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Publications Citing EOS Land Validation

The following 16 publications cited the EOS Land Validation project.

YearCitationDataset or Project
2023Kobayashi, T., H. Kobayashi, W. Yang, H. Murakami, Y. Honda, and K. Nishida Nasahara. 2023. The development of a global LAI and FAPAR product using GCOM-C/SGLI data. ISPRS Journal of Photogrammetry and Remote Sensing. 202:479-498. https://doi.org/10.1016/j.isprsjprs.2023.07.003
2021Guglielmo, M., F.H.M. Tang, C. Pasut, and F. Maggi. 2021. SOIL-WATERGRIDS, mapping dynamic changes in soil moisture and depth of water table from 1970 to 2014. Scientific Data. 8(1):. https://doi.org/10.1038/s41597-021-01032-4
2021O., S. and R. Orth. 2021. Global soil moisture data derived through machine learning trained with in-situ measurements. Scientific Data. 8(1):. https://doi.org/10.1038/s41597-021-00964-1
2020Zhang, Y. and S. Liang. 2020. Fusion of Multiple Gridded Biomass Datasets for Generating a Global Forest Aboveground Biomass Map. Remote Sensing. 12(16):2559. https://doi.org/10.3390/RS12162559
2019Reichle, R.H., Q. Liu, R.D. Koster, W.T. Crow, G.J.M. De Lannoy, J.S. Kimball, J.V. Ardizzone, D. Bosch, A. Colliander, M. Cosh, J. Kolassa, S.P. Mahanama, J. Prueger, P. Starks, and J.P. Walker. 2019. Version 4 of the SMAP Level-4 Soil Moisture Algorithm and Data Product. Journal of Advances in Modeling Earth Systems. 11(10):3106-3130. https://doi.org/10.1029/2019MS001729
2018Alemohammad, S.H., J. Kolassa, C. Prigent, F. Aires, and P. Gentine. 2018. Global Downscaling of Remotely-Sensed Soil Moisture using Neural Networks. Hydrology and Earth System Sciences Discussions. 1-19. https://doi.org/10.5194/hess-2017-680
2018Kolassa, J., R.H. Reichle, Q. Liu, S.H. Alemohammad, P. Gentine, K. Aida, J. Asanuma, S. Bircher, T. Caldwell, A. Colliander, M. Cosh, C. Holifield Collins, T.J. Jackson, J. Martinez-Fernandez, H. McNairn, A. Pacheco, M. Thibeault, and J.P. Walker. 2018. Estimating surface soil moisture from SMAP observations using a Neural Network technique. Remote Sensing of Environment. 204:43-59. https://doi.org/10.1016/j.rse.2017.10.045
2017Clewley, D., J.B. Whitcomb, R. Akbar, A.R. Silva, A. Berg, J.R. Adams, T. Caldwell, D. Entekhabi, and M. Moghaddam. 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 and Remote Sensing. 10(6):2663-2673. https://doi.org/10.1109/JSTARS.2017.2690220
2016Carroll, M.L., M.E. Brown, M.R. Wooten, J.E. Donham, A.B. Hubbard, and W.B. Ridenhour. 2016. In situ air temperature and humidity measurements over diverse land covers in Greenbelt, Maryland, November 2013-November 2015. Earth System Science Data. 8(2):415-423. https://doi.org/10.5194/essd-8-415-2016
2016Khwairakpam Amitab, , Debdatta Kandar, and A.K. Maji. 2016. Comparative Evaluation of Radial Basis Function Network Transfer Function for Filtering Speckle Noise in Synthetic Aperture Radar Images. 243-252. https://doi.org/10.1007/978-981-10-0287-8_22
2016Wang, Y., G. Li, J. Ding, Z. Guo, S. Tang, C. Wang, Q. Huang, R. Liu, and J.M. Chen. 2016. A combined GLAS and MODIS estimation of the global distribution of mean forest canopy height. Remote Sensing of Environment. 174:24-43. https://doi.org/10.1016/j.rse.2015.12.005
2014Dongdong Wang, and Shunlin Liang. 2014. Improving LAI Mapping by Integrating MODIS and CYCLOPES LAI Products Using Optimal Interpolation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7(2):445-457. https://doi.org/10.1109/JSTARS.2013.2264870
2014Dongdong Wang, and Shunlin Liang. 2014. Improving LAI Mapping by Integrating MODIS and CYCLOPES LAI Products Using Optimal Interpolation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7(2):445-457. https://doi.org/10.1109/JSTARS.2013.2264870
2014Gonsamo, A. and J.M. Chen. 2014. Improved LAI Algorithm Implementation to MODIS Data by Incorporating Background, Topography, and Foliage Clumping Information. IEEE Transactions on Geoscience and Remote Sensing. 52(2):1076-1088. https://doi.org/10.1109/TGRS.2013.2247405
2013Leonenko, G., S.O. Los, and P.R.J. North. 2013. Retrieval of leaf area index from MODIS surface reflectance by model inversion using different minimization criteria. Remote Sensing of Environment. 139:257-270. https://doi.org/10.1016/j.rse.2013.07.012
2008Ganguly, S., (2008). EARTH SYSTEM DATA RECORDS OF VEGETATION LEAF AREA INDEX FROM MULTIPLE SATELLITE-BORNE SENSORS. Geography and Environment, Doctor of Philosophy.