A sequential Bayesian procedure for integrating heterogeneous remotely sensed data for irrigation management

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 8531, Issue , 2012, Pages

  Addesso, Paolo ^a   Conte, Roberto ^a   Longo, Maurizio ^a   Restaino, Rocco ^a   Vivone, Gemine ^a  

^a UNIVERSITY OF SALERNO   (Italy)

Author keywords

Bayesian Filtering; Brightness Temperature; Irrigation Management; Kalman Filtering; Multisensor Data Fusion; Multitemporal Analysis; Thermal Sharpening; Wavelet Decomposition

Indexed keywords

BAYESIAN FILTERING; BRIGHTNESS TEMPERATURES; IRRIGATION MANAGEMENT; KALMAN-FILTERING; MULTI-TEMPORAL ANALYSIS; MULTISENSOR DATA FUSION; THERMAL SHARPENING;

ATMOSPHERIC TEMPERATURE; ECOSYSTEMS; HYDROLOGY; IRRIGATION; REMOTE SENSING; WATER SUPPLY; WAVELET DECOMPOSITION;

DATA INTEGRATION;

EID: 84880283681     PISSN: 0277786X     EISSN: 1996756X     Source Type: Conference Proceeding    
DOI: 10.1117/12.974659     Document Type: Conference Paper

References (16)

1. P. Addesso, R. Conte, M. Longo, R. Restaino, and G. Vivone. MAP-MRF cloud detection based on phd filtering. IEEE J. Sel. Topics Appl. Earth Observ., 5(3):919-929, June 2012.
2. N. Agam, W.P. Kustas, M.C. Anderson, F. Li, and P.D. Colaizzi. Utility of thermal image sharpening for monitoring field-scale evapotranspiration over rainfed and irrigated agricultural regions. Geophys. Res. Lett., 35:L02402, 2008.
3. N. Agam, W.P. Kustas, M.C. Anderson, F. Li, and C.M.U. Neale. A vegetation index based technique for spatial sharpening of thermal imagery. Remote Sensing of Environment, 107:545-558, 2007.
4. I. Amro, J. Mateos, M. Vega, R. Molina, and A.K. Katsaggelos. A survey of classical methods and new trends in pansharpening of multispectral images. EURASIP Journal on Advances in Signal Processing, (79):1-22, Sep 2011.
5. F. Baroncini, F. Castelli, F. Caparrini, and S. Ruffo. A dynamic cloud masking and filtering algorithm for msg retrieval of land surface temperature. International Journal of Remote Sensing, 29(12):3365-3382, 2008.
6. P.R Houser, G.J.M. De Lannoy, and J.P. Walker. Land surface data assimilation. In W. Lahoz, B. Khattatov, and R. Ménard, editors, Data Assimilation. Making Sense of Observations, pages 549-597. Academic Press, 2010.
7. P.L. Houtekamer and H.L. Mitchell. Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev., 126(3):796-811, Mar 1998.
8. J.-C. Jimenez-Munoz and J.A. Sobrino. Split-window coefficients for land surface temperature retrieval from low-resolution thermal infrared sensors. Geoscience and Remote Sensing Letters, IEEE, 5(4):806-809, Oct 2008.
9. R.E. Kalman. A new approach to linear filtering and prediction problems. J. Basic Eng.-T ASME, 82(1):35-45, 1960.
10. R.P.S. Mahler. Statistical Multisource-Multitarget Information Fusion. Artech House, 2007.
11. J. Nunez, X. Otazu, O. Fors, A. Prades, V. Pala, and R. Arbiol. Multiresolution-based image fusion with additive wavelet decomposition. IEEE Trans. Geosci. Remote Sens., 37(3):1204-1211, May 1999.
12. R. Rivas and V. Caselles. A simplified equation to estimate spatial reference evaporation from remote sensing-based surface temperature and local meteorological data. Remote Sensing of Environment, 93(1-2):68-76, 2004.
13. H.L. Van Trees. Detection, Estimation and Modulation Theory, Part I. Detection, Estimation and Linear Modulation Theory. John Wiley & Sons, 2001.
14. Z. Wan and J. Dozier. A generalized split-window algorithm for retrieving land-surface temperature from space. Geoscience and Remote Sensing, IEEE Transactions on, 34(4):892-905, Jul 1996.
15. K. Wang and R.E. Dickinson. A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability. Rev. Geophys., 50:RG2005, May 2012.
16. C.K. Wikle and L.M. Berliner. A Bayesian tutorial for data assimilation. Physica D, 230(1-2):1-16, Jun 2007.