On Wednesday, February 22nd from 9:00 a.m. to 11:00 a.m. (USA Mountain Time) AMSR-E, Aquarius, IceBridge, ICESat/GLAS, MODIS, NISE, and SMAP data will not be available for ordering due to system maintenance.

Published Research

The following references cite studies that used AMSR-E Validation data from NSIDC. Please contact User Services if you have a reference you would like to share on this page.


Gaur, Nandita, and Binayak P. Mohanty. 2016. Land-surface controls on near-surface soil moisture dynamics: Traversing remote sensing footprints. Water Resources Research 52(8): 6365–6385. doi: http://dx.doi.org/10.1002/2015WR018095.

Herzfeld, Ute C., et al. 2016. Geostatistical and Statistical Classification of Sea-Ice Properties and Provinces from SAR Data. Global Biogeochemical Cycles 30(7): 1054–1068. doi: http://dx.doi.org/10.1002/2015GB005337.

Kang, Do-Hyuk, Ana P. Barros, and Edward J. Kim. 2016. Evaluating Multispectral Snowpack Reflectivity With Changing Snow Correlation Lengths. IEEE Transactions on Geoscience and Remote Sensing 54(12): 7378-7384. doi: http://dx.doi.org/10.1109/TGRS.2016.2600958.

Santi, Emanuele, et al. 2016. Integration of passive and active microwave data from SMAP, AMSR2 and Sentinel-1 for Soil Moisture monitoring. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing. Piscataway, NJ: Institute of Electrical and Electronics Engineers ( IEEE ), 5252-5255. doi: http://dx.doi.org/10.1109/IGARSS.2016.7730368.

Shin, Yongchul, et al. 2016. Development of Dynamic Ground Water Data Assimilation for Quantifying Soil Hydraulic Properties from Remotely Sensed Soil Moisture. Water 8(7). Art. #311. doi: http://dx.doi.org/10.3390/w8070311.


Bateni, S. M., et al. 2015. Characterizing Snowpack and the Freeze–Thaw State of Underlying Soil via Assimilation of Multifrequency Passive/Active Microwave Data: A Case Study (NASA CLPX 2003). IEEE Transactions on Geoscience and Remote Sensing 53(1): 173-189. doi: http://dx.doi.org/10.1109/TGRS.2014.2320264.

Bruscantini, Cintia A., et al. 2015. L-Band Radar Soil Moisture Retrieval Without Ancillary Information. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8(12): 5526-5540. doi: http://dx.doi.org/10.1109/JSTARS.2015.2496326.

Chattopadhyay, Asis Kumar, Saptarshi Mondal, and Atanu Biswas. 2015. Independent Component Analysis and Clustering for Pollution Data. Environmental and Ecological Statistics 22(1): 33-43. doi: http://dx.doi.org/10.1007/s10651-014-0287-2.

Cho, Eunsang, Heewon Moon, and Minha Choi. 2015. First Assessment of the Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Contents in Northeast Asia. Journal of the Meteorological Society of Japan 93(1): 117-129. doi: http://dx.doi.org/10.2151/jmsj.2015-008.

Du, Jinyang, J. S. Kimball, and Mahta Moghaddam. 2015. Theoretical Modeling and Analysis of L- and P-band Radar Backscatter Sensitivity to Soil Active Layer Dielectric Variations. Remote Sensing 7(7): 9450-9472. doi: http://dx.doi.org/10.3390/rs70709450.

Kang, Do-Hyuk, Shurun Tang, and Edward J. Kim. 2015. Interpreting snowpack radiometry using currently existing microwave radiative transfer models. Proc. SPIE 9637. Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII. Art. #96371B. Bellingham, WA: SPIE. doi: http://dx.doi.org/10.1117/12.2195502.

Karaman, Muhittin, et al. 2015. Determination of seasonal changes in wetlands using CHRIS/Proba Hyperspectral satellite images: A case study from Acıgöl (Denizli), Turkey. Journal of Environmental Biology 36(S.I.): 73-83.

Kornelsen, Kurt C., Michael H. Cosh, and Paulin Coulibaly. 2015. Potential of bias correction for downscaling passive microwave and soil moisture data. Journal of Geophysical Research - Atmospheres 120(13): 6460-6479. doi: http://dx.doi.org/10.1002/2015JD023550.

Kwon, Yonghwan, et al. 2015. Error Characterization of Coupled Land Surface-Radiative Transfer Models for Snow Microwave Radiance Assimilation. IEEE Transactions on Geoscience and Remote Sensing 53(9): 5247-5268. doi: http://dx.doi.org/10.1109/TGRS.2015.2419977.

Neelam, Maheshwari, and Binayak P. Mohanty. 2015. Global sensitivity analysis of the radiative transfer model. Water Resources Research 51(4): 2428-2443. doi: http://dx.doi.org/10.1002/2014WR016534.

Shen, Xinyi, et al. 2015. A Semiphysical Microwave Surface Emission Model for Soil Moisture Retrieval. IEEE Transactions on Geoscience and Remote Sensing 120(13): 6460-6479. doi: http://dx.doi.org/10.1002/2015JD023550.

Vander Jagt, Benjamin J., et al. 2015. On the characterization of vegetation transmissivity using LAI for application in passive microwave remote sensing of snowpack. Remote Sensing of Environment 156: 310-321. doi: http://dx.doi.org/10.1016/j.rse.2014.09.001.

Zhao, Tianjie, et al. 2015. Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval . Physics and Chemistry of the Earth, Parts A/B/C 83-84: 65-74. doi: http://dx.doi.org/10.1016/j.pce.2015.04.001.


Bi, HaiYun, et al. 2014. Simultaneous Estimation of Soil Moisture and Hydraulic Parameters Using Residual Resampling Particle Filter. Science China-Earth Sciences 57(4): 824-838. doi: http://dx.doi.org/10.1007/s11430-013-4742-y.

Kang, Do Hyuk, A. P. Barros, and S. J. Dery. 2014. Evaluating Passive Microwave Radiometry for the Dynamical Transition From Dry to Wet Snowpacks. IEEE Transactions on Geoscience and Remote Sensing 52(1): 3-15 p. doi: http://dx.doi.org/10.1109/TGRS.2012.2234468.

Kulie, Mark S., et al. 2014. Triple-Frequency Radar Reflectivity Signatures of Snow: Observations and Comparisons with Theoretical Ice Particle Scattering Models. Journal of Applied Meteorology and Climatology 53(4): 1080-1098. doi: http://dx.doi.org/ 10.1175/JAMC-D-13-066.1.

Ling, Zi-wei, Long-bin He, and Hui Zeng. 2014. Evaluating the performance of the UCLA method for spatially downscaling soil moisture products using three Ts/ VI indices. Chinese Journal of Applied Ecology 25(2): 545-552.

Mahdavi, Sahel, Yasser Maghsoudi, and Sahar Dehnavi. 2014. A Method for Soil Moisture Retrieval in Vegetated Areas Using Multi-Frequency Data Considering Different kinds of Interaction in Different Frequencies. Proceedings of EUSAR 2014; 10th European Conference on Synthetic Aperture Radar: 755-758.

Malik, M. Jahanzeb et al. 2014. Improving modeled snow albedo estimates during the spring melt season. Journal of Geophysical Research - Atmospheres 119(12): 7311–7331. doi: http://dx.doi.org/10.1002/2013JD021344.

McCreight, J. L., A. G. Slater, H. P. Marshall, and B. Rajagopalan. 2014. Inference and Uncertainty of Snow Depth Spatial Distribution at the Kilometre Scale in the Colorado Rocky Mountains: The Effects of Sample Size, Random Sampling, Predictor Quality, and Validation Procedures. Hydrological Processes 28(3): 933-957. doi: http://dx.doi.org/10.1002/hyp.9618.

Notarnicola, C. 2014. A Bayesian Change Detection Approach for Retrieval of Soil Moisture Variations Under Different Roughness Conditions. IEEE Geoscience and Remote Sensing Letters 11(2): 414-418. doi: http://dx.doi.org/10.1109/LGRS.2013.2264159.

Notarnicola, C., and Romina Solorza. 2014. Integration of Remotely Sensed Images and Electromagnetic Models into a Bayesian Approach for Soil Moisture Content Retrieval: Methodology and Effect of Prior Information. Dynamic Programming and Bayesian Inference, Concepts and Applications edited by Mohammad Saber Fallah Nezhad. InTech: 39-63. doi: http://dx.doi.org/10.5772/57562.

Peng, Chunming. 2014. Intergration of remote sensing and meteorological data for monitoring agricultural drought. : xvi, 223 p. George Mason University. Ph. D.

Richardson, Mark, Ian Davenport, and Robert Gurney. 2014. Global Snow Mass Measurements and the Effect of Stratigraphic Detail on Inversion of Microwave Brightness Temperatures. Surveys in Geophysics 35: 785–812. doi: http://dx.doi.org/10.1007/s10712-013-9263-x.

Shin, Yongchui, and Yonghun Jung. 2014. Development of Irrigation Water Management Model for Reducing Drought Severity Using Remotely Sensed Soil Moisture Footprints. Journal of Irrigation and Drainage Engineering 140(7). Art. #04014021. doi: http://dx.doi.org/10.1061/(ASCE)IR.1943-4774.0000736.

Srivastava, Prashant K., et al. 2014. Estimation of Land Surface Temperature from Atmospherically Corrected LANDSAT TM Image Using 6S and NCEP Global Reanalysis Product.. Environmental Earth Sciences. doi: http://dx.doi.org/10.1007/s12665-014-3388-1.

Stillman, Susan, et al. 2014. Summer Soil Moisture Spatiotemporal Variability in Southeastern Arizona. Journal of Hydrometeorology 15(4): 1473-1485. doi: http://dx.doi.org/10.1175/JHM-D-13-0173.1.

Tuttle, Samuel E., and Guido D. Salvucci. 2014. A New Approach for Validating Satellite Estimates of Soil Moisture Using Large-Scale Precipitation: Comparing AMSR-E Products. Remote Sensing of Environment 142: 207-222. doi: http://dx.doi.org/10.1016/j.rse.2013.12.002.


De Michele, C., et al. 2013. Investigating the Dynamics of Bulk Snow Density in Dry and Wet Conditions Using a One-Dimensional Model.. The Cryosphere 7: 433-444. doi: http://dx.doi.org/10.5194/tc-7-433-2013.

Dou, TingFeng, and CunDe Xiao. 2013. Measurements of physical characteristics of summer snow cover on sea ice during the Third Chinese Arctic Expedition. Science in Cold and Arid Regions 5(3): 309-315. doi: http://dx.doi.org/10.3724/SP.J.1226.2013.00309.

Gaur, N., and B. P. Mohanty. 2013. Evolution of Physical Controls for Soil Moisture in Humid and Subhumid Watersheds. Water Resources Research 49(3): 1244–1258. doi: http://dx.doi.org/10.1002/wrcr.20069.

Iodice, A., A. Natale, and D. Riccio. 2013. Polarimetric Two-Scale Model for Soil Moisture Retrieval via Dual-Pol HH-VV SAR Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6(3): 1163-1171. doi: http://dx.doi.org/10.1109/JSTARS.2013.2238893.

Logan, Liz, et al. 2013. A Novel Method for Predicting Fracture in Floating Ice. Journal of Glaciology 59(216): 750-758. doi: http://dx.doi.org/10.3189/2013JoG12J210.

Mallick, Kaniska, et al. 2013. Latent Heat Flux and Canopy Conductance Based on Penman–Monteith, Priestley–Taylor Equation, and Bouchet’s Complementary Hypothesis. Journal of Hydrometeorology 14: 419-442. doi: http://dx.doi.org/10.1175/JHM-D-12-0117.1.

Notarnicola, C. 2013. Ensemble of Regressors for Soil Moisture Retrieval in Agricultural Fields. 2013 IEEE International Geoscience and Remote Sensing Symposium (IGARSS): 723-726. doi: http://dx.doi.org/10.1109/IGARSS.2013.6721259.

Ogashawara, I., Marcelo Pedroso Curtarelli, and Celso M. Ferreira. 2013. The Use of Optical Remote Sensing For Mapping Flooded Areas. Journal of Engineering Research and Application 3(5): 1956-1960.

Rösel, Anja. 2013. Melt Pond Determination from MODIS Data. Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Databy Anja Rösel. Springer Netherlands: 27-36. doi: http://dx.doi.org/10.1007/978-3-642-37033-5_5.

Seyednasrollah, Bijan, Mukesh Kumar, and Timothy E. Link. 2013. On the Role of Vegetation Density on Net Snow Cover Radiation at the Forest Floor. Journal of Geophysical Research - Atmospheres 118(15): 8359-8374. doi: http://dx.doi.org/10.1002/jgrd.50575.

Shin, Yongchul, Binayak P. Mohanty, and Amor V. M. Ines. 2013. Estimating Effective Soil Hydraulic Properties Using Spatially Distributed Soil Moisture and Evapotranspiration. Vadose Zone Journal 12(3). doi: http://dx.doi.org/10.2136/vzj2012.0094.

Yang, Yongmin, et al. 2013. A New Evapotranspiration Model Accounting for Advection and Its Validation During SMEX02. Advances in Meteorology 2013. Art. #389568. doi: http://dx.doi.org/10.1155/2013/389568.


Andreadis, Konstantinos M. 2012. Implications of Representing Snowpack Stratigraphy for the Assimilation of Passive Microwave Satellite Observations. Journal of Hydrometeorology 13(5): 1493-1506.

Barnhart, B. L., W. E. Eichinger, and J. H. Prueger. 2012. Introducing an Ogive Method for Discontinuous Data. Agricultural and Forest Meteorology 162-163: 58-62. doi: http://dx.doi.org/10.1016/j.bbr.2011.03.031.

Barnhart, B., W. Eichinger, and J. Prueger. 2012. A New Eddy-Covariance Method Using Empirical Mode Decomposition. Boundary-Layer Meteorology 14 p. doi: http://dx.doi.org/10.1007/s10546-012-9741-6.

Crow, Wade T., Aaron A. Berg, Michael H. Cosh, Alexander Loew, Binayak P. Mohanty, Rocco Panciera, Patricia de Rosnay, Dongryeol Ryu, and Jeffrey P. Walker. 2012. Upscaling Sparse Ground-Based Soil Moisture Observations for the Validation of Coarse-Resolution Satellite Soil Moisture Products. Reviews of Geophysics 50(2).

Davenport, I. J., M. J. Sandells, and R. J. Gurney. 2012. The Effects of Variation in Snow Properties on Passive Microwave Snow Mass Estimation. Remote Sensing of Environment 118: 168-175. doi: http://dx.doi.org/10.1016/j.rse.2011.11.014.

Dietz, Andreas J., Claudia Kuenzer, and Ursula Gessner. 2012. Remote Sensing of Snow - a Review of Available Methods. International Journal of Remote Sensing 33(13): 4094-4134. doi: http://dx.doi.org/10.1080/101431161.2011.640964.

Do Hyuk Kang and A. P. Barros. 2012.  Observing System Simulation of Snow Microwave Emissions Over Data Sparse Regions–Part II: Multilayer Physics. Geoscience and Remote Sensing, IEEE Transactions 50(5): 1806-1820.

Jiang, Lingmei, et al. 2012. Evaluation of Emission from Snow-Covered Ground for Passive Microwave Remote Sensing. International Journal of Remote Sensing 33(3): 872-886. doi: http://dx.doi.org/10.1080/01431161.2011.577835.

Kim, J., and T. S. Hogue. 2012. Improving Spatial Soil Moisture Representation Through Integration of AMSR-E and MODIS Products. Ieee Transactions on Geoscience and Remote Sensing 50(20): 446-460. doi: http://dx.doi.org/10.1109/tgrs.2011.2161318.

Malik, M. J., R. van der Velde, Z. Vekerdy, and Z. B. Su. 2012. Assimilation of Satellite-Observed Snow Albedo in a Land Surface Model. Journal of Hydrometeorology 13(3): 1119-1130. doi: http://dx.doi.org/10.1175/jhm-d-11-0125.1.

Mao, Ke-biao, et al. 2012. The Monitoring Analysis for the Drought in China by Using an Imporved MPI Method. Journal of Integrative Agriculture 11(6): 1048-1058. doi: http://dx.doi.org/10.1016/S2095-3119(12)60097-5.

Natale, A., A. Iodice, and D. Riccio. 2012. Soil Moisture Retrieval via the Polarimetric Two-Scale Model and Dual-Pol SAR Data. Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International 22-27 July 2012:  646-649. doi: http://dx.doi.org/10.1109/IGARSS.2012.6351511.

Notarnicola, C. 2012. Retrieval of Soil Moisture Variations in Agricultural Fields through a New Bayesian Change Detection Approach. Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International 22-27 July 2013: 1235-1238. doi: http://dx.doi.org/10.1109/IGARSS.2012.6351320.

Srivastava, Prashant K., et al. 2012. Selection of Classification Techniques for Land Use/Land Cover Change Investigation. Advances in Space Research 50(9): 1250-1265. doi: http://dx.doi.org/10.1016/j.asr.2012.06.032.

Zaman, Bushra, Mac Mckee, and Christopher M. U. Neale. 2012. Fusion of Remotely Sensed Data for Soil Moisture Estimation Using Relevance Vector and Support Vector Machines. International Journal of Remote Sensing 33(20): 6516-6552. doi: http://dx.doi.org/10.1080/01431161.2012.690540.


Chopping, M., C. B. Schaaf, F. Zhao, Z. Wang, A. W. Nolin, G. G. Moisen, J. V. Martonchik, and M. Bull. 2011. Forest Structure and Aboveground Biomass in the Southwestern United States from MODIS and MISR. Remote Sensing of Environment  115(11): 2943-2953. doi: http://dx.doi.org/10.1016/j.rse.2010.08.031.

Foster, J. L., D. K. Hall, J. B. Eylander, G. A. Riggs, S. V. Nghiem, M. Tedesco, E. Kim, P. M. Montesano, R. E. J. Kelly, K. A. Casey, and B. Choudhury. 2011. A Blended Global Snow Product Using Visible, Passive Microwave and Scatterometer Satellite Data. International Journal of Remote Sensing 32(5): 1371-1395. doi: http://dx.doi.org/10.1080/01431160903548013.

Hong, S., and I. Shin. 2011. A Physically-Based Inversion Algorithm for Retrieving Soil Moisture in Passive Microwave Remote Sensing. Journal of Hydrology 405 (1-2): 24-30. doi: http://dx.doi.org/10.1016/j.jhydrol.2011.05.005.

Hosseini, M., and M. R. Saradjian. 2011. Soil Moisture Estimation Based on Integration of Optical and Sar Images. Canadian Journal of Remote Sensing 37(1): 112-121. doi: http://dx.doi.org/10.5589/m11-015.

Li, Q., et al. 2011. Comparison of Two Retrieval Methods with Combined Passive and Active Microwave Remote Sensing Observations for Soil Moisture. Mathematical and Computer Modelling 54(3-4): 1181-1193. doi: http://dx.doi.org/10.1016/j.mcm.2010.11.052.

Liao, L., and R. Meneghini 2011. A Study on the Feasibility of Dual-Wavelength Radar for Identification of Hydrometeor Phases. Journal of Applied Meteorology & Climatology 50(2): 449-456. doi: http://dx.doi.org/10.1175/2010jamc2499.1.

Malik, M. J., R. van der Velde, Z. Vekerdy, Z. Su, and M. F. Salman. 2011. Semi-Empirical Approach for Estimating Broadband Albedo of Snow. Remote Sensing of Environment 115(8): 2086-2095. doi: http://dx.doi.org/10.1016/j.rse.2011.04.010.

Manfreda, S., et al. 2011. On the Use of Amsu-Based Products for the Description of Soil Water Content at Basin Scale. Hydrology and Earth System Sciences Discussions 8(3): 5319-5353. doi: http://dx.doi.org/10.5194/hessd-8-5319-2011.

Mascaro, G., E. R. Vivoni, and R. Deidda 2011. Soil Moisture Downscaling across Climate Regions and Its Emergent Properties. J. Geophys. Res. 116(D22): D22114. doi: http://dx.doi.org/10.1029/2011jd016231.

McCabe, M., E. Wood, H. Su, R. Vinukollu, C. Ferguson, and Z. Su. 2011. Multisensor Global Retrievals of Evapotranspiration for Climate Studies Using the Surface Energy Budget System. Land Remote Sensing and Global Environmental Change, edited by Ramachandran, B., C. O. Justice and M. J. Abrams: Springer New York: 747-778. doi: http://dx.doi.org/10.1007/978-1-4419-6749-7_33.

Negi, H. S., and A. Kokhanovsky. 2011. Retrieval of Snow Grain Size and Albedo Ofwestern Himalayan Snow Cover Using Satellite Data. The Cryosphere Discussions 5: 605-653. doi: http://dx.doi.org/10.5194/tcd-5-605-2011.

von Lerber, A., D. Moisseev, J. Leinonen, J. Tyynela, V. Chandrasekar, and M. T. Hallikainen 2011. Modeling Melting Layer Radar Observations at Gpm Frequencies; Comparison to Measurements. In Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International, 24-29 July 2011: 2507-2510.

Zhang, J., F. Yao, B. Li, H. Yan, Y. Hou, G. Cheng, and V. Boken. 2011. Progress in Monitoring High-Temperature Damage to Rice through Satellite and Ground-Based Optical Remote Sensing. SCIENCE CHINA Earth Sciences: 1-11 p. doi: http://dx.doi.org/10.1007/s11430-011-4210-5.


Al-Jassar, H. K., and K. S. Rao. 2010. Monitoring of Soil Moisture over the Kuwait Desert Using Remote Sensing Techniques. International Journal of Remote Sensing 31(16): 4373-4385. doi: http://dx.doi.org/10.1080/01431160903258233.

Colliander, A., et al. 2010. Utilization of Airborne and in Situ Data Obtained in Sgp99, Smex02, Clasic and Smapvex08 Field Campaigns for Smap Soil Moisture Algorithm Development and Validation. In Microwave Radiometry and Remote Sensing of the Environment (MicroRad), 2010 11th Specialist Meeting: 43-48. doi: http://dx.doi.org/10.1109/MICRORAD.2010.5559592.

Du, J., J. Shi, and H. Rott. 2010. Comparison between a Multi-Scattering and Multi-Layer Snow Scattering Model and Its Parameterized Snow Backscattering Model.. Remote Sensing of Environment 114(5): 1089-1098. doi: http://dx.doi.org/10.1016/j.rse.2009.12.020.

Duerr, R., R. Weaver, and M. A. Parsons. 2010. A New Approach to Preservation Metadata for Scientific Data – a Real World Example. Standard-Based Data and Information Systems for Earth Observation, edited by Di, L. and H. K. Ramapriyan: Springer Berlin Heidelberg: 113-125. doi: http://dx.doi.org/10.1007/978-3-540-88264-0_7.

Esmaeily-Gazkohani, A., H. B. Granberg, and Q. H. J. Gwyn. 2010. Repeat-Pass Cross-Track Interferometric Sar to Measure Dry Snow Water Equivalent and Depth. Canadian Journal of Remote Sensing 36 (S2): S316-S326. doi: http://dx.doi.org/10.5589/m10-064.

Parsons, M. A., R. Duerr, and J.-B. Minster. 2010. Data Citation and Peer Review. EOS 91(34): 297-298.

Pierdicca, N., L. Pulvirenti, and C. Bignami. 2010. Soil Moisture Estimation over Vegetated Terrains Using Multitemporal Remote Sensing Data. Remote Sensing of Environment 114(2): 440-448.

Ryu, D., et al. 2010. Soil Moisture Retrieval Using a Two-Dimensional L-Band Synthetic Aperture Radiometer in a Semiarid Environment. IEEE Transactions on Geoscience and Remote Sensing 48(12): 4273-4284.

Zhong, Ruofei, et al. 2010. Large-Scale Microwave Remote Sensing of Retrieving Surface Multi-Parameters Using Active and Passive Satellite Data: In the Tibetan Plateau Region of Maqu. Computer and Computing Technologies in Agriculture V, edited by Daoliang Li and Yingyi Chen, Springer Boston:  415-426.


Andreadis, K. M., D. Liang, L. Tsang, D. P. Lettenmaier, and E. G. Josberger. 2008. Characterization of Errors in a Coupled Snow Hydrology-Microwave Emission Model. Journal of Hydrometeorology 9(1): 149-164.

Bindlish, R., et al. 2008. Aircraft Based Soil Moisture Retrievals under Mixed Vegetation and Topographic Conditions. Remote Sensing of Environment 112(2): 375-390.

Choi, M. H., J. M. Jacobs, and D. D. Bosch. 2008. Remote Sensing Observatory Validation of Surface Soil Moisture Using Advanced Microwave Scanning Radiometer E, Common Land Model, and Ground Based Data: Case Study in SMEX03 Little River Region, Georgia, USA. Water Resources Research 44(W08421). doi: http://dx.doi.org/10.1029/2006WR005578.

Choi, M., and J. M. Jacobs. 2008. Temporal Variability Corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) Surface Soil Moisture: Case Study in Little River Region, Georgia USA. Sensors 8(4): 2617-2627.

Das, N. N., B. P. Mohanty, and E. G. Njoku. 2008. A Markov Chain Monte Carlo Algorithm for Upscaled Soil-Vegetation-Atmosphere-Transfer Modeling to Evaluate Satellite-Based Soil Moisture Measurements. Water Resources Research 44( W05416). doi: http://dx.doi.org/10.1029/2007WR006472.

Davis, R. E., et al. 2008. NASA Cold Land Processes Experiment (CLPX 2002/03): Spaceborne Remote Sensing. Journal of Hydrometeorology 9(6): 1427-1433.

Famiglietti, J. S., D. R. Ryu, A. A. Berg, M. Rodell, and T. J. Jackson. 2008. Field Observations of Soil Moisture Variability Across Scales. Water Resources Research 44(W01423). doi: http://dx.doi.org/10.1029/2006WR005804.

Gruhier, C., P. de Rosnay, Y. Kerr, E. Mougin, E. Ceschia, J. C. Calvet, and P. Richaume. 2008. Evaluation of AMSR-E Soil Moisture Product Based on Ground Measurements over Temperate and Semi-Arid Regions. Geophysical Research Letters 35(L10405). doi: http://dx.doi.org/10.1029/2008GL033330.

Hwang, B. J., and D. G. Barber. 2008. On the Impact of Ice Emissivity on Sea Ice Temperature Retrieval Using Passive Microwave Radiance Data. IEEE Geoscience and Remote Sensing Letters 5(3): 448-452.

Inoue, J., J. A. Curry, and J. A. Maslanik. 2008. Application of Aerosondes to Melt-Pond Observations over Arctic Sea Ice. Journal of Atmospheric and Oceanic Technology 25(2): 327-334.

Lee, H., and H. Han. 2008. Evaluation of SSM/I and AMSR-E Sea Ice Concentrations in the Antarctic Spring Using KOMPSAT-1 EOC Images. IEEE Transactions on Geoscience and Remote Sensing 46(7): 1905-1912.

Leuschen, C. J., et al. 2008. Combination of Laser and Radar Altimeter Height Measurements to Estimate Snow Depth During the 2004 Antarctic AMSR-E Sea Ice Field Campaign. Journal of Geophysical Research 113(C04S90). doi: http://dx.doi.org/10.1029/2007JC004285.

McCabe, M. F., et al. 2008. Hydrological Consistency Using Multi-Sensor Remote Sensing Data for Water and Energy Cycle Studies. Remote Sensing of Environment 112(2): 430-444.

Naoki, K., J. Ukita, F. Nishio, M. Nakayama, J. C. Comiso, and A. Gasiewski. 2008. Thin Sea Ice Thickness as Inferred from Passive Microwave and In Situ Observations. Journal of Geophysical Research 113(C02S16). doi: http://dx.doi.org/10.1029/2007JC004270.

O'Carroll, A. G., J. R. Eyre, and R. W. Saunders. 2008. Three-Way Error Analysis Between AATSR, AMSR-E, and In Situ Sea Surface Temperature Observations. Journal of Atmospheric and Oceanic Technology 25(7): 1197-1207.

Parkinson, C. L., and J. C. Comiso. 2008.  Antarctic Sea Ice Parameters from AMSR-E Data Using Two Techniques and Comparisons with Sea Ice from SSM/I. Journal of Geophysical Research 113(C02S06). doi: http://dx.doi.org/10.1029/2007JC004253.

Pulvirenti, L., N. Pierdicca, and F. S. Marzano. 2008. Topographic Effects on the Surface Emissivity of a Mountainous Area Observed by a Spaceborne Microwave Radiometer. Sensors 8(3): 1459-1474.

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