Academic literature on the topic 'Ocean bottom – Remote-sensing maps'
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Journal articles on the topic "Ocean bottom – Remote-sensing maps"
Frezzotti, Massimo. "Glaciological study in Terra Nova Bay, Antarctica, inferred from remote sensing analysis." Annals of Glaciology 17 (1993): 63–71. http://dx.doi.org/10.1017/s0260305500012623.
Full textFrezzotti, Massimo. "Glaciological study in Terra Nova Bay, Antarctica, inferred from remote sensing analysis." Annals of Glaciology 17 (1993): 63–71. http://dx.doi.org/10.3189/s0260305500012623.
Full textArnold, S. R., D. V. Spracklen, J. Williams, N. Yassaa, J. Sciare, B. Bonsang, V. Gros, et al. "Evaluation of the global oceanic isoprene source and its impacts on marine organic carbon aerosol." Atmospheric Chemistry and Physics Discussions 8, no. 4 (August 27, 2008): 16445–71. http://dx.doi.org/10.5194/acpd-8-16445-2008.
Full textde Lavergne, Casimir, Gurvan Madec, Julien Le Sommer, A. J. George Nurser, and Alberto C. Naveira Garabato. "On the Consumption of Antarctic Bottom Water in the Abyssal Ocean." Journal of Physical Oceanography 46, no. 2 (February 2016): 635–61. http://dx.doi.org/10.1175/jpo-d-14-0201.1.
Full textHofmann, Andreas F., Peter M. Walz, Hans Thomas, Edward T. Peltzer, and Peter G. Brewer. "High-Resolution Topography-Following Chemical Mapping of Ocean Hypoxia by Use of an Autonomous Underwater Vehicle: The Santa Monica Basin Example." Journal of Atmospheric and Oceanic Technology 30, no. 11 (November 1, 2013): 2630–46. http://dx.doi.org/10.1175/jtech-d-12-00249.1.
Full textSpecht, Cezary, Emilian Świtalski, and Mariusz Specht. "Application of an Autonomous/Unmanned Survey Vessel (ASV/USV) in Bathymetric Measurements." Polish Maritime Research 24, no. 3 (September 1, 2017): 36–44. http://dx.doi.org/10.1515/pomr-2017-0088.
Full textWason, Haneet, Felix Oghenekohwo, and Felix J. Herrmann. "Low-cost time-lapse seismic with distributed compressive sensing — Part 2: Impact on repeatability." GEOPHYSICS 82, no. 3 (May 1, 2017): P15—P30. http://dx.doi.org/10.1190/geo2016-0252.1.
Full textBunchuk, A. V., and A. N. Ivakin. "Remote acoustic sensing of manganese nodules on the ocean bottom." Journal of the Acoustical Society of America 95, no. 5 (May 1994): 2802–3. http://dx.doi.org/10.1121/1.409758.
Full textGreene, Chad A., and Preston S. Wilson. "Toward passive acoustic remote sensing of ocean‐bottom gas seeps." Journal of the Acoustical Society of America 127, no. 3 (March 2010): 1938. http://dx.doi.org/10.1121/1.3384877.
Full textReichstetter, Martina, Peter Fearns, Scarla Weeks, Lachlan McKinna, Chris Roelfsema, and Miles Furnas. "Bottom Reflectance in Ocean Color Satellite Remote Sensing for Coral Reef Environments." Remote Sensing 7, no. 12 (December 9, 2015): 16756–77. http://dx.doi.org/10.3390/rs71215852.
Full textDissertations / Theses on the topic "Ocean bottom – Remote-sensing maps"
Baxter, Katrina. "Linking seafloor mapping and ecological models to improve classification of marine habitats : opportunities and lessons learnt in the Recherche Archipelago, Western Australia." University of Western Australia. School of Plant Biology, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0181.
Full textUmbert, Ceresuela Marta. "Exploiting the multiscale synergy among ocean variables : application to the improvement of remote sensing salinity maps." Doctoral thesis, Universitat Politècnica de Catalunya, 2015. http://hdl.handle.net/10803/321115.
Full textRemote sensing imagery of the ocean surface provides a synoptic view of the complex geometry of ocean circulation, which is dominated by mesoscale variability. The signature of filaments and vortices is present in different ocean scalars advected by the oceanic flow. The most probable origin of the observed structures is the turbulent character of ocean currents, and those signatures are persistent over time scales compatible with ocean mesoscale dynamics. At spatial scales of kilometers or more, turbulence is mainly 2D, and a complex geometry, full of filaments and eddies of different sizes, emerges in remote sensing images of surface chlorophyll-a concentration and surface salinity, as well as in other scalars acquired with higher quality such as surface temperature and absolute dynamic topography. The aim of this thesis is to explore and apply mapping methodologies to improve the quality of remote sensing maps in general, but focusing in the case of remotely sensed sea surface salinity (SSS) data. The different methodologies studied in this thesis have been applied with the specific goal of improving surface salinity maps generated from data acquired by the European Space Agency's mission SMOS, the first satellite able to measure soil moisture and ocean salinity from space at a global scale. The first part of this thesis will introduce the characteristics of the operational SMOS Level 2 (L2) SSS products and the classical approaches to produce the best possible SSS maps at Level 3 (L3), namely data filtering, weighted average and Optimal Interpolation. In the course of our research we will obtain a set of recommendations about how to process SMOS data starting from L2 data. A fusion technique designed to exploit the common turbulent signatures between different ocean variables is also explored in this thesis, in what represents a step forward from L3 to Level 4 (L4). This fusion technique is theoretically based on the geometrical properties of advected tracers. Due to the effect of the strong shear in turbulent flows, the spatial structure of tracers inherit some properties of the underlying flow and, in particular, its geometrical arrangement. As a consequence, different ocean variables exhibit scaling properties, similar to the turbulent energy cascade. The fusion method takes a signal affected by noise, data gaps and/or low resolution, and improves it in a geophysically meaningful way. This signal improvement is achieved by using an appropriate data, which is another ocean variable acquired with higher quality, greater spatial coverage and/or finer resolution. A key point in this approach is the assumption of the existence of a multifractal structure in ocean images, and that singularity lines of the different ocean variables coincide. Under these assumptions, the horizontal gradients of both variables, signal and template, can be related by a smooth matrix. The first, simplest approach to exploit such an hypothesis assumes that the relating matrix is proportional to the identity, leading to a local regression scheme. As shown in the thesis, this simple approach allows reducing the error and improving the coverage of the resulting Level 4 product; Moreover, information about the statistical relationship between the two fields is obtained since the functional dependence between signal and template is determined at each point.
Siemes, Kerstin. "Establishing a sea bottom model by applying a multi-sensor acoustic remote sensing approach." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209381.
Full textChapters 4 and 5 are adapted from published work, with permission:
DOI:10.1121/1.3569718 (link: http://asadl.org/jasa/resource/1/jasman/v129/i5/p2878_s1) and
DOI:10.1109/JOE.2010.2066711 (link: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=5618582&queryText%3Dsiemes)
In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of the Université libre de Bruxelles' products or services.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished
Nguyen, Phu Duy. "Physics Based Approach for Seafloor Classification." PDXScholar, 2017. https://pdxscholar.library.pdx.edu/open_access_etds/4060.
Full textMuzi, Lanfranco. "Advances in Autonomous-Underwater-Vehicle Based Passive Bottom-Loss Estimation by Processing of Marine Ambient Noise." PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2612.
Full textLOUAHALA, SAM. "Signatures spectrales de roches en milieu tempere : valeurs reelles et valeurs percues par le satellite." Paris 7, 1988. http://www.theses.fr/1988PA077109.
Full textAbou, Karaki Najib. "Synthese et carte sismotectonique des pays de la bordure orientale de la mediterranee : sismicite du systeme de failles du jourdain-mer morte." Université Louis Pasteur (Strasbourg) (1971-2008), 1987. http://www.theses.fr/1987STR13067.
Full textEl, Hourany Roy. "Télédétection du phytoplancton par méthode neuronale : du global au régional, de la composition pigmentaire aux biorégions." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS095.
Full textThis thesis presents a novel approach to analyze and observe the phytoplankton community structure at global and regional scale using satellite data (Ocean colour and Sea surface temperature) and in-situ observations. The approach is based on neural network classification methods, such as Self-Organizing Maps (SOM) trained on a large global database composed of satellite observations collocated with in-situ measurements. First, we developed a method to estimate secondary phytoplankton pigments from satellite measurements in the global ocean. Then we focused our studies on the Mediterranean Sea. Phytoplankton groups (PFTs) were identified from the secondary pigments estimated in the first phase. We then characterized seven bio-regions by clustering annual cycles MLD obtained from Argo floats, SST and Chla by using an advanced SOM. At last, these bio-regions were characterized in terms of PFTs. The methods developed in this thesis allowed us to estimate uncertainties on secondary pigments and PFTs. The applicability of these methods are broad and can be used to investigate other oceanic areas
Diurba, Erin S. "Automated rugosity values from high frequency multibeam sonar data for benthic habitat classification." Thesis, 2007. http://hdl.handle.net/10125/20623.
Full textGrandin, Christopher John. "Associating remotely sensed seafloor types with groundfish species in Hecate Strait." Thesis, 2006. http://hdl.handle.net/1828/2087.
Full textBooks on the topic "Ocean bottom – Remote-sensing maps"
Schlee, John Stevens. Imaging the sea floor. [Washington]: U.S. G.P.O., 1995.
Find full textBlondel, Philippe. Handbook of seafloor sonar imagery. Chichester, [Eng.]: Wiley published in association with Praxis Pub., 1997.
Find full textLobkovskiĭ, L. I. Shirokougolʹnoe glubinnoe seĭsmicheskoe profilirovanie dna akvatoriĭ. Moskva: Nauka, 2001.
Find full textBreaker, Laurence C. Mapping and monitoring large-scale ocean fronts off the California Coast using imagery from the GOES-10 geostationary satellite: July 2000-June 2004. San Diego, CA: Sea Grant College Program, University of California, 2005.
Find full textCaruso, Michael J. Biweekly maps of wind stress for the North Pacific from the ERS-1 scatterometer, 1992-1995. Woods Hole, Mass: Woods Hole Oceanographic Institution, 1997.
Find full textBothner, Michael H. Processes influencing the transport and fate of contaminated sediments in the coastal ocean: Boston Harbor and Massachusetts Bay. Reston, Va: U.S. Geological Survey, 2007.
Find full textComiso, Josefino C. Polar microwave brightness temperatures from Nimbus-7 SMMR: Time series of daily and monthly maps from 1978 to 1987. Washington, D.C: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1989.
Find full textD, Kooker Lawrence, Boyle Michael E, and Geological Survey (U.S.), eds. MudScan: PC based sidescan sonar real-time data acquisition logging and display system. [Menlo Park, Ca.?]: U.S. Dept. of the Interior, U.S. Geological Survey ; a [Denver, Colo., 1993.
Find full textBlondel, Philippe. The Handbook of Sidescan Sonar. Springer, 2014.
Find full textBlondel, Philippe. The Handbook of Sidescan Sonar. Springer, 2008.
Find full textBook chapters on the topic "Ocean bottom – Remote-sensing maps"
Zheng, Q. "SAR Detection of Ocean Processes and Bottom Topography." In Comprehensive Remote Sensing, 145–96. Elsevier, 2018. http://dx.doi.org/10.1016/b978-0-12-409548-9.10403-8.
Full textXu, Qing, Quanan Zheng, Shuangshang Zhang, and Xiaofeng Li. "SAR Detection of Ocean Bottom Topography." In Advances in SAR Remote Sensing of Oceans, 147–76. CRC Press, 2018. http://dx.doi.org/10.1201/9781351235822-10.
Full textHorning, Ned, Julie A. Robinson, Eleanor J. Sterling, Woody Turner, and Sacha Spector. "Wetlands—estuaries, inland wetlands, and freshwater lakes." In Remote Sensing for Ecology and Conservation. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780199219940.003.0014.
Full textHorning, Ned, Julie A. Robinson, Eleanor J. Sterling, Woody Turner, and Sacha Spector. "Marine and coastal environments." In Remote Sensing for Ecology and Conservation. Oxford University Press, 2010. http://dx.doi.org/10.1093/oso/9780199219940.003.0013.
Full textConference papers on the topic "Ocean bottom – Remote-sensing maps"
Kovalenko, Evgenii O., Igor V. Prokhorov, Andrei A. Sushchenko, and Vladimir A. Kan. "Problem of multibeam remote sensing of sea bottom." In XXV International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, edited by Gennadii G. Matvienko and Oleg A. Romanovskii. SPIE, 2019. http://dx.doi.org/10.1117/12.2540977.
Full textBostater, Charles R., and Tyler Rotkiske. "Influence of bottom depths and bottom types on water surface reflectance." In Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2018, edited by Charles R. Bostater, Stelios P. Mertikas, and Xavier Neyt. SPIE, 2018. http://dx.doi.org/10.1117/12.2515669.
Full textFerre-Lillo, P., N. Rodriguez-Alvarez, X. Bosch-Lluis, E. Valencia, J. F. Marchan-Hernandez, and I. Ramos-Perez A. Camps. "Delay-Doppler Maps study over ocean, land and ice from space." In 2009 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2009. http://dx.doi.org/10.1109/igarss.2009.5418190.
Full textZavorotny, Valery U., and Alexander G. Voronovich. "GNSS-R delay-Doppler maps of ocean surface at weak winds." In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017. http://dx.doi.org/10.1109/igarss.2017.8127545.
Full textFont, J., C. Gabarro, J. Ballabrera, A. Turiel, J. Martinez, M. Umbert, F. Perez, et al. "SMOS CP34 soil moisture and ocean salinity maps." In 2012 12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad). IEEE, 2012. http://dx.doi.org/10.1109/microrad.2012.6185236.
Full textZhao, Yu, and Yan Qiu Chen. "Robust contour model for matching synthetic aperture radar (SAR) images with maps." In Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Stephen G. Ungar, Shiyi Mao, and Yoshifumi Yasuoka. SPIE, 2003. http://dx.doi.org/10.1117/12.467785.
Full textCohen, Sagy, Austin Raney, Dinuke Munasinghe, John Galantowicz, and G. Robert Brakenridge. "Estimating floodwater depths from flood inundation maps and topography." In Remote Sensing of the Open and Coastal Ocean and Inland Waters, edited by Robert J. Frouin and Hiroshi Murakami. SPIE, 2018. http://dx.doi.org/10.1117/12.2324982.
Full textLi, Yan, Jianyu Hu, Jing Li, Bin Fu, and Liming Ma. "Optical image modulation above the submarine bottom topography: a case study on the Taiwan Banks, China." In Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, edited by Robert J. Frouin, Yeli Yuan, and Hiroshi Kawamura. SPIE, 2003. http://dx.doi.org/10.1117/12.466156.
Full textWenxing Ji, Chundi Xiu, Weiqiang Li, and Lijun Wang. "Ocean surface target detection and positioning using the spaceborne GNSS-R Delay-Doppler maps." In IGARSS 2014 - 2014 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2014. http://dx.doi.org/10.1109/igarss.2014.6947313.
Full textKazama, Yoriko, and Tomonori Yamamoto. "Shallow water bathymetry correction using sea bottom classification with multispectral satellite imagery." In Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2017, edited by Charles R. Bostater, Stelios P. Mertikas, Xavier Neyt, and Sergey Babichenko. SPIE, 2017. http://dx.doi.org/10.1117/12.2280305.
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