Articles | Volume 16, issue 10
https://doi.org/10.5194/hess-16-3659-2012
https://doi.org/10.5194/hess-16-3659-2012
Research article
 | 
16 Oct 2012
Research article |  | 16 Oct 2012

An algorithm for generating soil moisture and snow depth maps from microwave spaceborne radiometers: HydroAlgo

E. Santi, S. Pettinato, S. Paloscia, P. Pampaloni, G. Macelloni, and M. Brogioni

Related subject area

Subject: Global hydrology | Techniques and Approaches: Remote Sensing and GIS
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Cited articles

Angiuli, E., Del Frate, F., and Monerris, A.: Application of Neural Networks to Soil Moisture Retrievals from L-Band Radiometric Data, Proc. IEEE Intern. Geosci Remote Sens. Symp., IGARSS 2008, Boston, MA, USA, II-61–II-64, 2008.
Balling, J., Søbjoerg, S., Kristensen, S., and Skou, N.: RFI and SMOS: Preparatory campaigns and first observations from space, Proc. 11th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), Washington, DC, March 2010, 282–287, 2010.
Barre, H. M. J., Duesmann, B., and Kerr, Y. H.: SMOS: The Mission and the System, IEEE T. Geosci. Remote Sens., 46, 587–593, March, 2008.
Bates, B. C., Kundzewicz, Z. W., Wu, S., and Palutikof, J. P. (Eds.): IPCC Secretariat, Geneva, 210 pp., June, 2008.
Becker, F. and Choudhury, B.: Relative Sensitivity of Normalized Difference Vegetation Index (NDVI) and Microwave Polarization Difference Index (MPDI) for Vegetation and Desertification Monitoring, Remote Sens. Environ., 24, 297–311, 1988.
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