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Barber, M.; Grings, F.; Perna, P.; Piscitelli, M.; Maas, M.; Bruscantini, C.; Jacobo-Berlles, J.; Karszenbaum, H. "Speckle noise and soil heterogeneities as error sources in a bayesian soil moisture retrieval scheme for SAR data" (2012) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 5(3):942-951
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Abstract:

Soil moisture retrieval from SAR images is always affected by speckle noise and uncertainties associated to soil parameters, which impact negatively on the accuracy of soil moisture estimates. In this paper a soil moisture Bayesian estimator from polarimetric SAR images is proposed to address these issues. This estimator is based on a set of statistical distributions derived for the polarimetric soil backscattering coefficients, which naturally includes models for the soil scattering, the speckle and the soil spatial heterogeneity. As a natural advantage of the Bayesian approach, prior information about soil condition can be easily included, enhancing the performance of the retrieval. The Oh's model is used as scattering model, although it presents a limiting range of validity for the retrieval of soil moisture. After fully stating the mathematical modeling, numerical simulations are presented. First, traditional minimization-based retrieval is investigated. Then, it is compared with the Bayesian retrieval scheme. The results indicate that the Bayesian model enlarges the validity region of the minimization-based procedure. Moreover, as speckle effects are reduced by multilooking, Bayesian retrieval approaches the minimization-based retrieval. On the other hand, when speckle effects are large, an improvement in the accuracy of the retrieval is achieved by using a precise prior. The proposed algorithm can be applied to investigate which are the optimum parameters regarding multilooking process and prior information required to perform a precise retrieval in a given soil condition. © 2012 IEEE.

Registro:

Documento: Artículo
Título:Speckle noise and soil heterogeneities as error sources in a bayesian soil moisture retrieval scheme for SAR data
Autor:Barber, M.; Grings, F.; Perna, P.; Piscitelli, M.; Maas, M.; Bruscantini, C.; Jacobo-Berlles, J.; Karszenbaum, H.
Filiación:Instituto de Astronomía y Física Del Espacio (IAFE), Buenos Aires, Argentina
Cátedra de Conservación y Manejo de Suelos, Facultad de Agronomía, Centro de la Pcia. de Buenos Aires (UNICEN), Buenos Aires, Argentina
Departamento de Computación, Facultad de Ciencias Exactas y Naturales (FCEN), Universidad de Buenos Aires (UBA), Buenos Aires, Argentina
Palabras clave:Bayesian methods; inverse problems; radar applications; soil moisture; synthetic aperture radar; Backscattering coefficients; Bayesian approaches; Bayesian estimators; Bayesian methods; Bayesian model; Bayesian retrieval; Error sources; Mathematical modeling; Multilooking; Optimum parameters; Polarimetric SAR; Prior information; Radar applications; SAR data; SAR Images; Scattering model; Soil conditions; Soil heterogeneity; Soil moisture retrievals; Soil parameters; Spatial heterogeneity; Speckle effects; Speckle noise; Statistical distribution; Algorithms; Bayesian networks; Computer simulation; Estimation; Inverse problems; Polarimeters; Soil moisture; Speckle; Synthetic aperture radar; Uncertainty analysis; Geologic models; accuracy assessment; algorithm; backscatter; Bayesian analysis; error analysis; heterogeneity; inverse problem; noise; numerical model; soil moisture; statistical distribution; synthetic aperture radar
Año:2012
Volumen:5
Número:3
Página de inicio:942
Página de fin:951
DOI: http://dx.doi.org/10.1109/JSTARS.2012.2191266
Título revista:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Título revista abreviado:IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.
ISSN:19391404
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19391404_v5_n3_p942_Barber

Referencias:

  • Kerr, Y.H., Soil moisture from space: Where are we? (2007) Hydrogeology Journal, 15 (1), pp. 117-120. , DOI 10.1007/s10040-006-0095-3, Remote Sensing and GIS in Hydrogeology
  • Ulaby, F.T., Moore, R.K., Fung, A.K., (1982) Microwave Remote Sensing: Active and Passive. Radar Remote Sensing and Surface Scattering and Emission Theory, 2. , Boston, MA: Addison-Wesley
  • Oliver, C., Quegan, S., (2004) Understanding Synthetic Aperture Radar Images, , New York: SciTech Publishing
  • Fung, A.K., (1994) Microwave Scattering and Emission Models and Their Applications, , Boston, MA: Artech House
  • Western, A.W., Grayson, R.B., Bloschl, G., Willgoose, G.R., McMahon, T.A., Observed spatial organization of soil moisture and its relation to terrain indices (1999) Water Resources Research, 35 (3), pp. 797-810. , DOI 10.1029/1998WR900065
  • Verhoest, N.E.C., Lievens, H., Wagner, W., Alvarez-Mozos, J., Moran, M.S., Mattia, F., On the soil roughness parameterization problem in soil moisture retrieval of bare surfaces from synthetic aperture radar (2008) Sensors, 8, pp. 4213-4248. , Jul
  • Satalino, G., Mattia, F., Davidson, M.W.J., Le Toan, T., Pasquariello, G., Borgeaud, M., On current limits of soil moisture retrieval from ers-sar data (2002) IEEE Trans. Geosci. Remote Sens., 40 (11), pp. 2438-2447. , Nov
  • Lee, J.S., Hoppel, K.W., Mango, S.A., Miller, A.R., Intensity and phase statistics of multilook polarimetric and interferometric sar imagery (1994) IEEE Trans. Geosci. Remote Sens., 32 (5), pp. 1017-1028. , Sep
  • Lee, J.S., Wen, J.-H., Ainsworth, T.L., Chen, K.-S., Chen, A.J., Improved sigma filter for speckle filtering of sar imagery (2009) IEEE Trans. Geosci. Remote Sens., 47 (1), pp. 202-213. , Jan
  • Lopez-Martinez, C., Hajnsek, I., Lee, J.-S., Pottier, E., Fabregas, X., Polarimetric speckle noise effects in quantitative physical parameters retrieval (2006) IEE Proceedings: Radar, Sonar and Navigation, 153 (3), pp. 250-259. , DOI 10.1049/ip-rsn:20045102
  • Hajnsek, I., Pottier, E., Cloude, S.R., Inversion of surface parameters from polarimetric sar (2003) IEEE Trans. Geosci. Remote Sens., 41 (4), pp. 727-744. , Apr
  • Balenzano, A., Mattia, F., Satalino, G., Davidson, M.W.J., Dense temporal series of c- and l-band sar data for soil moisture retrieval over agricultural crops (2011) IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. (JSTARS), 4 (2), pp. 439-450. , Jun
  • Mattia, F., Satalino, G., Pauwels, V.R.N., Loew, A., Soil moisture retrieval through a merging of multi-Temporal l-band sar data and hydrologic modelling (2009) Hydrol. Earth Syst. Sci., 13 (3), pp. 343-356
  • Kim, Y., Van Zyl, J.J., A time-series approach to estimate soilmoisture using polarimetric radar data (2009) IEEE Trans. Geosci. Remote Sens., 47 (8), pp. 2519-2527. , Aug
  • Verhoest, N.E.C., De Baets, B., Mattia, F., Satalino, G., Lucau, C., Defourny, P.A., A possibilistic approach to soil moisture retrieval from ers synthetic aperture radar backscattering under soil roughness uncertainty (2007) Water Resources Research, 43 (7), pp. W07435
  • Vernieuwe, H., Verhoest, N.E.C., Lievens, H., De Baets, B., Possibilistic soil roughness identification for uncertainty reduction on sarretrieved soil moisture (2011) IEEE Trans. Geosci. Remote Sens., 49 (2), pp. 628-638. , Feb
  • Oh, Y., Sarabandi, K., Ulaby, F.T., An empirical model and an inversion technique for radar scattering from bare soil surfaces (1992) IEEE Trans. Geosci. Remote Sens., 30 (2), pp. 370-381. , Mar
  • Dubois, P.C., Van Zyl, J., Engman, T., Measuring soil moisture with imaging radars (1995) IEEE Trans. Geosci. Remote Sens., 33 (4), pp. 915-926. , Jul
  • Oh, Y., Quantitative retrieval of soil moisture content and surface roughness from multipolarized radar observations of bare soil surfaces (2004) IEEE Trans. Geosci. Remote Sens., 42 (3), pp. 596-601. , Mar
  • Haddad, Z.S., Dubois, P., Van Zyl, J.J., Bayesian estimation of soil parameters from radar backscatter data (1996) IEEE Transactions on Geoscience and Remote Sensing, 34 (1), pp. 76-82. , PII S0196289296002793
  • Notarnicola, C., Posa, F., Bayesian algorithm for the estimation of the dielectric constant from active and passive remotely sensed data (2004) IEEE Geosci. Remote Sens. Lett., 1 (3), pp. 179-183. , Jul
  • Mattia, F., Satalino, G., Dente, L., Pasquariello, G., Using a priori information to improve soil moisture retrieval from envisat asar ap data in semiarid regions (2006) IEEE Trans. Geosci. Remote Sens., 44 (4), pp. 900-912. , Apr
  • Cloude, S.R., Pettier, E., A review of target decomposition theorems in radar polarimetry (1996) IEEE Transactions on Geoscience and Remote Sensing, 34 (2), pp. 498-518. , PII S0196289296010030
  • Tarantola, A., (2005) Inverse Problem Theory and Methods for Model Parameter Estimation, , Philadelphia, PA: Society for Industrial and Applied Mathematics (SIAM)
  • Vogel, C.R., (2002) Computational Methods for Inverse Problems, , Philadelphia, PA, USA: Society for Industrial and Applied Mathematics (SIAM)
  • Chen, K.S., Wu, T.-D., Tsang, L., Li, Q., Shi, J., Fung, A.K., Emission of rough surfaces calculated by the integral equation method with comparison to three-dimensional moment method simulations (2003) IEEE Trans. Geosci. Remote Sens., 41 (1), pp. 90-101. , Jan
  • Fung, A.K., Chen, K.S., An update on the iem surface backscattering model (2004) IEEE Geosci. Remote Sens. Lett., 1 (2), pp. 75-77. , Apr
  • Song, K., Zhou, X., Fan, Y., Empirically adopted iem for retrieval of soil moisture from radar backscattering coefficients (2009) IEEE Trans. Geosci. Remote Sens., 47 (6), pp. 1662-1672. , Jun
  • Merzouki, A., McNairn, H., Pacheco, A., Mapping soil moisture using radarsat-2 data and local autocorrelation statistics (2011) IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. (JSTARS), 4 (1), pp. 128-137. , Mar
  • Callens, M., Verhoest, N.E.C., Davidson, M.W.J., Parameterization of tillage-induced single-scale soil roughness from 4-m profiles (2006) IEEE Trans. Geosci. Remote Sens., 44 (4), pp. 878-888. , Mar
  • MacKay, D.J.C., (2003) Information Theory, Inference, and Learning Algorithms, , Cambridge, UK: Cambridge University Press
  • Western, A.W., Blöschl, G., On the spatial scaling of soilmoisture (1999) J. Hydrol., 217 (3-4), pp. 203-224
  • Jackson, T.J., First order surface roughness correction of active microwave observations for estimating soil moisture (1997) IEEE Transactions on Geoscience and Remote Sensing, 35 (4), pp. 1065-1069. , PII S0196289297034621
  • Wasserman, L., (2004) All of Statistics: A Concise Course in Statistical Inference, , New York: Springer

Citas:

---------- APA ----------
Barber, M., Grings, F., Perna, P., Piscitelli, M., Maas, M., Bruscantini, C., Jacobo-Berlles, J.,..., Karszenbaum, H. (2012) . Speckle noise and soil heterogeneities as error sources in a bayesian soil moisture retrieval scheme for SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5(3), 942-951.
http://dx.doi.org/10.1109/JSTARS.2012.2191266
---------- CHICAGO ----------
Barber, M., Grings, F., Perna, P., Piscitelli, M., Maas, M., Bruscantini, C., et al. "Speckle noise and soil heterogeneities as error sources in a bayesian soil moisture retrieval scheme for SAR data" . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5, no. 3 (2012) : 942-951.
http://dx.doi.org/10.1109/JSTARS.2012.2191266
---------- MLA ----------
Barber, M., Grings, F., Perna, P., Piscitelli, M., Maas, M., Bruscantini, C., et al. "Speckle noise and soil heterogeneities as error sources in a bayesian soil moisture retrieval scheme for SAR data" . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 3, 2012, pp. 942-951.
http://dx.doi.org/10.1109/JSTARS.2012.2191266
---------- VANCOUVER ----------
Barber, M., Grings, F., Perna, P., Piscitelli, M., Maas, M., Bruscantini, C., et al. Speckle noise and soil heterogeneities as error sources in a bayesian soil moisture retrieval scheme for SAR data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2012;5(3):942-951.
http://dx.doi.org/10.1109/JSTARS.2012.2191266