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Application of multi-window maximum cross-correlation to the mediterranean sea circulation by using MODIS data

Bartolomeo Doronzo, Stefano Taddei, Carlo Brandini

Article ID: 191
Vol 2, Issue 1, 2017, Article identifier:10-25

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Abstract

In a previous study an improved Maximum Cross-Correlation technique, called Multi-Window Maximum Cross-Correlation (MW-MCC), was proposed, and applied to noise-free synthetic images in order to show its potential and limits in oceanographic applications. In this work, instead, the application of MW-MCC to high resolution MODIS images, and its capability to provide useful and realistic results for ocean currents, is studied. When applied to real satellite images, the MW-MCC is subject to cloud cover and image quality problems. As a consequence the number of useful MODIS images is greatly reduced. However, for every MODIS image, multiple spec-tral bands are available, and it is possible to apply the MW-MCC algorithm to the same scene as many times as the number of these bands, increasing the possibility of finding valid current vectors. Moreover, the comparison among the results from different spectral bands allows to verify both the consistency of the computed current vectors and the validity of using a spectral band as a good tracer for the ocean circulation. Due to the lack of systematic current measurements in the area considered, it has been not possible to perform an ex-tensive error analysis of the MW-MCC results, although a case study of a comparison between HF radar measurements and MW-MCC data is shown. Moreover, some comparison between numerical ocean model simulations and MW-MCC results are also shown. The coherence of the resulting circulation flow, the high number of current vectors found, the agreement among different spectral bands, and conformity with the currents measured by the HF radars or simulated by hydrodynamic models show the validity of the technique.

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References

Al-Amri S S, Kalyankar N V and Khamitkar S D. (2010). A comparative study of removal noise from remote sensing image. International Journal of Computer Science, 7(1): 32–36.

Alexanin A I, Katamanov S N and Epstein Yu S. (2005). Problems of accurate automatic navigation of NOAA/AVHRR and FY-1D satellite images: Proceedings, 31st International Symposium on Remote Sensing of Environment: Global Monitoring for Sustainability and Security, June: 20–24.

Algazi V R and Ford G E. (1981). Radiometric equalization of nonperiodic striping in satellite data, Computer Graphics and Image Processing, 16 (3):287–295 http://dx.doi/10.1016/0146-664X(81)90041-1.

Antonelli P, di Bisceglie M, Episcopo R. (2004). Destriping MODIS data using IFOV overlapping, Geoscience and Remote Sensing Symposium, IGARSS '04. Proceedings IEEE International, 7. http://dx.doi/10.1109/IGARSS.2004.1370171.

Barton I J. (2002). Ocean currents from successive satellite images: The reciprocal filtering technique. Journal of Atmospheric and Oceanic Technology, 19: 1677–1689. https://dx.doi.org/10.1175/1520-0426(2002)019<1677:OCFSSI>2.0.CO;2.

Bouali M. (2010). A simple and robust destriping algorithm for imaging spectrometers: application to MODIS data, ASPRS 2010 Annual Conference San Diego.

Bowen M M, Emery W J, Wilkin J L, et al. (2002). Extracting multiyear surface currents from sequential thermal imagery using the maximum cross-correlation technique. Journal of Atmospheric and Oceanic Technology, 19 (10): 1665–1676. https://dx.doi.org/10.1175/1520-0426(2002)019<1665:EMSCFS>2.0.CO;2.

Breaker L C, Krasnopolsky V M, Rao D B, et al. (1994). The feasibility of estimating ocean surface currents on an operational basis using satellite feature tracking methods. Bulletin of American Meteorological Society, 75: 2085–2094. https://dx.doi.org/10.1175/1520-0477(1994)075<2085:TFOEOS>2.0.CO;2.

Carvalho Jr O A, Correia da Silva N, Ferreira de Carvalho A P, et al. (2012). Combining noise-adjusted principal components transform and median filter techniques for denoising MODIS temporal signatures. Revista Brasileira de Geofısica, 30(2): 147–157. http://dx.doi.org/10.1590/rbgf.v30i2.88.

Chen J, Shao Y, Guo H, et al. (2003). Destriping CMODIS data by power filtering. IEEE Transactions On Geoscienceand Remote Sensing, 41(9): 2119–2124. https://dx.doi.org/10.1109/TGRS.2003.817206.

Crippen R E. (1989). A simple spatial filtering routine for the cosmetic removal of scan line noise from Landsat TM P-tape imagery. Photogrammetric Engineering & Remote Sensing, 55(3): 327–331.

Crocker R I, Emery W J, Matthews D K, et al. (2007). Computing coastal ocean surface currents from infrared and ocean color satellite imagery. IEEE Transactions On Geoscience and Remote Sensing, 45(2): 435–447. https://dx.doi.org/10.1109/TGRS.2006.883461.

Di Bisceglie M, Episcopo R, Galdi C, et al. (2009). Destriping MODIS data using overlapping field-of-view method. IEEE Transactions On Geoscience and Remote Sensing, 47(2): 637–651. https://dx.doi.org/10.1109/TGRS.2008.2004034.

Doronzo B, Taddei S, Brandini C, et al. (2015). Extensive analysis of potentialities and limitations of a mum cross-correlation technique for surface circulation by using realistic ocean model simulations. Ocean Dynamics, 65(8): 1183–1198. https://dx.doi.org/10.1007/s10236-015-0859-1.

Emery W J, Thomas A C, Collins M J, et al. (1986). An objective method for computing advective surface velocities from sequential infrared satellite images. Journal of Geophysics Research, vol.91: 12865–12878. https://dx.doi.org/10.1029/JC091iC11p12865.

Emery W J, Baldwin D and Matthews D K.(2003). Maximum cross correlation automatic satellite image navigation and attitude corrections for open ocean image navigation, IEEE Trans. Geosci. Remote Sens. 41: 33–42.

http://dx.doi.org/10.1109/TGRS.2002.808061.

Esaias W E, Abbott M A, Barton I, et al. (1998). An overview of MODIS capabilities for ocean science observations. IEEE Transactions On Geoscience and Remote Sensing, 36: 1250–1265. https://dx.doi.org/10.1109/36.701076.

Garcia C A E and Robinson I S. (1989). Sea surface velocities in shallow seas extracted from sequential Coastal Zone Color Scanner satellite data. Journal of Geophysics Research, 94: 12681–12691. https://dx.doi.org/10.1029/JC094iC09p12681.

Gonzales R C and Woods R E. (2002). Digital Image Processing, Prentice Hall.

Gumley L, Frey R and Moeller C. (2005). Destriping of MODIS L1B 1KM Data for Collection 5 Atmosphere Algorithms, MODIS Meetings - Poster Session. Retrieved from https://modis.gsfc.nasa.gov/sci_team/meetings/200503/posters/atmos/gumley1.pdf

Gumley L. (2002). Proceedings MODIS Workshop, URL: Western Autralian Satellite Technology and Applications Consortium. Nov. 26–29. Retrieved from http://www.wastac.wa.gov.au/modis_workshop_2002/Lecture_3_Scanner_Characteristics_Image_Artifacts_Destriping.ppt

Horn B K P and Woodham R J. (1979). Destriping Landsat MSS images by histogram modification. Computer Graphics and Image Processing, 10: 69–83. https://dx.doi.org/10.1016/0146-664X(79)90035-2.

Huang H L, Gumley L E, Strabala K, et al. (2004). International MODIS and AIRS Processing Package (IMAPP): A Direct Broadcast Software Package for the NASA Earth Ob-serving System. Bulletin of the American Meteorological Society, 85: 159–161. https://dx.doi.org/10.1175/BAMS-85-2-159.

Istituto Idrografico della Marina, (1982). Atlante delle correnti superficiali dei mari italiani, Istituto Idrografico della Marina, Genova.

Justice C O, Townshend J R G, Vermote E F, et al. (2002). An overview of MODIS land data processing and product status. Remote Sensing of Environment, 83: 3–15. https://dx.doi.org/10.1016/S0034-4257(02)00084-6.

Kamachi M. (1989). Advective surface velocities derived from sequential images for rotational flow field: Limitations and applications of Maximum Cross Correlation method with rotational registration. Journal of Geophysical Research, 94(C12): 18227–18233. https://dx.doi.org/10.1029/JC094iC12p18227.

Kay S, Hedley J D and Lavender S. (2009). Sun glint correction of high and low spatial resolution images of aquatic scenes: A review of methods for visible and near-infrared wavelengths. Remote Sensing, 1(4): 697–730. https://dx.doi.org/10.3390/rs1040697.

Marcello J, Eugenio F, Marqués F, et al. (2008). Motion estimation techniques to automatically track oceanographic thermal structures in multisensor image sequences. IEEE Transactions On Geoscience and Remote Sensing, 46(9): 2743–2762. https://dx.doi.org/10.1109/TGRS.2008.919274.

Matthews D K and Emery W J. (2009). Velocity observations of the California Current derived from satellite imagery. Journal of Geophysics Research, 114(C8). https://dx.doi.org/10.1029/2008JC005029..

Mikelsons K, Wang M, Jiang L, et al. (2014). Destriping algorithm for improved satellite-derived ocean color product imagery. Optics Express, 22(23): 28058–28070. https://dx.doi.org/10.1364/OE.22.028058.

Millot C. (1999). Circulation in the Western Mediterranean Sea. Journal of Marine Systems, 20(1–4): 423–442. https://dx.doi.org/10.1016/S0924-7963(98)00078-5.

Minnett P J and Barton I J. (2009). Remote sensing of the earth’s surface temperature, In Radiometric Temperature Measurements II. Applications. In Z M Zhang, B K Tsai, and G Machin (Eds), Experimental Methods in the Physi-cal Sciences, vol.43, Academic Press/Elsevier, 333–391.

Notarstefano G, Poulain P and Mauri E. (2008). Estimation of surface currents in the Adriatic Sea from sequential infra-red satellite images. Journal of Atmospheric and Oceanographic Technology, 25: 271–285. https://dx.doi.org/10.1175/2007JTECHO527.1.

Pan J J and Chang C I. (1992). Destriping of Landsat MSS images by filtering techniques, Photogrammetric Engineering & Remote Sensing, 58(10): 1417–1423.

Prasad J S, Reajawat A S, Pradhan Y, et al. (2002). Retrieval of sea surface velocities using sequential ocean color monitor data. Proceedings of Indian Academy of Sciences, Earth and Planetary Sciences, 111(3): 189–195. http://dx.doi.org/10.1007/BF02701965.

Rainey K and Hallenborg E. (2013). Characterization of Sun Glitter Statistics in Ocean Video, SSC Pacific, San Diego, CA, Tech. Rep. 2031.

Rakwatin P, Takeuchi W and Yasuoka Y. (2007). Stripe noise reduction in MODIS data by combining histogram matching with facet filter. IEEE Transactions On Geoscience and Remote Sensing, 45(6): 1844–1856. https://doi.org/10.1109/TGRS.2007.895841.

Schroeder K. Haza A C, Griffa A, et al. (2011). Relative dispersion in the Liguro-Provencal basin: From sub-mesoscale to mesoscale. Deep Sea Research Part I: Oceanographic Re-search Papers, 58: 209–228. https://dx.doi.org/10.1016/j.dsr.2010.11.004.

Shao Y, Taff G N and Lunetta R S. (2011). A review of selected moderate-resolution imaging spectroradiometer algorithms, data products, and applications. In: Q. Weng (ed.), Advances in Remote Sensing — Chapter 2: 31–55. Boca Ra-ton, Florida: CRC Press LLC. https://dx.doi.org/10.1201/b10599-4.

Shchepetkin A F and McWilliams J C. (2005). The Regional Ocean Modeling System: A split-explicit, free-surface, topography following coordinates ocean model. Ocean Modelling, 9(4): 347–404. https://dx.doi.org/10.1016/j.ocemod.2004.08.002.

Simpson J J and Yhann S R. (1994). Reduction of noise in AVHRR channel 3 data with minimum distortion. IEEE Transactions On Geoscience and Remote Sensing, 32 (2): 315–328. https://dx.doi.org/10.1109/36.295047.

Simpson J J, Gobat J I and Frouin R. (1995). Improved destriping of GOES images using finite impulse response filters. Remote Sensing of Environment, 52(1): 15–35. https://dx.doi.org/10.1016/0034-4257(94)00078-2.

Simpson J J, Stitt J R and Leath D M. (1998). Improved finite impulse response filters for enhanced destriping of geostationary satellite data. Remote Sensing of Environment, 66(3): 235–249. https://dx.doi.org/10.1016/S0034-4257(98)00070-4.

Srinivasan R, Cannon M and White J. (1988). Landsat data destriping using power spectral filtering, Optical Engineering, 27(11): 939–943. https://dx.doi.org/10.1117/12.7976791.

Wahl D D and Simpson J J. (1990). Physical processes affecting the objective determination of near-surface velocity from satellite data. Journal of Geophysical Research, 95: 13511–13619. https://dx.doi.org/10.1029/JC095iC08p13511.

Weinreb M P, Xie R, Lienesch J H, et al. (1989). Destriping GOES images by matching empirical distribution functions. Remote Sensing of Environment, 29(2): 185–195. https://dx.doi.org/10.1016/0034-4257(89)90026-6.

Zavialov P O, Grigorieva J V, Moller O O Jr, et al. (2002). Continuity preserving modified maximum cross-correla-tion technique. Journal of Geophysical Research, 94 (C10): 24-1–24-10. https://dx.doi.org/10.1029/2001JC001116.


DOI: http://dx.doi.org/10.18063/SOM.2017.01.002
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