The Use of Satellite Data in Ocean Engineering

1977 ◽  
pp. 407-418
Author(s):  
P. G. Teleki
Keyword(s):  
Satellite Data ◽  
Ocean Engineering

scholarly journals THE PREDICTION OF EXTREME VALUE WIND SPEEDS AND WAVE HEIGHTS FROM SATELLITE DATA

2018 ◽  
pp. 1
Author(s):  
Alicia Takbash ◽  
Ian Young
Keyword(s):  
Wind Speed ◽  
Numerical Model ◽  
Wave Height ◽  
Satellite Data ◽  
Extreme Values ◽  
Essential Element ◽  
Extreme Value ◽  
Ocean Engineering ◽  
Wind Speeds

The prediction of extreme value (e.g. 1 in 100 year) estimates of wind speed and wave height is an essential element of coastal and ocean engineering design. Despite decades of research on the statistics of extreme values, the consistent limitation faced by practitioners is the requirement for a long (20 plus years) dataset at the location of interest. Long term insitu buoy deployments have started to provide useful records in some geographic locations. Long term numerical model hindcasts have also proved useful. However, buoy deployments are seldom at the location of interest and the accuracy of numerical model hindcasts more than 20 years in the past is questionable. This paper will investigate the use of long-term satellite data sets of wind speed and wave height to provide global estimates of extreme values.

Generation of DEM and Ortho-image from High Resolution Stereo Satellite Data for a selected part of Southeast Bangladesh

2011 ◽  
Vol 4 (1) ◽  
pp. 500-502
Author(s):  
Md. Fazlul Haque ◽  
◽  
Md. Mostafizur Rahman Akhand ◽  
Dr. Dewan Abdul Quadir
Keyword(s):  
High Resolution ◽  
Satellite Data

Distributed access and search for the satellite data of remote sensing

2007 ◽  
Vol 13 (1s) ◽  
pp. 80-85
Author(s):  
E.B. Kudashev ◽  
◽  
A.N. Filonov ◽  
Keyword(s):  
Remote Sensing ◽  
Satellite Data

Delay-throughput tradeoff in satellite data relay networks with prioritized user satellites

2020 ◽  
Vol 17 (11) ◽  
pp. 219-230
Author(s):  
Yan Zhu ◽  
Min Sheng ◽  
Jiandong Li ◽  
Di Zhou
Keyword(s):  
Satellite Data ◽  
Relay Networks

Evaluation of Capacity of Salandi Reservoir Using Remote Sensing Data Along With Qgis Software

2018 ◽  
Vol 6 (8) ◽  
pp. 339
Author(s):  
Rupali Dhal ◽  
D. P. Satapathy
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Project Work ◽  
Space Technology ◽  
Reservoir Water ◽  
Sediment Distribution ◽  
Sensing Data ◽  
Spread Area ◽  
Water Spread

The dynamic aspects of the reservoir which are water spread, suspended sediment distribution and concentration requires regular and periodical mapping and monitoring. Sedimentation in a reservoir affects the capacity of the reservoir by affecting both life and dead storages. The life of a reservoir depends on the rate of siltation. The various aspects and behavior of the reservoir sedimentation, like the process of sedimentation in the reservoir, sources of sediments, measures to check the sediment and limitations of space technology have been discussed in this report. Multi satellite remote sensing data provide information on elevation contours in the form of water spread area. Any reduction in reservoir water spread area at a specified elevation corresponding to the date of satellite data is an indication of sediment deposition. Thus the quality of sediment load that is settled down over a period of time can be determined by evaluating the change in the aerial spread of the reservoir at various elevations. Salandi reservoir project work was completed in 1982 and the same is taken as the year of first impounding. The original gross and live storages capacities were 565 MCM& 556.50 MCM respectively. In SRS CWC (2009), they found that live storage capacity of the Salandi reservoir is 518.61 MCM witnessing a loss of 37.89 MCM (i.e. 6.81%) in a period of 27 years.The data obtained through satellite enables us to study the aspects on various scales and at different stages. This report comprises of the use of satellite to obtain data for the years 2009-2013 through remote sensing in the sedimentation study of Salandi reservoir. After analysis of the satellite data in the present study(2017), it is found that live capacity of the reservoir of the Salandi reservoir in 2017 is 524.19MCM witnessing a loss of 32.31 MCM (i.e. 5.80%)in a period of 35 years. This accounts for live capacity loss of 0.16 % per annum since 1982. The trap efficiencies of this reservoir evaluated by using Brown’s, Brune’s and Gill’s methods are 94.03%, 98.01and 99.94% respectively. Thus, the average trap efficiency of the Salandi Reservoir is obtained as 97.32%.

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