Hong-Yan], Wang, S.D.[Shu-Dong], Liu, K.[Kai], Li, X.[Xueke], Li, Z.Q.[Zheng-Qiang], Zhang, X.Y.[Xiao-Yuan], Liu, B.X.[Bing-Xuan],
Downscaling of AMSR-E Soil Moisture over North China Using Random Forest Regression,
IJGI(11), No. 2, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Luo, P.[Peng], Song, Y.Z.[Yong-Ze], Huang, X.[Xin], Ma, H.L.[Hong-Liang], Liu, J.[Jin], Yao, Y.[Yao], Meng, L.Q.[Li-Qiu],
Identifying determinants of spatio-temporal disparities in soil moisture of the Northern Hemisphere using a geographically optimal zones-based heterogeneity model,
PandRS(185), 2022, pp. 111-128.
Elsevier DOI 2202
Spatial heterogeneity, Soil moisture, Spatial determinants, Geographically optimal zones-based heterogeneity model, Spatial statistics BibRef

Guan, Y.[Yunyi], Grote, K.[Katherine], Schott, J.[Joel], Leverett, K.[Kelsi],
Prediction of Soil Water Content and Electrical Conductivity Using Random Forest Methods with UAV Multispectral and Ground-Coupled Geophysical Data,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Hao, G.B.[Gui-Bin], Su, H.B.[Hong-Bo], Zhang, R.H.[Ren-Hua], Tian, J.[Jing], Chen, S.H.[Shao-Hui],
A Two-Source Normalized Soil Thermal Inertia Model for Estimating Field-Scale Soil Moisture from MODIS and ASTER Data,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Li, W.J.[Wei-Jiao], Wang, Y.P.[Yun-Peng], Yang, J.X.[Jing-Xue], Deng, Y.J.[Yu-Jiao],
Time-Lag Effect of Vegetation Response to Volumetric Soil Water Content: A Case Study of Guangdong Province, Southern China,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Yin, J.[Jifu], Zhan, X.[Xiwu], Liu, J.[Jicheng], Ferraro, R.R.[Ralph R.],
A New Method for Generating the SMOPS Blended Satellite Soil Moisture Data Product without Relying on a Model Climatology,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Ming, W.T.[Wen-Ting], Ji, X.[Xuan], Zhang, M.[Mingda], Li, Y.G.[Yun-Gang], Liu, C.[Chang], Wang, Y.F.[Yin-Fei], Li, J.Q.[Ji-Qiu],
A Hybrid Triple Collocation-Deep Learning Approach for Improving Soil Moisture Estimation from Satellite and Model-Based Data,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Brown, J.P.[Jordan P.], Long, D.G.[David G.],
Resolution Enhancement of SMAP Passive Soil Moisture Estimates,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Yang, Y.Q.[Yan-Qing], Bao, Z.X.[Zhen-Xin], Wu, H.[Houfa], Wang, G.Q.[Guo-Qing], Liu, C.[Cuishan], Wang, J.[Jie], Zhang, J.Y.[Jian-Yun],
An Exponential Filter Model-Based Root-Zone Soil Moisture Estimation Methodology from Multiple Datasets,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Gupta, S.[Surya], Papritz, A.[Andreas], Lehmann, P.[Peter], Hengl, T.[Tomislav], Bonetti, S.[Sara], Or, D.[Dani],
Global Mapping of Soil Water Characteristics Parameters: Fusing Curated Data with Machine Learning and Environmental Covariates,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Xu, M.[Ming], Li, H.P.[Hong-Ping], Chen, H.H.[Hai-Hua], Yin, X.B.[Xia-Bin],
Quantitative Measurement of Radio Frequency Interference for SMOS Mission,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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

de Lima, R.S.[Raul Sampaio], Li, K.Y.[Kai-Yun], Vain, A.[Ants], Lang, M.[Mait], Bergamo, T.F.[Thaisa Fernandes], Kokamägi, K.[Kaupo], Burnside, N.G.[Niall G.], Ward, R.D.[Raymond D.], Sepp, K.[Kalev],
The Potential of Optical UAS Data for Predicting Surface Soil Moisture in a Peatland across Time and Sites,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Llamas, R.M.[Ricardo M.], Valera, L.[Leobardo], Olaya, P.[Paula], Taufer, M.[Michela], Vargas, R.[Rodrigo],
Downscaling Satellite Soil Moisture Using a Modular Spatial Inference Framework,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Nie, S.[Shihai], Wang, Y.X.[Yan-Xia], Tu, J.S.[Jin-Sheng], Li, P.[Peng], Xu, J.H.[Jian-Hui], Li, N.[Nan], Wang, M.[Mengke], Huang, D.[Danni], Song, J.[Jia],
Retrieval of Soil Moisture Content Based on Multisatellite Dual-Frequency Combination Multipath Errors,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Chen, H.[He], Lin, R.[Rencai], Zhang, B.Z.[Bao-Zhong], Wei, Z.[Zheng],
Improving Soil Water Content and Surface Flux Estimation Based on Data Assimilation Technique,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Hu, Z.X.[Zi-Xuan], Chai, L.[Linna], Crow, W.T.[Wade T.], Liu, S.M.[Shao-Min], Zhu, Z.L.[Zhong-Li], Zhou, J.[Ji], Qu, Y.Q.[Yu-Quan], Liu, J.[Jin], Yang, S.Q.[Shi-Qi], Lu, Z.[Zheng],
Applying a Wavelet Transform Technique to Optimize General Fitting Models for SM Analysis: A Case Study in Downscaling over the Qinghai-Tibet Plateau,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Du, J.Y.[Jin-Yang], Kimball, J.S.[John S.], Bindlish, R.[Rajat], Walker, J.P.[Jeffrey P.], Watts, J.D.[Jennifer D.],
Local Scale (3-m) Soil Moisture Mapping Using SMAP and Planet SuperDove,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Acharya, U.[Umesh], Daigh, A.L.M.[Aaron L. M.], Oduor, P.G.[Peter G.],
Soil Moisture Mapping with Moisture-Related Indices, OPTRAM, and an Integrated Random Forest-OPTRAM Algorithm from Landsat 8 Images,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Cui, X.[Xia], Xu, G.[Gang], He, X.F.[Xiao-Fei], Luo, D.[Danqi],
Influences of Seasonal Soil Moisture and Temperature on Vegetation Phenology in the Qilian Mountains,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Mao, T.N.[Tao-Ning], Wei, S.G.[Shang-Guan], Li, Q.L.[Qing-Liang], Li, L.[Lu], Zhang, Y.[Ye], Huang, F.[Feini], Li, J.[Jianduo], Liu, W.[Wei], Zhang, R.[Ruqing],
A Spatial Downscaling Method for Remote Sensing Soil Moisture Based on Random Forest Considering Soil Moisture Memory and Mass Conservation,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Zhang, L.[Li], Lv, X.L.[Xiao-Lei], Wang, R.[Rui],
Soil Moisture Estimation Based on Polarimetric Decomposition and Quantile Regression Forests,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Farahani, A.[Ali], Moradikhaneghahi, M.[Mahsa], Ghayoomi, M.[Majid], Jacobs, J.M.[Jennifer M.],
Application of Soil Moisture Active Passive (SMAP) Satellite Data in Seismic Response Assessment,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Liu, Y.[Yi], Chen, R.Q.[Rui-Qi], Yuan, S.S.[Shan-Shui], Ren, L.L.[Li-Liang], Zhang, X.X.[Xiao-Xiang], Liu, C.J.[Chang-Jun], Ma, Q.[Qiang],
Satellite Soil Moisture Data Reconstruction in the Temporal and Spatial Domains: Latent Error Assessments and Performances for Tracing Rainstorms and Droughts,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Zhang, E.[Ermei], Liu, Y.J.[Yu-Jie], Pan, T.[Tao], Tan, Q.H.[Qing-Hua], Ma, Z.[Zhiang],
Evaluating the Effects of Climate Change and Human Activities on the Seasonal Trends and Spatial Heterogeneity of Soil Moisture,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Li, H.Y.[Hong-Yi], Xiao, Z.[Ziniu], Wei, J.[Junhong], Wang, G.[Ge],
The Seasonal and Diurnal Variation Characteristics of Soil Moisture at Different Depths from Observational Sites over the Tibetan Plateau,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Zhao, J.H.[Jian-Hui], Zhang, C.Y.[Chen-Yang], Min, L.[Lin], Guo, Z.W.[Zheng-Wei], Li, N.[Ning],
Retrieval of Farmland Surface Soil Moisture Based on Feature Optimization and Machine Learning,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Wernicke, L.J.[Liza J.], Chew, C.C.[Clara C.], Small, E.E.[Eric E.], Das, N.N.[Narendra N.],
Downscaling SMAP Brightness Temperatures to 3 km Using CYGNSS Reflectivity Observations: Factors That Affect Spatial Heterogeneity,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
BibRef

Deng, K.A.K.[Khidir Abdalla Kwal], Petropoulos, G.P.[George P.], Bao, Y.S.[Yan-Song], Pavlides, A.[Andrew], Chaibou, A.A.S.[Abdoul Aziz Saidou], Habtemicheal, B.A.[Birhanu Asmerom],
An Examination of the SMAP Operational Soil Moisture Products Accuracy at the Tibetan Plateau,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Mu, T.H.[Tian-Hao], Liu, G.[Guiwei], Yang, X.[Xiguang], Yu, Y.[Ying],
Soil-Moisture Estimation Based on Multiple-Source Remote-Sensing Images,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Zhang, Y.[Ye], Huang, F.[Feini], Li, L.[Lu], Li, Q.L.[Qing-Lian], Zhang, Y.[Yongkun], Shangguan, W.[Wei],
Real-Time Forecast of SMAP L3 Soil Moisture Using Spatial-Temporal Deep Learning Model with Data Integration,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Cheng, L.[Lin], Liu, S.[Suxia], Mo, X.G.[Xing-Guo], Hu, S.[Shi], Zhou, H.[Haowei], Xie, C.S.[Chao-Shuai], Nielsen, S.[Sune], Grosen, H.[Henrik], Bauer-Gottwein, P.[Peter],
Assessing the Potential of 10-m Resolution TVDI Based on Downscaled LST to Monitor Soil Moisture in Tang River Basin, China,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Nadeem, A.A.[Adeel Ahmad], Zha, Y.Y.[Yuan-Yuan], Shi, L.S.[Liang-Sheng], Ali, S.[Shoaib], Wang, X.[Xi], Zafar, Z.[Zeeshan], Afzal, Z.[Zeeshan], Tariq, M.A.U.R.[Muhammad Atiq Ur Rehman],
Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Huang, S.[Shuzhe], Zhang, X.[Xiang], Wang, C.[Chao], Chen, N.C.[Neng-Cheng],
Two-step fusion method for generating 1km seamless multi-layer soil moisture with high accuracy in the Qinghai-Tibet plateau,
PandRS(197), 2023, pp. 346-363.
Elsevier DOI 2303
Multi-layer soil moisture, High resolution, Seamless, High accuracy, The Qinghai-Tibet plateau BibRef

Ma, Y.T.[Yu-Tiao], Hou, P.[Peng], Zhang, L.J.[Lin-Jing], Cao, G.Z.[Guang-Zhen], Sun, L.[Lin], Pang, S.[Shulin], Bai, J.J.[Jun-Jun],
High-Resolution Quantitative Retrieval of Soil Moisture Based on Multisource Data Fusion with Random Forests: A Case Study in the Zoige Region of the Tibetan Plateau,
RS(15), No. 6, 2023, pp. 1531.
DOI Link 2304
BibRef

Dabboor, M.[Mohammed], Atteia, G.[Ghada], Meshoul, S.[Souham], Alayed, W.[Walaa],
Deep Learning-Based Framework for Soil Moisture Content Retrieval of Bare Soil from Satellite Data,
RS(15), No. 7, 2023, pp. 1916.
DOI Link 2304
BibRef

Wang, Y.L.[Ying-Lin], Zhao, J.H.[Jian-Hui], Guo, Z.W.[Zheng-Wei], Yang, H.J.[Hui-Jin], Li, N.[Ning],
Soil Moisture Inversion Based on Data Augmentation Method Using Multi-Source Remote Sensing Data,
RS(15), No. 7, 2023, pp. 1899.
DOI Link 2304
BibRef

Wang, R.[Ran], Zhao, J.H.[Jian-Hui], Yang, H.J.[Hui-Jin], Li, N.[Ning],
Inversion of Soil Moisture on Farmland Areas Based on SSA-CNN Using Multi-Source Remote Sensing Data,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Salunke, R.[Rakesh], Nobahar, M.[Masoud], Alzeghoul, O.E.[Omer Emad], Khan, S.[Sadik], Cour, I.L.[Ian La], Amini, F.[Farshad],
Near-Surface Soil Moisture Characterization in Mississippi's Highway Slopes Using Machine Learning Methods and UAV-Captured Infrared and Optical Images,
RS(15), No. 7, 2023, pp. 1888.
DOI Link 2304
BibRef

Nijaguna, G.S., Manjunath, D.R., Abouhawwash, M.[Mohamed], Askar, S.S., Basha, D.K.[D. Khalandar], Sengupta, J.[Jewel],
Deep Learning-Based Improved WCM Technique for Soil Moisture Retrieval with Satellite Images,
RS(15), No. 8, 2023, pp. 2005.
DOI Link 2305
BibRef

Guo, X.M.[Xiao-Meng], Fang, X.[Xiuqin], Zhu, Q.[Qiuan], Jiang, S.[Shanhu], Tian, J.[Jia], Tian, Q.J.[Qing-Jiu], Jin, J.X.[Jia-Xin],
Estimation of Root-Zone Soil Moisture in Semi-Arid Areas Based on Remotely Sensed Data,
RS(15), No. 8, 2023, pp. 2003.
DOI Link 2305
BibRef

Bandak, S.[Soraya], Naeini, S.A.R.M.[Seyed Ali Reza Movahedi], Komaki, C.B.[Chooghi Bairam], Verrelst, J.[Jochem], Kakooei, M.[Mohammad], Mahmoodi, M.A.[Mohammad Ali],
Satellite-Based Estimation of Soil Moisture Content in Croplands: A Case Study in Golestan Province, North of Iran,
RS(15), No. 8, 2023, pp. 2155.
DOI Link 2305
BibRef

Babaeian, E.[Ebrahim], Tuller, M.[Markus],
The Feasibility of Remotely Sensed Near-Infrared Reflectance for Soil Moisture Estimation for Agricultural Water Management,
RS(15), No. 11, 2023, pp. 2736.
DOI Link 2306
BibRef

Yang, Z.J.[Zhang-Jian], He, Q.[Qisheng], Miao, S.Q.[Shu-Qi], Wei, F.[Feng], Yu, M.X.[Ming-Xiao],
Surface Soil Moisture Retrieval of China Using Multi-Source Data and Ensemble Learning,
RS(15), No. 11, 2023, pp. 2786.
DOI Link 2306
BibRef

Salvatore, M.R.[Mark R.], Barrett, J.E.[John E.], Fackrell, L.E.[Laura E.], Sokol, E.R.[Eric R.], Levy, J.S.[Joseph S.], Kuentz, L.C.[Lily C.], Gooseff, M.N.[Michael N.], Adams, B.J.[Byron J.], Power, S.N.[Sarah N.], Knightly, J.P.[J. Paul], Matul, H.M.[Haley M.], Szutu, B.[Brian], Doran, P.T.[Peter T.],
The Distribution of Surface Soil Moisture over Space and Time in Eastern Taylor Valley, Antarctica,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
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

Xu, L.[Lei], Yu, H.C.[Hong-Chu], Chen, Z.[Zeqiang], Du, W.Y.[Wen-Ying], Chen, N.C.[Neng-Cheng], Huang, M.[Min],
Hybrid Deep Learning and S2S Model for Improved Sub-Seasonal Surface and Root-Zone Soil Moisture Forecasting,
RS(15), No. 13, 2023, pp. 3410.
DOI Link 2307
BibRef

Jia, R.[Renhao], Liu, J.[Jianli], Zhang, J.[Jiabao], Niu, Y.J.[Yu-Jie], Jiang, Y.F.[Yi-Fei], Xuan, K.[Kefan], Wang, C.[Can], Ji, J.C.[Jing-Chun], Ma, B.[Bin], Li, X.P.[Xiao-Peng],
An Improved UAV-Based ATI Method Incorporating Solar Radiation for Farm-Scale Bare Soil Moisture Measurement,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Song, L.S.[Li-Sheng], Xu, Y.[Yanhao], Liddell, M.[Michael], Cui, Y.[Yaokui], Liu, S.M.[Shao-Min], Xu, P.P.[Pei-Pei],
Application of a two source energy balance model coupled with satellite based soil moisture and thermal infrared data,
PandRS(204), 2023, pp. 15-26.
Elsevier DOI 2310
Evapotranspiration, TSEB-SM, Soil moisture, Spatio-temporally continuous BibRef

Preetham, A.[Anusha], Battu, V.V.[Vishnu Vardhan],
Soil Moisture Retrieval Using Sail Squirrel Search Optimization-based Deep Convolutional Neural Network with Sentinel-1 Images,
IJIG(23), No. 5 2023, pp. 2350048.
DOI Link 2310
BibRef

Li, X.Q.[Xu-Qing], Wang, X.D.[Xiao-Dan], Wu, J.J.[Jian-Jun], Luo, W.[Wei], Tian, L.[Lingwen], Wang, Y.C.[Yan-Cang], Liu, Y.Y.[Yu-Yan], Zhang, L.[Liang], Zhao, C.Y.[Chen-Yu], Zhang, W.L.[Wen-Long],
Soil Moisture Monitoring and Evaluation in Agricultural Fields Based on NDVI Long Time Series and CEEMDAN,
RS(15), No. 20, 2023, pp. 5008.
DOI Link 2310
BibRef

Cai, Y.L.[Yu-Lin], Fan, P.[Puran], Lang, S.[Sen], Li, M.Y.[Meng-Yao], Muhammad, Y.[Yasir], Liu, A.[Aixia],
Downscaling of SMAP Soil Moisture Data by Using a Deep Belief Network,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Celik, M.F.[Mehmet Furkan], Isik, M.S.[Mustafa Serkan], Yuzugullu, O.[Onur], Fajraoui, N.[Noura], Erten, E.[Esra],
Soil Moisture Prediction from Remote Sensing Images Coupled with Climate, Soil Texture and Topography via Deep Learning,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Lei, X., Wang, Y., Guo, T.,
Downscaling of SMAP Soil Moisture Product By Data Fusion With VIIRS LST/EVI Product,
SmartCityApp21(355-360).
DOI Link 2201
BibRef

Entezari, M., Esmaeily, A., Niazmardi, S.,
Estimation of Soil Moisture and Earth's Surface Temperature Using Landsat-8 Satellite Data,
SMPR19(327-330).
DOI Link 1912
BibRef

Sandric, I., Diamandi, A., Oana, N., Saizu, D., Vasile, C., Lucaschi, B.,
Validation And Upscaling Of Soil Moisture Satellite Products In Romania,
ISPRS16(B2: 313-317).
DOI Link 1610
BibRef

Kong, J.L., Xian, T., Yang, J., Chen, L., Yang, X.T.,
Monitoring Soil Moisture In A Coal Mining Area With Multi-phase Landsat Images,
ISPRS16(B7: 537-542).
DOI Link 1610
BibRef

Berwal, P., Murthy, C.S., Raju, P.V., Sai, M.V.R.S.[M. V. R. Sesha],
Geospatial Analysis Of Near-surface Soil Moisture Time Series Data Over Indian Region,
ISPRS16(B7: 631-637).
DOI Link 1610
BibRef

Yu, F., Li, H.T., Jia, Y., Han, Y.S., Gu, H.Y.,
The Multi-Level and Multi-Scale Factor Analysis for Soil Moisture Information Extraction by Multi-Source Remote Sensing Data,
IWIDF13(167-171).
DOI Link 1311
BibRef

Mobasheri, M.R., Bidkhan, N.G.,
Development of New Hyperspectral Angle Index for Estimation of Soil Moisture Using in Situ Spectral Measurments,
SMPR13(481-486).
DOI Link 1311
BibRef

Mishra, P., Singh, D.,
Transmission Line Theory Based Two Layer Model for Determining Soil Moisture,
Hannover13(253-256).
DOI Link 1308
BibRef

Dor, E.B.,
Soil Spectral Imaging: Moving From Proximal Sensing To Spatial Quantitative Domain,
AnnalsPRS(I-7), No. 2012, pp. 67-70.
DOI Link 1209
BibRef

Brinkhoff, T., Jansen, S.,
Sensor Web Services For Early Flood Warnings Based On Soil Moisture Profiles,
ISPRS12(XXXIX-B4:461-466).
DOI Link 1209
BibRef

Sohrabinia, M., Rack, W., Zawar-reza, P.,
Geostatistical Analysis of Surface Temperature and in-situ Soil Moisture Using Lst Time-series From Modis,
ISPRS12(XXXIX-B7:17-21).
DOI Link 1209
BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Soil Moisture, GNSS-R .

Last update:Nov 30, 2023 at 15:51:27