Published Research

The following references cite studies that used data distributed by NSIDC DAAC. Please contact User Services if you have a reference you would like to share on this page.


Colliander, Andreas; Cosh, Michael H.; Misra, Sidharth; Jackson, Thomas J.; Crow, Wade T.; Powers, Jarrett; McNairn, Heather; Bullock, Paul; Berg, Aaron; Magagi, Ramata; Gao, Ying; Bindlish, Rajat; Williamson, Ross; Ramos, Isaac; Latham, Barron; O'Neill. 2019. Comparison of high-resolution airborne soil moisture retrievals to SMAP soil moisture during the SMAP validation experiment 2016 (SMAPVEX16). Remote Sensing of Environment. doi:


Gao, Y.; Walker, J.P.; Ye, N.; Pancera, R.; Monerris, A.; Ryu, D.; Rudiger, C.; Jackson, T.J. 2018. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. . doi:

Kim, S-B.; Huang, H.; Liao, T-H.; Colliander, A. 2018. Estimating Vegetation Water Content and Soil Surface Roughness Using Physical Models of L-Band Radar Scattering for Soil Moisture Retrieval. Remote Sensing 10(4). doi:

Rowlandson, T.L.; Berg, A.A.; Roy, A.; Kim, E.; Pardo Lara, R.; Powers, J.; Lewis, K.; Houser, P.; McDonald, K.; Toose, P.; Wu, A.; De Marco, E.; Derksen, C.; Entin, J.; Colliander, A.; Xu, X.; Mavrovic, A. 2018. Capturing agricultural soil freeze/thaw state through remote sensing and ground observations: A soil freeze/thaw validation campaign. Remote Sensing of Environment 211: 59-70. doi:

Rowlandson, T.L.; Berg, A.A; Bullock, P.R.; Hanis-Gervais, K.; Ojo, E.R.T.; Cosh, M.H.; Powers, J.; McNairn, H. 2018. Temporal transferability of soil moisture calibration equations. Journal of Hydrology 556: 349-358. doi:

Wang, H.; Magagi, R.; Goïta, K. 2018. Potential of a two-component polarimetric decomposition at C-band for soil moisture retrieval over agricultural fields. Remote Sensing of Environment 217: 38-51. doi:

Zhu, L.; Walker, J.P.; Ye, N.; Rudiger, C.; Hacker, J.; Panciera, R.; Tanase, M.A.; Wu, X.; Gray, D.A.; Stacy, N.; Goh, A.; Yardley, H.; Mead, J. 2018. The Polarimetric L-Band Imaging Synthetic Aperture Radar (PLIS): Description, Calibration, and Cross-Validation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. doi:


Cai, Xitian, et al. 2017. Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model. Water Resources Research 53(4): 3013–3028. doi:

Chakrabarti, S.; Judge, J.; Rangarajan, A.; Ranka, S. 2017. Utilizing Self-Regularized Regressive Models to Downscale Microwave Brightness Temperatures for Agricultural Land Covers in the SMAPVEX-12 Region. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing 10(2): 478. doi:

Clewley, D.; Whitcomb, J.B.; Akbar, R.; Silva, A.R.; Berg, A.; Adams, J.R.; Caldwell, T.; Entekhabi, D.; Moghaddam, M. 2017. A Method for Upscaling In Situ Soil Moisture Measurements to Satellite Footprint Scale Using Random Forests. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing 10(6): 2663. doi:

Colliander, A.; Cosh, M.H.; Misra, S.; Jackson, T.J.; Crow, W.T.; Chan, S.; Bindlish, R.; Chae, C.; Holifield Collins, C.; Yueh, S.H. 2017. Validation and scaling of soil moisture in a semi-arid environment: SMAP validation experiment 2015 (SMAPVEX15). Remote Sensing of Environment. doi:

Emami, H.; Mojaradi, B.; 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. International Journal of Remote Sensing 38(23): 6623. doi:

Fascetti, F.; Pierdicca, N.; Pulvirenti, L. 2017. Empirical fitting of forward backscattering models for multitemporal retrieval of soil moisture from radar data at L-band. Journal of Applied Remote Sensing 11: 16002. doi:

Garnaud, C.; Bélair, S.; Carrera, M.L.; Mcnairn, H.; Pacheco, A. 2017. Field-Scale Spatial Variability of Soil Moisture and L-B and Brightness Temperature from Land Surface Modeling. Journal of Hydrometeorology. doi:

Huang, H.; Liao, T-H.; Tsang, L.; Njoku, E.G.; Colliander, A.; Jackson, T.J.; Burgin, M.S.; Yueh, S. 2017. Modelling and Validation of Combined Active and Passive Microwave Remote Sensing of Agricultural Vegetation at L-Band. Progress in Electromagnetics Research B 78: 91-124. doi:

Ma, J.; Huang, S.; Li, J.; Li, X.; Song, X.; Leng, P.; Sun, Y. 2017. Estimating Vegetation Water Content of Corn and Soybean Using Different Polarization Ratios Based on L- and S-Band Radar Data. IEEE Geoscience & Remote Sensing Letters 14(3): 364-368. doi:

Manns, H.R.; Berg, A.A.; Bullock, P.R.; McNairn, H.; Groenevelt, P.; Yang, W. 2017. Importance of soil organic carbon in near-surface soil water content estimation: A simple model comparison in dry-end Canadian Prairie soils. Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques 42(4): 364. doi:

Wang, H.; Magagi, R.; Goita, K. 2017. Comparison of different polarimetric decompositions for soil moisture retrieval over vegetation covered agricultural area. Remote Sensing of Environment. doi:

Wu, X.; Walker, J.P.; Rudiger, C.; Panciera, R.; Gao, Y. 2017. Intercomparison of Alternate Soil Moisture Downscaling Algorithms Using Active–Passive Microwave Observations. IEEE Geoscience & Remote Sensing Letters. doi:

Wu, X.; Walker, J.P.; Rudiger, C.; Panciera, R.; Gao, Y. 2017. Medium-Resolution Soil Moisture Retrieval Using the Bayesian Merging Method. IEEE Transactions on Geoscience and Remote Sensing. doi:


Colliander, Andreas, et al. 2016. Retrieving soil moisture for non-forested areas using PALS radiometer measurements in SMAPVEX12 field campaign. Remote Sensing of Environment 184: 86-100. doi:

Djamai, Najib, et al. 2016. A combination of DISPATCH downscaling algorithm with CLASS land surface scheme for soil moisture estimation at fine scale during cloudy days. Remote Sensing of Environment 184: 1-14. doi:

Ma, Hongzhang, and and Sumei Liu. 2016. The Potential Evaluation of Multisource Remote Sensing Data for Extracting Soil Moisture Based on the Method of BP Neural Network. Canadian Journal of Remote Sensing 42(2): 117-124. doi:

Ma, Hongzhang, et al. 2016. Active and passive cooperative algorithm at L-Band for bare soil moisture inversion. Transactions of the Chinese Society of Agricultural Engineering 32(19): 131-138. doi:

Wang, Hongquan, et al. 2016. Evaluation of Simplified Polarimetric Decomposition for Soil Moisture Retrieval over Vegetated Agricultural Fields. Remote Sensing 8(2). Art. #142. doi:


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:

Colliander, A., et al. 2015. Comparison of Airborne Passive and Active L-Band System (PALS) Brightness Temperature Measurements to SMOS Observations During the SMAP Validation Experiment 2012 (SMAPVEX12). IEEE Geoscience and Remote Sensing Letters 12(4): 801-805. doi:

Manns, Hida R., Aaron A. Berg, and Andreas Colliander. 2015. Soil organic carbon as a factor in passive microwave retrievals of soil water content over agricultural croplands. Journal of Hydrology 528: 643-651. doi: