On the use of temporal series of L-and X-band SAR data for soil moisture retrieval. Capitanata plain case study

References

• Baghdadi N., Gaultier S., King C. (2002)—Retrieving surface roughness and soil moisture from synthetic aperture radar (SAR) data using neural network. Canadian Journal of Remote Sensing, 28 (5): 701–711. doi: http://dx.doi.org/10.5589/m03-057.
   Web of Science ®Google Scholar
• Baghdadi N. Bernier M., Gauthier R., Neeson I. (2001)—Evaluation of C-band SAR data for wetlands mapping. International Journal of Remote Sensing, 22 (1): 71–88. doi: http://dx.doi.org/10.1080/014311601750038857.
   Web of Science ®Google Scholar
• Balenzano A., Mattia F., Satalino G., Pauwels V., Snoeij P. (2012)—SMOSAR algorithm for soil moisture retrieval using Sentinel-1 data. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany, 1200–1203. doi: http://dx.doi.org/10.1109/IGARSS.2012.6351332.
   Google Scholar
• Balenzano A, Mattia F., Satalino G., Davidson M. (2011)—Dense temporal series of C-and L-band SAR data for soil moisture retrieval over agricultural crops. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4 (2): 439–450. doi: http://dx.doi.org/10.1109/JSTARS.2010.2052916.
   Web of Science ®Google Scholar
• Brown S.C.M, Quegan S., Morrison K., Bennett J.C., Cookmartin G. (2003)—HighResolution Measurements of Scattering in Wheat Canopies—Implications for Crop Parameter Retrieval. IEEE Transactions on Geoscience and Remote Sensing, 41 (7): 1602–1610. doi: http://dx.doi.org/10.1109/TGRS.2003.814132.
   Web of Science ®Google Scholar
• Covello F., Battazza F., Coletta A., Lopinto E., Fiorentino C., Pietranera L., Valentini G., Zoffolia S. (2010)—COSMO-SkyMed an existing opportunity for observing the Earth. Journal of Geodynamics, 49 (3–4): 171–180. doi: http://dx.doi.org/10.1016/j.jog.2010.01.001.
   Web of Science ®Google Scholar
• Giraldez A.E. (2003)—Saocom-1 Argentina L band SAR mission overview. Coastal and Marine Applications of SAR Symposium.
   Google Scholar
• Hallikainen M.T., Ulaby F.T., Dobson M.C., M. El-Rayes A., Wu L.K. (1985)—Microwave dielectric behaviour of wet soil part I: Empirical models and experimental observations. IEEE Transactions on Geoscience and Remote Sensing, GE-23: 25–34. doi: http://dx.doi.org/10.1016/10.1109/TGRS.1985.289497.
   Web of Science ®Google Scholar
• Hornàĉek M., Wagner W., Sabel D., Truong H.L., Snoeij P., Hahmann T., Diedrich E., Doubkovà M. (2012)—Potential for high resolution systematic global surface soil moisture retrieval via change detection using Sentinel-1. IEEE Journal of Selected Topics in Applied Earth Observations abd Remote Sensing, 5 (4): 1303–1311. doi: http://dx.doi.org/10.1016/10.1109/JSTARS.2012.2190136.
   Web of Science ®Google Scholar
• Iacobellis V., Gioia A., Milella P., Satalino G., Balenzano A., Mattia F. (2013) -Inter-comparison of hydrological model simulations with dense time series of SAR-derived soil moisture map. European Journal of Remote Sensing, 46: 739–757. doi: http://dx.doi.org/10.5721/EuJRS20134644.
   Web of Science ®Google Scholar
• Kerr Y.H., Waldteufel P., Wigneron J.P., Delwart S., Cabot F., Boutin J., Escorihuela M.J., Font J., Reul N., Gruhier C., Juglea S.E., Drinkwater M.R., Hahne A., Martin-Neira M., Mecklenburg S. (2010)—The SMOS Mission: New Tool for Monitoring Key Elements of the Global Water Cycle. IEEE Transactions on Geoscience and Remote Sensing, 98 (5): 666–687. doi: http://dx.doi.org/10.1016/10.1109/JPROC.2010.2043032
   Google Scholar
• Lee J.S., Hoppel K.W., Mango S.A, Miller A.R. (1994)—Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery. IEEE Transactions on Geoscience and Remote Sensing, 32 (5): 1017–1028. doi: http://dx.doi.org/10.1016/10.1109/36.312890.
   Web of Science ®Google Scholar
• Le Toan T., Laur H., Mougin E., Lopes A. (1989)—Multitemporal and dual polarization observations of agricultural vegetation covers by X-band SAR images. IEEE Transactions on Geoscience and Remote Sensing, 27 (6): 709–718. doi: http://dx.doi.org/10.1016/10.1109/TGRS.1989.1398243.
   Web of Science ®Google Scholar
• Macelloni G., Paloscia S., Pampaloni P., Sigismondi S., De Matthaeis P., Ferrazzoli P., Schiavon G., Solimini D. (1999)—The SIR-C/X-SAR experiment on Montespertoli: Sensitivity to hydrological parameters. International Journal of Remote Sensing, 20 (13): 2597–2612. doi: http://dx.doi.org/10.1016/10.1080/014311699211958.
   Web of Science ®Google Scholar
• Mattia F., Satalino G., Balenzano A., D'Urso G., Capodici F., Iacobellis V., Gioia A., Milella P., Rinaldi M., Ruggieri S., Dini L. (2012) -Time series of COSMO-SkyMed data for landcover classification and surface parameter retrieval over agricultural sites. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany, 6511–6514. doi: http://dx.doi.org/10.1016/10.1109/IGARSS.2012.6352738.
   Google Scholar
• Mattia F., Satalino G., Pauwels V, Loew A. (2009)—Soil moisture retrieval through a merging of multi-temporal L-band SAR data and hydrologic modelling. Hydrology and Earth System Sciences, 13(3): 343–356. doi: http://dx.doi.org/10.1016/10.5194/hess-13-343-2009.
   Web of Science ®Google Scholar
• Mattia F., Satalino G., Dente L., Pasquariello G. (2006)—Using A Priori Information to Improve Soil Moisture Retrieval From ENVISAT ASAR AP Data in Semiarid Regions. IEEE Transactions on Geoscience and Remote Sensing, 44 (4): 900–912. doi: http://dx.doi.org/10.1016/10.1109/TGRS.2005.863483.
   Web of Science ®Google Scholar
• Naeimi V., Scipal K., Bartalis Z, Hasenauer S., Wagner W. (2009)—An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations. IEEE Transactions on Geoscience and Remote Sensing, 47 (7): 1999–2013. doi: http://dx.doi.org/10.1016/10.1109/TGRS.2008.2011617.
   Web of Science ®Google Scholar
• Pierdicca N., Pulvirenti L., Pace G. (2013)—A prototype software package to retrieve soil moisture from Sentinel-1 data using a Bayesian multitemporal algorithm. Accepted for publication in the Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
   Google Scholar
• Prevot L., Champion I., Guyot G. (1993)—Estimating surface soil moisture and leaf area index of wheat canopy using a dual-frequency (C and X bands) scatterometer. Remote Sensing of Environment, 46: 331–339. doi: http://dx.doi.org/10.1016/10.1016/0034-4257(93)90053-Z.
   Web of Science ®Google Scholar
• Rinaldi M., Campi P., Castellini M., Ferrara R.M., Fiorentino C., Garofalo P., Satalino G. (2007) -AQUATER Project: The Measurement Campaign in Capitanata Plain of Soil-Plant-Atmosphere Continuum. Proceedings of the 5th International Symposium on Retrieval of Bio-and Geophysical Parameters from SAR Data for Land Applications, Bari, Italy.
   Google Scholar
• Quegan S., Yu J.J. (2001)—Filtering of Multichannel SAR Images. IEEE Transactions on Geoscience and Remote Sensing, 39 (11): 2372–2379. doi: http://dx.doi.org/10.1016/10.1109/36.964973.
   Google Scholar
• Oliver C., Quegan S. (1988)—Understanding Synthetic Aperture Radar Images. Artech House, Boston.
   Google Scholar
• Satalino G., Balenzano A., Mattia F., Davidson M.W.J. (2013)—C-band SAR data for mapping crops dominated by surface or volume scattering. IEEE Geoscience and Remote Sensing Letters, doi: http://dx.doi.org/10.1016/10.1109/LGRS.2013.2263034.
   Google Scholar
• Satalino G., Panciera R., Balenzano A., Mattia F., Walker J. (2012)—COSMO-SkyMed multi-temporal data for landcover classification and soil moisture retrieval over an agricultural site in Southern Australia, Proceedings of 2012 International Geoscience and Remote Sensing Symposium, Munich, Germany, 5701–5704. doi: http://dx.doi.org/10.1016/10.1109/IGARSS.2012.6352317.
   Google Scholar
• Satalino G., Mattia F., Le Toan T., Rinaldi M. (2009)—Wheat mapping by using ASAR AP data. IEEE Transactions on Geoscience and Remote Sensing, 47 (2): 527–530. doi: http://dx.doi.org/10.1016/10.1109/TGRS.2008.2008026.
   Google Scholar
• Suzuki S., Osawa Y., Hatooka Y., Kankaku Y., Watanabe T. (2009)—Overview of Japan's Advanced Land Observing Satellite-2 mission. Proceedings SPIE 7474, Sensors, Systems, and Next-Generation Satellites XIII, 74740Q, Berlin, Germany. doi: http://dx.doi.org/10.1016/10.1117/12.831340.
   Google Scholar
• Taconet O., Benallegue M., Vidal-Madjar D., Prevot L., Dechambre M., Normand M. (1994) -Estimation of soil and crop parameters for wheat from airborne radar backscattering data in C and X bands. Remote Sensing of Environment, 50: 287–294. doi: http://dx.doi.org/10.1016/10.1016/0034-4257(94)90078-7.
   Web of Science ®Google Scholar
• Torres R., Snoeij P., Geudtner D., Bibby D., Davidson M., Attema E., Potin P., Rommen B., Floury N., Brown M., Navas Traver I., Deghaye P., Duesmann B., Rosich B., Miranda N., Bruno C., L'Abbate M., Croci R., Pietropaolo A., Huchler M., Rostan F. (2012) -GMES Sentinel-1 mission. Remote Sensing of Environment, 120: 9–24. doi: http://dx.doi.org/10.1016/10.1016/j.rse.2011.05.028.
   Web of Science ®Google Scholar
• Walker J.P., Houser P.R. (2004)—Requirements of a global near-surface soil moisture satellite 1129 mission: accuracy, repeat time, and spatial resolution. Advances in Water Resources, 27: 785–801. doi: http://dx.doi.org/10.1016/10.1016/j.advwatres.2004.05.006.
   Web of Science ®Google Scholar
• Werninghaus R., Buckreuss S. (2010) -The TerraSAR-X Mission and System Design. IEEE Transactions on Geoscience and Remote Sensing, 48 (2): 606–614. doi: http://dx.doi.org/10.1016/10.1109/TGRS.2009.2031062.
   Google Scholar
• Wickel A.J., Jackson T.J., Wood. E.F. (2001)—Multitemporal monitoring of soil moisture with RADARSAT SAR during the 1997 Southern Great Plains hydrology experiment. International Journal of Remote Sensing, 22 (8): 1571–1583. doi: http://dx.doi.org/10.1016/10.1080/01431160120291.
   Web of Science ®Google Scholar