Publications: Soil Moisture
The publications on this page are focused on soil moisture, which uses the same technology (L-band) used to detect sea surface salinity.
Publications: 116 | Category: Soil Moisture
Burgin, M.S., Colliander, A., Njoku, E.G., Chan, S.K., Cabot, F., Kerr, Y.H., Bindlish, R., Jackson, T.J., Entekhabi, D., and Yueh, S.H. (2017). A Comparative Study of the SMAP Passive Soil Moisture Product With Existing Satellite-Based Soil Moisture Products
, IEEE T. Geosci. Remote, 55 (5), 2959-2971, doi: 10.1109/TGRS.2017.2656859. Utku, C., and Le Vine, D.M. (2010). A Model for Prediction of the Impact of Topography on Microwave Emission
, IEEE T. Geosci. Remote, 49 (1), 395-405, doi: 101109/tgrs.2010.2053936. Guo, P., Shi, J.C., Liu, Q., and Du, J.Y. (2013). A New Algorithm for Soil Moisture Retrieval With L-Band Radiometer
, IEEE J-STARS, 6 (3), 1147-1155, doi: 101109/jstars.2013.2244852. Gaur, N. and Mohanty, B.P. (2018). A Nomograph to Incorporate Geophysical Heterogeneity in Soil Moisture Downscaling
, Water Resour. Res. 55 (1), 34-54, doi: 10.1029/2018wr023513. Lv, S.N., Zeng, Y.J., Wen, J., and Su, Z.B. (2016). A Reappraisal of Global Soil Effective Temperature Schemes
, Remote Sens. Environ., 183, 144-153, doi: 10.1016/j.rse.2016.05.012. Mironov, V.L., Kerr, Y.H., Kosolapova, L.G., Savin, I.V., Musaleviskiy, K.V. (2015). A Temperature-Dependent Dielectric Model for Thawed and Frozen Organic Soil at 1.4 GHz
, IEEE J-STARS, 8 (9), 4470-4477, doi:10.1109/JSTARS.2015.2442295. Holmes, T.R.H., Jackson, T.J., Reichle, R.H., abd Basara, J.B. (2012). An Assessment of Surface Soil Temperature Products from Numerical Weather Prediction Models Using Ground-based Measurements
, Water Resour. Res, 48, doi: 10.1029/2011wr010538. Blyverket, J., Hamer, P.D., Bertino, L., Albergel, C., Fairbairn, D., and Lahoz, W.A. (2019). An Evaluation of the EnKF vs. EnOI and the Assimilation of SMAP, SMOS and ESA CCI Soil Moisture Data over the Contiguous US
, Remote Sens., 11 (5), 478, doi: https://doi.org/10.3390/rs11050478. Senanayake, I.P., Yeo, I.Y., Tangdamrongsub, N., Willgoose, G.R., Hancock, G.R., Welis, T., et al. (2019). An In-situ Data Based Model to Downscale Radiometric Satellite Soil Moisture Products in the Upper Hunter Region of NSW, Australia
, J. Hydro., 572, 820-838, doi: 10.1016/j.jhydrol.2019.03.014. Bruscantini, C.A., Crow, W.T., Grings, F., Perna, P., Maas, M., and Karszenbaum, H. (2014). An Observing System Simulation Experiment for the Aquarius/SAC-D Soil Moisture Product
, IEEE T. Geosci. Remote, 52 (10), 6086-6094, doi: 10.1109/TGRS.2013.2294915. Burgin, M.S. and van Zyl, M.S. (2016). Analysis of Polarimetric Radar Data and Soil Moisture from Aquarius: Towards a Regression-Based Soil Moisture Estimation Algorithm
, IEEE J. Sel. Top. Appl., 9 (8), 3497-3504, doi: 10.1109/JSTARS.2016.2526899. Wang, Q., van der Velde, R., Su, Z., and Wen, J. (2015). Aquarius L-band Scatterometer and Radiometer Observations Over a Tibetan Plateau Site
, Int. J. Appl. Earth Obs., 45, 165-177, doi: 10.1016/j.jag.2015.06.010. Al-Yaari, A., Wigneron, J.P., Dorigo, W., Colliander, A., Pellarin, T., Hahn, S., et al. (2019). Assessment and Inter-comparison of Recently Developed/Reprocessed Microwave Satellite Soil Moisture Products Using ISMN Ground-based Measurements
, Remote Sens. Environ., 224, 289-303, doi: 10.1016/j.rse.2019.02.008. Pablos, M., Gonzalez-Zamora, A., Sanchez, N., and Martinez-Fernandez, J. (2018). Assessment of Root Zone Soil Moisture Estimations from SMAP, SMOS and MODIS Observations
, Remote Sens., 10 (7), doi: 10.3390/rs10070981. Liu, P.-W., Bongiovanni, T., Monsivais-Huertero, A., Judge, J., Steele-Dunne, S., Bindlish, R., and Jackson, T.J. (2016). Assimilation of Active and Passive Microwave Observations for Improved Estimates of Soil Moisture and Crop Growth
, IEEE J. Sel. Top. Appl., 9 (4), 1357-1369, doi: 10.1109/JSTARS.2015.2506504. Girotto, M., De Lannoy, G.J.M., Reichle, R.H., and Rodell, M. (2016). Assimilation of Gridded Terrestrial Water Storage Observations from GRACE into a Land Surface Model
, Water Resour. Res., 52 (5), 4164-4183, doi: 10.1002/2015wr018417. De Lannoy, G.J.M. and Reichle, R.H. (2016). Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model
, Hydrol. Earth Syst. Sc., 20 (12), 4895-4911, doi: 105194/hess-20-4895-2016. Xu, X.Y., Tolson, B.A., Li, J., and Davison, B. (2017). Assimilation of Synthetic Remotely Sensed Soil Moisture in Environment Canada’s MESH Model
, IEEE J-STARS, 10 (4), 1317-1327, doi: 101109/jstars.2016.2626256. Loew, A. and Schwank, M. (2010). Calibration of a Soil Moisture Model Over Grassland Using L-Band Microwave Radiometry
, Int. J. Remote Sens., 31 (19), 5163-5177, doi: 101080/01431160903260981. Magagi, R., Berg, A.A., Goita, K., Belair, S., Jackson, T.J., Toth, B., Walker, A., McNairn, H., O'Neill, P.E., Moghaddam, M., Gherboudj, I., Colliander, A., Cosh, M.H., Burgin, M., Fisher, J.B., Kim, S-B., Mladenova, I., Djamai, N., Rousseau, L-P.B., Belanger, J., Shang, J., and Merzouki, A. (2012). Canadian Experiment for Soil Moisture in 2010 (CanEx-SM10): Overview and Preliminary Results
, IEEE T. Geosci. Remote, 51 (1), 347-363, doi: 101109/tgrs.2012.2198920. Colliander, A., Jackson, T., McNairn, H., Chazanoff, S., Dinardo, S., Latham, B., O'Dwyer, I., Chun, W., Yueh, S., and Njoku, E. (2014). Comparison of Airborne Passive and Active L-Band System (PALS) Brightness Temperature Measurements to SMOS Observations During the SMAP Validation Experiment 2012 (SMAPVEX12)
, IEEE Geosci. Remote S., 12(4), 801-805, doi: 101109/lgrs.2014.2362889. Monsivais-Huertero, A. and Judge, J. (2010). Comparison of Backscattering Models at L-Band for Growing Corn
, IEEE Geosci. Remote S., 8 (1), 24-28, doi: 101109/lgrs.2010.2050459. Ford, T.W. and Quiring, S.M. (2019). Comparison of Contemporary In Situ, Model, and Satellite Remote Sensing Soil Moisture With a Focus on Drought Monitoring
, Water Resour. Res., 55 (2), 1565-1582, doi: 10.1029/2018wr024039. Miernecki, M., Wigneron, J-P., Lopez-Baeza, E., Kerr, Y., De Jeu, R., De Lannoy, G.J.M., Jackson, T.J., O'Neill, P.E., Schwank, M., Moran, R.F., Bircher, S., Lawrence, H., Mialon, A., Al Bitar, A., and Richaume, P. (2014). Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-Based Radiometer Data Over a Vineyard Field
, Remote Sens. Environ., 154, 89-101, doi: 101016/j.rse.2014.08.002. De Lannoy, G.J.M., Reichle, R.H., Peng, J.Z., Kerr, Y., Castro, R., Kim, E.J., and Liu, Q. (2015). Converting Between SMOS and SMAP Level-1 Brightness Temperature Observations Over Nonfrozen Land
, Geosci. Remote S., 12 (9), 1908-1912, doi: 101109/lgrs.2015.2437612. Kim, S.B., Ouellette, J.D., van Zyl, J.J., and Johnson, J.T. (2016). Detection of Inland Open Water Surfaces Using Dual Polarization L-Band Radar for the Soil Moisture Active Passive Mission
, IEEE T. Geosci. Remote, 54 (6), 3388-3399, doi: 10.1109/TGRS.2016.2517010. Knipper, K.R., Hogue, T.S., Franz, K.J., and Scott, R.L. (2017). Downscaling SMAP and SMOS Soil Moisture with Moderate-Resolution Imaging Spectroradiometer Visible and Infrared Products Over Southern Arizona
, J. Appl. Remote Sens., 11, doi: 101117/1.jrs.11.026021. Bruscantini, C.A., Perna, P., Ferrazzoli, P., Grings, F., Karszenbaum, H., and Crow, W.T. (2013). Effect of Forward/Inverse Model Asymmetries Over Retrieved Soil Moisture Assessed with an OSSE for the Aquarius/SAC-D Mission
, IEEE J. Sel. Top. Appl., 7 (3), 943-949, doi: 10.1109/JSTARS.2013.2265076. Pierdicca, N., Fascetti, F., Pulvirenti, L., and Crapolicchio, R. (2017). Error Characterization of Soil Moisture Satellite Products: Retrieving Error Cross-Correlation Through Extended Quadruple Collocation
, IEEE J-STARS, 10 (10), 4522-4530, doi: 101109/jstars.2017.2714025. Martens, B., Lievens, H., Colliander, A., Jackson, T.J., and Verhoest, N.E.C. (2015). Estimating Effective Roughness Parameters of the L-MEB Model for Soil Moisture Retrieval Using Passive Microwave Observations From SMAPVEX12
, IEEE T. Geosci. Remote, 53 (7), 4091-4103, doi: 101109/tgrs.2015.2390259. Champagne, C., Zhang, Y.S., Cherneski, P., and Hadwen, T. (2018). Estimating Regional Scale Hydroclimatic Risk Conditions from the Soil Moisture Active-Passive (SMAP) Satellite
, Geosci. J., 8 (4), 127, doi: 103390/geosciences8040127. Lv, S.N., Zeng, Y.J., Wen, J., Zhao, H., and Su, Z.B. (2018). Estimation of Penetration Depth from Soil Effective Temperature in Microwave Radiometry
, Remote Sens., 10 (4), doi: 10.3390/rs10040519. Liu, C. and Shi, J. (2016). Estimation of Vegetation Parameters of Water Cloud Model for Global Soil Moisture Retrieval Using Time-Series L-Band Aquarius Observations
, IEEE J. Sel. Top. Appl., 9 (12), 5621-5633, doi: 10.1109/JSTARS.2016.2596541. Al-Yaari, A., Wigneron, J-P., Kerr, Y., Rodríguez-Fernández, N., O'Neill, P.E., Jackson, T.J., De Lannoy, G.J.M., Al Bitar, A., Mialon, A., Richaume, P., Walker, J.P., Mahmoodi, A., and Yueh, S. (2017). Evaluating Soil Moisture Retrievals from ESA’s SMOS and NASA’s SMAP Brightness Temperature Datasets
, Remote Sens. Environ., 193, 257-273, doi: 10.1016/j.rse.2017.03.010. Cui, H.Z., Jiang, L.M., Du, J.Y., Zhao, S.J., Wang, G.X., Lu, Z., and Wang, J. (2017). Evaluation and Analysis of AMSR-2, SMOS, and SMAP Soil Moisture Products in the Genhe Area of China
, J. Geophys. Res.-Atmos., 122 (16), 8650-8666, doi: 101002/2017jd026800. Jin, M.J., Zheng, X.M., Jiang, T., Li, X.F., Li, X.J., and Zhao, K. (2017). Evaluation and Improvement of SMOS and SMAP Soil Moisture Products for Soils with High Organic Matter Over a Forested Area in Northeast China
, Remote Sens., 9 (4), doi: 10.3390/rs9040387. Ray, R.L., Fares, A., He, Y.P., and Temimi, M. (2017). Evaluation and Inter-Comparison of Satellite Soil Moisture Products Using In Situ Observations Over Texas, US
, Water-SUI, 9 (6), 372, doi: 10.3390/w9060372. Stillman, S., Zeng, X., and Bosilovich, M.G. (2015). Evaluation of 22 Precipitation and 23 Soil Moisture Products Over a Semiarid Area in Southeastern Arizona
, J. Hydrometeorol., 17 (1), 211-230, doi: 10.1175/JHM-D-15-0007.1. Adams, J.R., McNairn, H., Berg, A.A., and Champagne, C. (2014). Evaluation of Near-Surface Soil Moisture Data from an AAFC Monitoring Network in Manitoba, Canada: Implications for L-Band Satellite Validation
, J. Hydrol., 521, 582-592, doi: 101016/j.jhydrol.2014.10.024. Chen, Y.Y., Yang, K., Qin, J., Cui, Q., Lu, H., La, Z., Han, M.L., and Tang, W.J. (2017). Evaluation of SMAP, SMOS, and AMSR2 Soil Moisture Retrievals Against Observations from Two Networks on the Tibetan Plateau
, J. Geophys. Res.-Atmos., 122 (11), 5780-5792, doi: 101002/2016jd026388. El Hajj, M., Baghdadi, N., Zribi, M., Rodreguez-Fernández, N., Wigneron, J.P., Al-Yaari, A., Al Bitar, A., Albergel, C., and Calvet, J.C. (2018). Evaluation of SMOS, SMAP, ASCAT and Sentinel-1 Soil Moisture Products at Sites in Southwestern France
, Remote Sens., 10 (4), doi: 10.3390/rs10040569. El Hajj, M., Baghdadi, N., Zribi, M., Rodríguez-Fernández, N., Wigneron, J.P., Al-Yaari, A., Al Bitar, A., Albergel, C., and Calvet, J.-C. (2018). Evaluation of SMOS, SMAP, ASCAT and Sentinel-1 Soil Moisture Products at Sites in Southwestern France
, Remote Sens., 10, 569, doi: 10.3390/rs10040569. Roy, A., Royer, A., Derksen, C., Brucker, L., Langlois, A., Mialon, A., and Kerr, Y.H. (2015). Evaluation of Spaceborne L-band Radiometer Measurements for Terrestrial Freeze/Thaw Retrievals in Canada
, IEEE J. Sel. Top. Appl., 8 (9), 4442 - 4459, doi: 10.1109/JSTARS.2015.2476358. Tarik, S.B. (2014). Evaluation of the NASA Microwave Radiative Transfer Model for Soil Moisture Estimation Using Aquarius Brightness Temperature Observations Over the Continental United States
, Thesis (MS). Kim, S.B., Jackson, T.J., Yueh, S.H., Xu, X.L., and Hensley, S. (2015). Feasibility of Inter-Comparing Airborne and Spaceborne Observations of Radar Backscattering Coefficients
, IEEE J-STARS, 8 (7), 3507-3519, doi: 101109/jstars.2015.2424715. Li, D., Zhao, T., Shi, J., Bindlish, R., Jackson, T.J., Peng, B., An, M., and Han, B. (2015). First Evaluation of Aquarius Soil Moisture Products Using In Situ Observations and GLDAS Model Simulations
, IEEE J. Sel. Top. Appl., 8 (12), 5511-5525, doi: 10.1109/JSTARS.2015.2452955. Xu, X., Derksen, C., Yueh, S.H., Dunbar, R.S., and Colliander, A. (2016). Freeze/Thaw Detection and Validation Using Aquarius L-Band Backscattering Data
, IEEE J. Sel. Top. Appl., 9 (4), 1370-1381, doi: 10.1109/JSTARS.2016.2519347. Sawada, Y., Koike, T., Aida, K., Toride, K., and Walker, J.P. (2017). Fusing Microwave and Optical Satellite Observations to Simultaneously Retrieve Surface Soil Moisture, Vegetation Water Content, and Surface Soil Roughness
, IEEE T. Geosci. Remote, 55 (11), 6195-6206, doi: 101109/tgrs.2017.2722468. De Lannoy, G.J.M. and Reichle, R.H. (2016). Global Assimilation of Multiangle and Multipolarization SMOS Brightness Temperature Observations into the GEOS-5 Catchment Land Surface Model for Soil Moisture Estimation
, Journal of Hydrometeorology, 17 (2), 669-691, doi: 101175/jhm-d-15-0037.1. De Lannoy, G.J.M., Reichle, R.H., and Pauwels, V.R.N. (2013). Global Calibration of the GEOS-5 L-Band Microwave Radiative Transfer Model Over Nonfrozen Land Using SMOS Observations
, J. Hydrometeorol., 14 (3), 765-785, doi: 101175/jhm-d-12-092.1. Parrens, M., Wigneron, J.P., Richaume, P., Mialon, A., Al Bitar, A., Fernandez-Moran, R., Al-Yaari, A., and Kerr, Y.H. (2016). Global Scale Surface Roughness Effects at L-Band as Estimated from SMOS Observations
, Remote Sens. Environ., 181, 122-136, doi: 10.1016/j.rse.2016.04.006. Bindlish, R., Jackson, T., Cosh, M., Zhao, T., and O'Neill, P. (2015). Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment
, IEEE Geosci. Remote S., 12 (5), 923-927, doi: 10.1109/LGRS.2014.2364151. Chen, F., Crow, W.T., Bindlish, R., Colliander, A., Burgin, M.S., Asanuma, J., and Aida, K. (2018). Global-Scale Evaluation of SMAP, SMOS and ASCAT Soil Moisture Products Using Triple Collocation
, Remote Sens. Environ., 214, 1-13, doi: 10.1016/j.rse.2018.05.008. Brocca, L., Tarpanelli, A., Filippucci, P., Dorigo, W., Zaussinger, F., Gruber, A., and Fernandez-Prieto, D. (2018). How Much Water is Used for Irrigation? A New Approach Exploiting Coarse Resolution Satellite Soil Moisture Products
, Int. J. Appl, Earth Obs., 73, 752-766, doi: 10.1016/j.jag.2018.08.023. Nagarajan, K., Judge, J., Monsivais-Huertero, A., and Graham, W.D. (2012). Impact of Assimilating Passive Microwave Observations on Root-Zone Soil Moisture Under Dynamic Vegetation Conditions
, IEEE T. Geosci. Remote, 50 (11), 4279-4291, doi: 101109/tgrs.2012.2191154. Yin, J.F. and Zhan, X.W. (2018). Impact of Bias-Correction Methods on Effectiveness of Assimilating SMAP Soil Moisture Data into NCEP Global Forecast System Using the Ensemble Kalman Filter
, IEEE Geosci. Remote S., 15 (5), 659-663, doi: 101109/lgrs.2018.2806092. Lu, Y., Dong, J.Z., and Steele-Dunne, S.C. (2019). Impact of Soil Moisture Data Resolution on Soil Moisture and Surface Heat Flux Estimates through Data Assimilation: A Case Study in the Southern Great Plains
, J. Hydrometeorol., 20 (4), 715-730, doi: 10.1175/jhm-d-18-0234.1. Roy, S.K., Rowlandson, T.L., Berg, A.A., Champagne, C., and Adams, J.R. (2014). Impact of Sub-Pixel Heterogeneity on Modelled Brightness Temperature for an Agricultural Region
, Int. J. Appl. Earth Obs., 45, 212-220, doi:101016/j.jag.2015.10.003. Crosson, W.L., Limaye, A.S., and Laymon, C.A. (2010). Impacts of Spatial Scaling Errors on Soil Moisture Retrieval Accuracy at L-Band
, IEEE J-STARS, 3 (1), 67-80, doi: 101109/jstars.2010.2041636. Jung, H.C., Getirana, A., Arsenault, K.R., Kumar, S., and Maigary, I. (2019). Improving Surface Soil Moisture Estimates in West Africa Through GRACE Data Assimilation
, J. Hydrol., 575, 192-201, doi: 10.1016/j.jhydrol.2019.05.042. Seyyedi, H., Anagnostou, E.N., Kirstetter, P.E., Maggioni, V., Hong, Y., and Gourley, J.J. (2014). Incorporating Surface Soil Moisture Information in Error Modeling of TRMM Passive Microwave Rainfall
, IEEE T. Geosci. Remote, 52 (10), 6226-6240, doi: 101109/tgrs.2013.2295795. Lettenmaier, D.P., Alsdorf, D., Dozier, J., Huffman, G.J., Pan, M., and Wood, E.F. (2015). Inroads of Remote Sensing into Hydrologic Science During the WRR Era
, Water Resour. Res., 51 (9), 7309-7342, doi.org/10.1002/2015WR017616. Guerriero, L., Ferrazzoli, P., Vittucci, C., and Rahmoune, R. (2016). L-Band Passive and Active Signatures of Vegetated Soil: Simulations with a Unified Model
, IEEE J. Sel. Top. Appl., 9 (6), 2520-2531, doi: 10.1109/JSTARS.2016.2570424. Bruscantini, C.A., Konings, A.G., Narvekar, P.S., and McColl, K.A. (2015). L-band Radar Soil Moisture Retrieval Without Ancillary Information
, IEEE J. Sel. Top. Appl., 8 (12), 5526-5540, doi: 10.1109/JSTARS.2015.2496326. Dong, J.Z. and Crow, W.T. (2019). L-band Remote-sensing Increases Sampled Levels of Global Soil Moisture-air Temperature Coupling Strength
, Remote Sens. Environ., 220, 51-58, doi: 10.1016/j.rse.2018.10.024. Konings, A.G., Piles, M., Das, N., and Entekhabi, D. (2017). L-Band Vegetation Optical Depth and Effective Scattering Albedo Estimation from SMAP
, Remote Sens. Environ., 198, 460-470, doi: 10.1016/j.rse.2017.06.037. Bruscantini, C.A., Maas, M., Grings, F., and Karszenbaum, H. (2015). Land Intercalibration and Drift Monitoring of MWR Radiometer on Board SAC-D/Aquarius
, IEEE J. Sel. Top. Appl., 8 (12), 5462-5467, doi: 10.1109/JSTARS.2015.2444271. Sazib, N., Mladenova, I., and Bolten, J. (2018). Leveraging the Google Earth Engine for Drought Assessment Using Global Soil Moisture Data
, Remote Sens., 10 (8), doi: 10.3390/rs10081265. Soldo, Y., Le Vine, D.M., Bringer, A., de Matthaeis, P., Oliva, R., Johnson, J.T., and Piepmeier, J.R. (2018). Location of Radio-Frequency Interference Sources Using the SMAP L-Band Radiometer
, IEEE T. Geosci. Remote Sens., 56 (11), 6854-6866, doi: 10.1109/tgrs.2018.2844127. Colliander, A., Chan, S., Kim, S.B., Das, N., Yueh, S., Cosh, M., Bindlish, R., Jackson, T., and Njoku, E. (2012). Long Term Analysis of PALS Soil Moisture Campaign Measurements for Global Soil Moisture Algorithm Development
, Remote Sens. Environ., 121, 309-322, doi: 101016/j.rse.2012.02.002. Babaeian, E., Sadeghi, M., Franz, T.E., Jones, S., and Tuller, M. (2018). Mapping Soil Moisture with the OPtical TRApezoid Model (OPTRAM) Based on Long-Term MODIS Observations
, Remote Sens. Environ., 211, 425-440, doi: 10.1016/j.rse.2018.04.029. Wigneron, J.-P., Jackson, T.J., O'Neill, P., De Lannoy, G., de Rosnay, P., Walker, J.P., Ferrazzoli, P., Mironov, V., Bircher, S., Grant, J.P., Kurum, M., Schwank, M., Munoz-Sabater, J., Das, N., Royer, A., Al-Yaari, A., Al Bitar, A., Fernandez-Moran, R., Lawrence, H., Mialon, A., Parrens, M., Richaume, P., Delwart, S., and Kerr, Y. (2017). Modelling the Passive Microwave Signature from Land Surfaces: A Review of Recent Results and Application to the L-band SMOS & SMAP Soil Moisture Retrieval Algorithms
, Remote Sens. Environ., 192, 238-262, doi: 10.1016/j.rse.2017.01.024. Kim, S.B., Moghaddam, M., Tsang, L., Burgin, M., Xu, X., and Njoku, E.G. (2013). Models of L-band Radar Backscattering Coefficients Over Global Terrain for Soil Moisture Retrieval
, IEEE T. Geosci. Remote, 52 (2), 1381-1396, doi: 10.1109/TGRS.2013.2250980. Pablos, M., Martinez-Fernandez, J., Piles, M., Sanchez, N., Vall-Ilossera, M., and Camps, A. (2016). Multi-Temporal Evaluation of Soil Moisture and Land Surface Temperature Dynamics Using in Situ and Satellite Observations
, Remote Sens., 8 (7), doi: 10.3390/rs8070587. Park, C.H., Behrendt, A., LeDrew, E., and Wulfmeyer, V. (2017). New Approach for Calculating the Effective Dielectric Constant of the Moist Soil for Microwaves
, Remote Sens., 9 (7), doi: 10.3390/rs9070732. Colliander, A. and Xu, X. (2012). Normalized Residual Scattering Index Applied to Aquarius L-band Measurements
, IEEE Geosci. Remote S., 10 (4), 890-894, doi: 10.1109/LGRS.2012.2226559. Prince, M., Roy, A., Brucker, L., Royer, A., Kim, Y., and Zhao, T. (2018). Northern Hemisphere Surface Freeze/Thaw Product from Aquarius L-band Radiometers
, Earth Syst. Sci. Data, doi: 10.5194/essd-2018-25. de Jeu, R. and Dorigo, W. (2015). On the Importance of Satellite Observed Soil Moisture
, Int. J. Appl. Earth Obs., 45 (Part B), 107-109, doi: 10.1016/j.jag.2015.10.007. Kornelsen, K.C., Cosh, M.H., and Coulibaly, P. (2015). Potential of Bias Correction for Downscaling Passive Microwave and Soil Moisture Data
, J. Geophys. Res.-Atmos., 120 (13), 6460-6479, doi: 101002/2015jd023550. Luo, Y., Feng, X., Houser, P., Anantharaj, V., Fan, X., De Lannoy, G., Zhan, X., and Dabbiru, L. (2013). Potential Soil Moisture Products from the Aquarius Radiometer and Scatterometer Using an Observing System Simulation Experiment
, Geosci. Instrum. Method. Data Syst. Discuss., 2 (1), 113-120, doi: 10.5194/gi-2-113-2013. Luo, Y., Feng, X., Houser, P., Anantharaj, V., Fan, X., De Lannoy, G., Zhan, X., and Dabbiru, L. (2013). Potential Soil Moisture Products from the Aquarius Radiometer and Scatterometer Using an Observing System Simulation Experiment
, Geosci. Instrum. Method. Data Syst. Discuss., 2 (2), 457-476, doi: 10.5194/gid-2-457-2012. Koster, R.D., Brocca, L., Crow, W.T., Burgin, M.S., and De Lannoy, G.J.M. (2016). Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals
, Water Resour. Res., 52 (9), 7213-7225, doi: 10.1002/2016wr019024. Zhao, T.J., Shi, J.C., Bindlish, R., Jackson, T.J., Kerr, Y.H., Cosh, M.H., Cui, Q., Li, Y.Q., Xiong, C., and Che, T. (2014). Refinement of SMOS Multiangular Brightness Temperature Toward Soil Moisture Retrieval and its Analysis Over Reference Targets
, IEEE J-STARS, 8 (2), 589-603, doi: 101109/jstars.2014.2336664. Rötzer, K., Montzka, C., Entekhabi, D., Konings, A.G., McColl, K.A., Piles, M., and Vereecken, H. (2017). Relationship Between Vegetation Microwave Optical Depth and Cross-Polarized Backscatter from Multiyear Aquarius Observations
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, Remote Sens. Environ., 172, 178-189, doi: 10.1016/j.rse.2015.11.009. Note: Year and sorting are based on the date of online publication [YYYY-MM-DD (YYYY-01-01 or YYYY-MM-01 if month and/or day are unknown)] or, in the case of MS theses or PhD dissertations, available graduation or defense dates.