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: 122 | Category: Soil Moisture
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. 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. 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. 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. 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. 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. 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. 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. 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. Greifeneder, F., Notarnicola, C., Hahn, S., Vreugdenhil, M., Reimer, C., Santi, E., et al. (2018). The Added Value of the VH/VV Polarization-Ratio for Global Soil Moisture Estimations From Scatterometer Data
, IEEE J. Sel. Top. Appel., 11 (10), 3668-3679, doi: 10.1109/jstars.2018.2865185. 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. Carreno-Luengo, H., Luzi, G., and Crosetto, M. (2018). Sensitivity of CyGNSS Bistatic Reflectivity and SMAP Microwave Radiometry Brightness Temperature to Geophysical Parameters Over Land Surfaces
, IEEE J. Sel. Top. App., 12 (1), 107-122, doi: 10.1109/jstars.2018.2856588. 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. 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. Ye, N., Walker, J.P., Rudiger, C., Ryu, D., and Gurney, R.J. (2018). Surface Rock Effects on Soil Moisture Retrieval from L-Band Passive Microwave Observations
, Remote Sens. Environ., 215, 33-43, doi: 10.1016/j.rse.2018.05.025. 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. 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. Chew, C.C. and Small, E.E. (2018). Soil Moisture Sensing Using Spaceborne GNSS Reflections: Comparison of CYGNSS Reflectivity to SMAP Soil Moisture
, Geophys. Res. Lett., 45 (9), 4049-4057, doi: 101029/2018gl077905. 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. 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. 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. 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. 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. Kim, H., Parinussa, R., Konings, A.G., Wagner, W., Cosh, M.H., Lakshmi, V., Zohaib, M., and Choi, M., (2018). Global-Scale Assessment and Combination of SMAP with ASCAT (Active) and AMSR2 (Passive) Soil Moisture Products
, Remote Sens. Environ., 204, 260-275, doi: 10.1016/j.rse.2017.10.026. Chan, S.K., Bindlish, R., O'Neill, P., Jackson, T., Njoku, Dunbar, S., Chaubell, J., Piepmeier, J., Yueh, S., Entekhabi, D., Colliander, A., Chen, F., Cosh, M.H., Caldwell, T., Walker, J., Berg, A., McNairn, H., Thibeault, M., Martinez-Fernandez, J., Uldall, F., Seyfried, M., Bosch, D., Starks, P., Collins, C.H., Preuger, J., van der Velde, R., Asanuma, J., Palecki, M., Small, E.E., Zreda, M., Calvet, J., Crow, W.T., and Kerr, Y. (2018). Development and Assessment of the SMAP Enhanced Passive Soil Moisture Product
, Remote Sens. Environ., 204, 931-941, doi: 10.1016/j.rse.2017.08.025. Kolassa, J., Reichle, R.H., Liu, Q., Cosh, M., Bosch, D.D., Caldwell, T.G., Colliander, A., Collins, C.H., Jackson, T.J., Livingston, S.J., Moghaddam, M., and Starks, P.J. (2018). Data Assimilation to Extract Soil Moisture Information from SMAP Observations
, Remote Sens., 9 (11), 1179, doi: 10.3390/rs9111179. Zhang, L., He, C., and Zhang, M. (2018). Multi-Scale Evaluation of the SMAP Product Using Sparse In-Situ Network Over a High Mountainous Watershed, Northwest China
, Remote Sens., 9 (11), 1111, doi: 10.3390/rs9111111. Kolassa, J., Reichle, R.H., Liu, Q., Alemohammad, S.H., Gentine, P., Aida, K., Asanuma, J., Bircher, S., Caldwell, T., Colliander, A., Cosh, M., Collins, C.H., Jackson, T.J., Martinez-Fernandez, McNairn, H., Pacheco, A., Thibeault, M., and Walker, J.P. (2018). Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique
, Remote Sens. Environ., 204, 43-59, doi: 10.1016/j.rse.2017.10.045. Cui, C.Y., Xu, J., Zeng, J.Y., Chen, K.S., Bai, X.J., Lu, H., Chen, Q., and Zhao, T.J. (2017). Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI Over Two Dense Network Regions at Different Spatial Scales
, Remote Sens., 10 (1), doi: 10.3390/rs10010033. Lyu, H., McColl, K.A., Li, X., Derksen, C., Berg, A., Black, T.A., Euskirchen, E., Loranty, M., Pulliainen, J., Rautiainen, K., Rowlandson, T., Roy, A., Royer, A., Langlois, A, Stephens, J., Lu, H., and Entekhabi, D. (2017). Validation of the SMAP Freeze/Thaw Product Using Categorical Triple Collocation
, Remote Sens. Environ., 205, 329-337, doi: 10.1016/j.rse.2017.12.007. 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. Wang, Q., van der Velde, R., and Su, Z. (2017). Use of a Discrete Electromagnetic Model for Simulating Aquarius L-Band Active/Passive Observations and Soil Moisture Retrieval
, Remote Sens. Environ., 205, 434-452, doi: 10.1016/j.rse.2017.10.044. 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. Emami, H., Mojaradi, B., and Safari, A. (2017). The Effect of Soil Salinity on the Use of the Universal Triangle Method to Estimate Saline Soil Moisture from Landsat Data: Application to the SMAPEx-2 and SMAPEx-3 Campaigns
, Int. J. Remote Sens., 38 (23), 6623-6652, doi: 10.1080/01431161.2017.1363431. 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. 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. 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
, IEEE J-STARS, 10 (10), 4493-4503, doi: 101109/jstars.2017.2716638. 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. 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. Peng, J., Misra, S., Piepmeier, J.R., Dinnat, E.P., Hudson, D., Le Vine, D.M., De Amnici, G., Mohammed, P.N., Bindlish, R., Yueh, S.H., Meissner, T., and Jackson, J. (2017). Soil Moisture Active/Passive L-Band Microwave Radiometer Postlaunch Calibration
, IEEE Geosci. Remote, 55 (9), 5339-5354, doi:10.1109/TGRS.2017.2705342. Al Bitar, A., Mialon, A., Kerr, Y,H., Cabot, F., Richaume, P., Jacquette, E., Quesney, A., Mahmoodi, A., Tarot, S., Parrens, M., Al-Yaari, A., Pellarin, T., Rodríguez-Fernández, N., and Wigneron, J.P. (2017). The Global SMOS Level 3 Daily Soil Moisture and Brightness Temperature Maps
, Earth Syst. Sci. Data, 9 (1), 293-315, doi: 105194/essd-9-293-2017. Srivastava, P.K. (2017). Satellite Soil Moisture: Review of Theory and Applications in Water Resources
, Water Resour. Manag., 31(10), 3161-3176, doi: 10.1007/s11269-017-1722-6. 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. 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. 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. Colliander, A., Cosh, M.H., Misra, S., Jackson, T.J., Crow, W.T., Chan, S., Bindlish, R., Chae, C., Collins, C.H., and Yueh, S.H. (2017). Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)
, Remote Sens. Environ., 196, 101-112, doi: 10.1016/j.rse.2017.04.022. 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. Derksen, C., Xu, X., Dunbar, R.S., Colliander, A., Kim, Y., Kimball, J.S., Black, T.A., Euskirchen, E., Langlois, A., Loranty, M.M., Marsh, P., Rautiainen, K., Roy, A., Royer, A., and Stephens, J. (2017). Retrieving Landscape Freeze/Thaw State from Soil Moisture Active Passive (SMAP) Radar and Radiometer Measurements
, Remote Sens. Environ., 194, 48-62, doi: 10.1016/j.rse.2017.03.007. 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. Naderpour, R., Schwank, M., Matzler, C., Lemmetyinen, J., and Steffen, K. (2017). Snow Density and Ground Permittivity Retrieved From L-Band Radiometry: A Retrieval Sensitivity Analysis
, IEEE J-STARS, 10 (7), 3148-3161, doi: 101109/jstars.2017.2669336. Cai, X.T., Pan, M., Chaney, N.W., Colliander, A., Misra, S., Cosh, M.H., Crow, W.T., Jackson, T.J., and Wood, E.F. (2017). Validation of SMAP Soil Moisture for the SMAPVEX15 Field Campaign Using a Hyper-Resolution Model
, Water Resour. Res., 53 (4), 3013-3028, doi: 10.1002/2016wr019967. 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. 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. He, L.M., Chen, J.M., and Chen, K.S. (2017). Simulation and SMAP Observation of Sun-Glint Over the Land Surface at the L-Band
, IEEE T. Geosci. Remote, 55 (5), 2589-2604, doi: 101109/tgrs.2017.2648502. Montzka, C., Bogena, H.R., Zreda, M., Monerris, A., Morrison, R., Muddu, S., and Vereecken, H. (2017). Validation of Spaceborne and Modelled Surface Soil Moisture Products with Cosmic-Ray Neutron Probes
, Remote Sens., 9 (2), doi: 10.3390/rs9020103. 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. 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. 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. Colliander, A., Njoku, E.G., Jackson, T.J., Chazanoff, S., McNairn, H., Powers, J., and Cosh, M.H. (2016). Retrieving Soil Moisture for Non-forested Areas Using PALS Radiometer Measurements in SMAPVEX12 Field Campaign
, Remote Sens. Environ., 184, 86-100, doi: 10.1016/j.rse.2016.06.001. 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. 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. 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. 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. 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. 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. 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. Pellarin, T., Mialon, A., Biron, R., Coulaud, C., Gibon, F., Kerr, Y., Lafaysse, M., Mercier, B., Morin, S., Redor, I., Schwank, M., and Völksch, I. (2016). Three Years of L-Band Brightness Temperature Measurements in a Mountainous Area: Topography, Vegetation and Snowmelt Issues
, Remote Sens. Environ., 180, 85-98, doi: 101016/j.rse.2016.02.047. 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. Lemmetyinen, J., Schwank, M., Rautiainen, K., Kontu, A., Parkkinen, T., Mätzler, C., Wiesmann, A., Wegmüller, R., Derksen, C., Toose, P., Roy, A., and Pulliainen, J. (2016). Snow Density and Ground Permittivity Retrieved from L-Band Radiometry: Application to Experimental Data
, Remote Sens. of Environ., 180, 377-391, doi: 101016/j.rse.2016.02.002. Gonzalez-Zamora, A., Sanchez, N., and Martinez-Fernandez, J. (2016). Validation of Aquarius Soil Moisture Products Over the Northwest of Spain: A Comparison with SMOS
, IEEE J. Sel. Top. Appl., 9 (6), 2763 - 2769, doi: 10.1109/JSTARS.2016.2517401. 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. McColl, K.A., Roy, A., Derksen, C., Konings, A.G., Alemohammed, S.H., and Entekhabi, D. (2016). Triple Collocation for Binary and Categorical Variables: Application to Validating Landscape Freeze/Thaw Retrievals
, Remote Sens. Environ., 176, 31-42, doi: 10.1016/j.rse.2016.01.010. 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. 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. Olesk, A., Voormansik, K., Vain, A., Noorma, M., and Praks, J. (2015). Seasonal Differences in Forest Height Estimation from Interferometric TanDEM-X Coherence Data
, IEEE J. Sel. Top. Appl., 8 (12), 5565-5572, doi: 10.1109/JSTARS.2015.2501648. Konings, A.G., Piles, M., Rotzer, K., McColl, K.A., Chan, S.K., and Entekhabi, D. (2015). Vegetation Optical Depth and Scattering Albedo Retrieval Using Time Series of Dual-polarized L-band Radiometer Observations
, Remote Sens. Environ., 172, 178-189, doi: 10.1016/j.rse.2015.11.009. 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. de Jeu, R. and Dorigo, W. (2015). On the Importance of Satellite Observed Soil Moisture
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