Zeitschriftenartikel: „Sea monitoring“

1

Gornitz, Vivien. „Monitoring sea level changes“. Climatic Change 31, Nr. 2-4 (Dezember 1995): 515–44. http://dx.doi.org/10.1007/bf01095160.

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2

Korotaev, G. K., V. V. Malinovsky, V. V. Pustovoitenko, L. N. Radaikina und S. V. Stanichny. „Sea area monitoring space experiment“. Kosmìčna nauka ì tehnologìâ 8, Nr. 2-3 (30.05.2002): 227–30. http://dx.doi.org/10.15407/knit2002.02.227.

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3

Woodworth, PL, A. Aman und T. Aarup. „Sea level monitoring in Africa“. African Journal of Marine Science 29, Nr. 3 (Dezember 2007): 321–30. http://dx.doi.org/10.2989/ajms.2007.29.3.2.332.

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4

Ben-Michael, Chai, und Gilad Even-Tzur. „GNSS-Based Sea Level Monitoring“. Marine Geodesy 30, Nr. 4 (07.11.2007): 333–44. http://dx.doi.org/10.1080/01490410701568426.

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5

GRONVALL, H. „Towards optimal sea-ice monitoring in the Baltic Sea“. ICES Journal of Marine Science 56 (Dezember 1999): 165–71. http://dx.doi.org/10.1006/jmsc.1999.0628.

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6

肖, 永红. „Design and Implementation of Graphical Network Monitoring System“. Software Engineering and Applications 07, Nr. 02 (2018): 84–90. http://dx.doi.org/10.12677/sea.2018.72010.

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7

黄, 业霆. „Design of Sericulture Information Monitoring and Management System“. Software Engineering and Applications 10, Nr. 03 (2021): 372–81. http://dx.doi.org/10.12677/sea.2021.103042.

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8

Tuen, K. L. „Monitoring of sea surface temperature in the South China Sea“. Hydrobiologia 285, Nr. 1-3 (Juni 1994): 1–5. http://dx.doi.org/10.1007/bf00005648.

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9

Weaver, Ronald L. S., Konrad Steffen, John Heinrichs, James A. Maslanik und Gregory M. Flato. „Data assimilation in sea-ice monitoring“. Annals of Glaciology 31 (2000): 327–32. http://dx.doi.org/10.3189/172756400781820039.

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AbstractThe detection of small changes in concentration or thickness in the Arctic or Antarctic ice cover is an important topic in the current global-climate-change debate. Change detection using satellite data alone requires rigorous error analysis for their derived ice products, including inter-satellite validation for long time series. All models of physical processes are only approximations, and the best models of complicated physical processes have errors and uncertainties. A promising approach is data assimilation, combining model, in situ data and satellite remote-sensing data. Sea-ice monitoring from satellite, ice-model estimates, and the potential benefit of combining the two are discussed in some detail. In a case-study we demonstrate how the sea-ice backscatter for the Beaufort Sea region was derived using a backscattering model in combination with an ice model. We conclude that, for data assimilation, the first steps include the use of simple models, moving, with success at this level, to progressively more complex models. We also recommend reconfiguring the current remote-sensing data to include precise time tags with each pixel. For example, the current Special Sensor Microwave Imager data might be reissued in a time-tagged orbital (or gridded) format as opposed to the currently available daily averaged gridded data. Finally, error statistics and quality-control information also need to be readily available in a form useful for assimilation. The effectiveness of data-assimilation techniques is directly linked to the availability of data error statistics.

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10

Kang, Hye‐Jin, In‐Ky Cho, Jung‐Ho Kim, Hwan‐Ho Yong, Sung‐Ho Song und Young‐Gyu Park. „SP Monitoring at a Sea Dike“. Near Surface Geophysics 12, Nr. 1 (Oktober 2013): 83–92. http://dx.doi.org/10.3997/1873-0604.2013063.

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11

Wilbur, Grant, Bryce MacMillan, Kyle M. Bade und Igor Mastikhin. „MRI monitoring of sea spray freezing“. Journal of Magnetic Resonance 310 (Januar 2020): 106647. http://dx.doi.org/10.1016/j.jmr.2019.106647.

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12

Wedekind, Ch, G. Schilling, M. Grüttmüller und K. Becker. „Gamma-radiation monitoring network at sea“. Applied Radiation and Isotopes 50, Nr. 4 (April 1999): 733–41. http://dx.doi.org/10.1016/s0969-8043(98)00062-1.

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13

Homes, Gordon M. „Changing technology—Monitoring sea level change“. Australian Surveyor 37, Nr. 1 (März 1992): 13–22. http://dx.doi.org/10.1080/00050326.1992.10438770.

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14

Kravtsova, V. I., und T. V. Tarasenko. „Space monitoring of Aral Sea degradation“. Water Resources 37, Nr. 3 (Mai 2010): 285–96. http://dx.doi.org/10.1134/s0097807810030036.

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15

Bett, Brian. „Environmental monitoring in the deep sea“. Marine Pollution Bulletin 21, Nr. 1 (Januar 1990): 3–4. http://dx.doi.org/10.1016/0025-326x(90)90129-v.

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16

Reise, Karsten. „Monitoring the Wadden Sea — an introduction“. Helgoländer Meeresuntersuchungen 43, Nr. 3-4 (September 1989): 259–62. http://dx.doi.org/10.1007/bf02365887.

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17

赵, 鹏泽. „Design and Implementation of Intelligent Water Environment Monitoring Platform“. Software Engineering and Applications 09, Nr. 01 (2020): 72–81. http://dx.doi.org/10.12677/sea.2020.91009.

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18

Tougaard, Svend. „Monitoring harbour seal (Phoca vitulina) in the Danish Wadden Sea“. Helgoländer Meeresuntersuchungen 43, Nr. 3-4 (September 1989): 347–56. http://dx.doi.org/10.1007/bf02365895.

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19

冯, 丹. „Design and Realization of Intelligent Monitoring System Based on TMS320DM8168“. Software Engineering and Applications 05, Nr. 02 (2016): 164–70. http://dx.doi.org/10.12677/sea.2016.52018.

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20

王, 志昌. „Research on Meteorological Data Partitioning Strategy for Forest Fire Monitoring“. Software Engineering and Applications 07, Nr. 01 (2018): 46–52. http://dx.doi.org/10.12677/sea.2018.71005.

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21

Karvonen, J. „Operational SAR-based sea ice drift monitoring over the Baltic Sea“. Ocean Science 8, Nr. 4 (16.07.2012): 473–83. http://dx.doi.org/10.5194/os-8-473-2012.

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Abstract. An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR) images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine) with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR-based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season, and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

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22

Karvonen, J. „Operational SAR-based sea ice drift monitoring over the Baltic Sea“. Ocean Science Discussions 9, Nr. 1 (30.01.2012): 359–84. http://dx.doi.org/10.5194/osd-9-359-2012.

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Abstract. An algorithm for computing ice drift from pairs of synthetic aperture radar (SAR) images covering a common area has been developed at FMI. The algorithm has been developed based on the C-band SAR data over the Baltic Sea. It is based on phase correlation in two scales (coarse and fine) with some additional constraints. The algorithm has been running operationally in the Baltic Sea from the beginning of 2011, using Radarsat-1 ScanSAR wide mode and Envisat ASAR wide swath mode data. The resulting ice drift fields are publicly available as part of the MyOcean EC project. The SAR based ice drift vectors have been compared to the drift vectors from drifter buoys in the Baltic Sea during the first operational season and also these validation results are shown in this paper. Also some navigationally useful sea ice quantities, which can be derived from ice drift vector fields, are presented.

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23

Andersen, Ole B., Per Knudsen und Brian Beckley. „Monitoring sea level and sea surface temperature trends from ERS satellites“. Physics and Chemistry of the Earth, Parts A/B/C 27, Nr. 32-34 (Januar 2002): 1413–17. http://dx.doi.org/10.1016/s1474-7065(02)00081-5.

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24

El-Sikaily, Amany, Azza Khaled und Ahmed El Nemr. „Heavy Metals Monitoring using Bivalves from Mediterranean Sea and Red Sea“. Environmental Monitoring and Assessment 98, Nr. 1-3 (November 2004): 41–58. http://dx.doi.org/10.1023/b:emas.0000038178.98985.5d.

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25

Temimi, Marouane, Peter Romanov, Hosni Ghedira, Reza Khanbilvardi und Kim Smith. „Sea-ice monitoring over the Caspian Sea using geostationary satellite data“. International Journal of Remote Sensing 32, Nr. 6 (15.02.2011): 1575–93. http://dx.doi.org/10.1080/01431160903578820.

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26

杨, 成慧. „Target Tracking and Alarm Monitoring Research Based on Wireless Sensor Network“. Software Engineering and Applications 02, Nr. 01 (2013): 35–41. http://dx.doi.org/10.12677/sea.2013.21007.

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27

Stepanova, O. „Results of Black Sea algal viruses monitoring“. Limnology and Freshwater Biology, Nr. 4 (2020): 1030–31. http://dx.doi.org/10.31951/2658-3518-2020-a-4-1030.

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28

Konings, H. „Oil pollution monitoring on the North Sea“. Spill Science & Technology Bulletin 3, Nr. 1-2 (Januar 1996): 47–52. http://dx.doi.org/10.1016/s1353-2561(96)00028-x.

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29

Liu, Jianqiang, Runheng Huang, Zhengang Jin, Kuiqiao Wu und Congrong Sun. „Bohai Sea Ice Monitoring Using Satellite Images“. Journal of Cold Regions Engineering 14, Nr. 2 (Juni 2000): 93–100. http://dx.doi.org/10.1061/(asce)0887-381x(2000)14:2(93).

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30

Soulat, F., M. Caparrini, O. Germain, P. Lopez-Dekker, M. Taani und G. Ruffini. „Sea state monitoring using coastal GNSS-R“. Geophysical Research Letters 31, Nr. 21 (November 2004): n/a. http://dx.doi.org/10.1029/2004gl020680.

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31

Snow, Mary M., und Richard K. Snow. „Modeling, monitoring, and mitigating sea level rise“. Management of Environmental Quality: An International Journal 20, Nr. 4 (12.06.2009): 422–33. http://dx.doi.org/10.1108/14777830910963753.

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32

Ruhl, Henry A., und Imants G. Priede. „Open up monitoring of deep-sea drilling“. Nature 473, Nr. 7346 (Mai 2011): 154. http://dx.doi.org/10.1038/473154b.

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33

Nystuen, Jeffrey A. „Monitoring air–sea exchange using ambient sound“. Journal of the Acoustical Society of America 103, Nr. 5 (Mai 1998): 2910. http://dx.doi.org/10.1121/1.422071.

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34

Abdallah, Renee I., Nagla M. Khalil und Mohamid I. Roushdie. „Monitoring of pollution in Egyptian Red Sea“. Egyptian Journal of Petroleum 24, Nr. 1 (März 2015): 59–70. http://dx.doi.org/10.1016/j.ejpe.2015.02.006.

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35

Matthijs, E., und M. Stalmans. „Monitoring of LAS in the North Sea“. Tenside Surfactants Detergents 30, Nr. 1 (01.01.1993): 29–33. http://dx.doi.org/10.1515/tsd-1993-300109.

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36

徐, 颖捷. „Design and Implementation of Wide Range Frequency Monitoring System Based on PIC18F452“. Software Engineering and Applications 10, Nr. 03 (2021): 234–45. http://dx.doi.org/10.12677/sea.2021.103027.

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37

叶, 忠儒. „Design and Implementation of Human Health Intelligent Monitoring System with Multi-Sensor“. Software Engineering and Applications 10, Nr. 02 (2021): 60–69. http://dx.doi.org/10.12677/sea.2021.102009.

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38

Zhao, Y., P. Wei, H. Zhu und B. Xing. „SEA ICE DRIFT MONITORING IN THE BOHAI SEA BASED ON GF4 SATELLITE“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (30.04.2018): 2419–25. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2419-2018.

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The Bohai Sea is the inland sea with the highest latitude in China. In winter, the phenomenon of freezing occurs in the Bohai Sea due to frequent cold wave influx. According to historical records, there have been three serious ice packs in the Bohai Sea in the past 50 years which caused heavy losses to our economy. Therefore, it is of great significance to monitor the drift of sea ice and sea ice in the Bohai Sea. The GF4 image has the advantages of short imaging time and high spatial resolution. Based on the GF4 satellite images, the three methods of SIFT (Scale invariant feature &ndash; the transform and Scale invariant feature transform), MCC (maximum cross-correlation method) and sift combined with MCC are used to monitor sea ice drift and calculate the speed and direction of sea ice drift, the three calculation results are compared and analyzed by using expert interpretation and historical statistical data to carry out remote sensing monitoring of sea ice drift results. The experimental results show that the experimental results of the three methods are in accordance with expert interpretation and historical statistics. Therefore, the GF4 remote sensing satellite images have the ability to monitor sea ice drift and can be used for drift monitoring of sea ice in the Bohai Sea.

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Roussel, Nicolas, Guillaume Ramillien, Frédéric Frappart, José Darrozes, Adrien Gay, Richard Biancale, Nicolas Striebig, Vincent Hanquiez, Xavier Bertin und Damien Allain. „Sea level monitoring and sea state estimate using a single geodetic receiver“. Remote Sensing of Environment 171 (Dezember 2015): 261–77. http://dx.doi.org/10.1016/j.rse.2015.10.011.

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40

Theodorou, A. J. „Ecological monitoring studies for volos sea outfall (Pagassitikos Gulf, western Aegean Sea)“. Water Science and Technology 32, Nr. 2 (01.07.1995): 273–80. http://dx.doi.org/10.2166/wst.1995.0117.

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Nutrient pollution in Pagassitikos Gulf arises mainly from the disposal of Volos untreated domestic wastewater inside Volos Bay, and also the agricultural run-off from the surrounding the Gulf cultivated areas. Volos Bay's limited circulation provides the conditions for the Bay's eutrophication by the discharge of untreated wastewater. In July 1987 this surface discharge was replaced by a new deep outfall system. The latter was located outside Volos Bay discharging primary treated effluents offshore at a depth of 55 m. To monitor any ecological changes, pre-operational (1986-1987) and operational (1988-1989) oceanographic data have been compared. The results showed a decrease in nutrient and phytoplankton concentrations between pre-operational and operational periods. Furthermore, in the vicinity of the present discharge a significant increase in the abundance of benthic communities occurred, due presumably to the continuous supply of food, adequate water circulation and high dissolved oxygen levels.

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41

Sun, Hequan, Chunhua Li und Yifeng Cheng. „Monitoring Polar Sea Ice Using Optical and SAR Data“. Marine Technology Society Journal 53, Nr. 6 (01.11.2019): 35–41. http://dx.doi.org/10.4031/mtsj.53.6.4.

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AbstractWith the movement and destructiveness of sea ice, conventional in situ instruments are restricted or unavailable for polar sea ice observation. Satellite remote sensing is a feasible way to monitor sea ice in the polar area. Multispectral imaging spectrometer and synthetic aperture radar are applied to monitoring the sea ice in this article with high spatial resolution, wide swath, and continuous imaging. The sea ice distribution and motion can be measured by analyzing satellite remote sensing images. The image segmentation method is presented in the article to obtain the sea ice distribution. Meanwhile, the cross-correlation algorithm to extract sea ice motion is proposed as well as the processed vector results.

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42

Ragimova, Nazila Ali, Vugar Hajimahmud Abdullayev und Vasila Soltanaga Abbasova. „ORGANIZATION OF ENVIRONMENTAL MONITORING IN THE CASPIAN SEA“. ScienceRise 2 (30.04.2020): 3–9. http://dx.doi.org/10.21303/2313-8416.2020.001277.

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The object of research is ecological monitoring of the Caspian Sea. This article addressed the objectives and components of environmental monitoring. It also describes the objectives for the establishment of a Unified State Environmental Monitoring System. Special attention is paid to the structure of the environmental network monitoring system, which consists of three levels: low, medium and high. One of the main problems is the establishment of the Unified State Environmental Monitoring System of the Caspian Sea. This article considered the main functions and objectives of the Unified State Environmental Monitoring System. Here are also discussed the computing center of the environmental monitoring system and its functions and components. The research used three main components for environmental data processing: database management systems, geographic information system and integrated software packages. Examples of a computer system of environmental monitoring include: ArcGIS, MapInfo, ArcView and OCEAN. The main scientific results of this research are the main functions, objectives and components of environmental monitoring of the Caspian Sea to reduce pollution levels. The obtained results can be used to optimize the characteristics of environmental information systems, which are used to organize environmental monitoring. Innovative technological product of this research is the development of an algorithm for the organization of environmental monitoring of the Caspian Sea. It will allow ecologists to monitor the environmental situation of the Caspian Sea and further improve it. The obtained innovative technological product will be useful for carrying out environmental monitoring of the most contaminated section of the water basin, and more precisely for monitoring the scale of pollution and further improving the environmental situation of the water area.

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朱, 明. „Design and Implementation of a Dataflow Monitoring System Based on the Genetic Algorithm Thought“. Software Engineering and Applications 02, Nr. 06 (2013): 131–37. http://dx.doi.org/10.12677/sea.2013.26023.

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44

杜, 井峰. „The Design and Implementation of Integrating Multi-Source Data in Disaster Monitoring and Assessment“. Software Engineering and Applications 06, Nr. 04 (2017): 92–101. http://dx.doi.org/10.12677/sea.2017.64010.

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45

杨, 岗. „The Monitoring System for Cargo Holographic Status in Freight EMUs Based on ZigBee Technology“. Software Engineering and Applications 08, Nr. 05 (2019): 245–52. http://dx.doi.org/10.12677/sea.2019.85030.

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46

徐, 友洪. „Research on Security Technology of Industrial Control System Based on Network Traffic Abnormal Monitoring“. Software Engineering and Applications 09, Nr. 06 (2020): 497–506. http://dx.doi.org/10.12677/sea.2020.96057.

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47

Asmus, V. V., E. V. Vasilenko, V. V. Zatyagalova, N. P. Ivanova, V. A. Krovotyntsev, A. A. Maksimov und I. S. Trenina. „Satellite Monitoring of Sea Ice Cover and Water Parameters for the Caspian Sea“. Russian Meteorology and Hydrology 43, Nr. 10 (Oktober 2018): 686–96. http://dx.doi.org/10.3103/s1068373918100084.

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48

Boardman, Diane, David Darwin, Jolyon Martin, Neil Mclntyre und Ken Sullivan. „Development of a sea-ice workstation for the automated monitoring of sea ice“. Polar Record 31, Nr. 177 (April 1995): 155–60. http://dx.doi.org/10.1017/s0032247400013656.

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AbstractUK-based operations that range from ship routing and resource exploration to weather forecasting and glaciology have direct and growing interests in the oceans of the polar regions. Typically, information describing sea-ice conditions in localised regions is required on short time scales. To explore this market, the UK's Defence Research Agency, as part of a programme of the British National Space Centre, has commissioned the development of a prototype sea-ice workstation by a consortium led by Earth Observation Sciences Ltd.The sea-ice workstation (SIWS) uses data from several current earth observation sensors, thereby combining the advantages of regional survey, all-weather capability, and high-resolution imagery. The workstation has been designed to run with a minimum of operator intervention in order to optimise speed of operation and ensure consistency of results. The geophysical processing chains generate charts of the ice edge, ice type, ice concentration, ice-motion vectors, and sea-surface temperatures.Although taking full advantage of developments made elsewhere, the project has also made significant progress in research into the automated mapping of ice types. Existing ice-motion algorithms have been significantly enhanced as well. Considerable emphasis is being placed on the validation of the results from the system in order to assess their quality, this being one of the major concerns of potential users. The sea-ice workstation was completed in July 1994 and will form the basis for a series of evaluations that are intended to assess the value of the system for mapping and monitoring sea ice.

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49

Ya-Qiu Jin. „Monitoring regional sea ice of China's Bohai Sea by SSM/I scattering indexes“. IEEE Journal of Oceanic Engineering 23, Nr. 2 (April 1998): 141–44. http://dx.doi.org/10.1109/48.664093.

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50

Stagg, R. M. „North Sea Task Force Biological Effects Monitoring Programme“. Water Science and Technology 24, Nr. 10 (01.11.1991): 87–98. http://dx.doi.org/10.2166/wst.1991.0279.

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This paper describes the biological effects monitoring programme proposed by the North Sea Task Force (NSTF). The rationale for each of the recommended methods will be outlined and the advantages and limitations, within the framework of the objectives of the monitoring programme, will be discussed.

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Zeitschriftenartikel zum Thema „Sea monitoring“

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