Dong-Jiing Doong

National Cheng Kung University

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Li-Chung Wu

National Cheng Kung University

Chia Chuen Kao

National Cheng Kung University

Kuo-Ching Jao

National Cheng Kung University

Beng-Chun Lee

Huafan University

Laurence Zsu-Hsin Chuang

National Cheng Kung University

Cho‐Teng Liu

National Taiwan University

Wu Li-Chung

National Cheng Kung University

Laurence Zsu Hsin Chuang

National Cheng Kung University

Chwen-Ling Kuo

Ministry of Economic Affairs

Wei‐Cheng Lo

National Cheng Kung University

Cooperative Institutions

National Cheng Kung University

National Taiwan Ocean University

National Taiwan University

Delft University of Technology

National Yang Ming Chiao Tung University

National Central University

National Applied Research Laboratories

Feng Chia University

Institute of Applied Physics

Russian Academy of Sciences

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Quantification of non-homogeneity from ocean remote-sensing images using two-dimensional continuous wavelet transforms

International Journal of Remote Sensing (2011)

Li-Chung Wu Laurence Zsu-Hsin Chuang Dong-Jiing Doong Chia Chuen Kao

In this study, a two-dimensional continuous wavelet transform is applied to quantify the non-homogeneity from remote-sensing wave images. Our study shows that the non-homogeneity index, which is proposed here, is capable of identifying the degree of non-homogeneity from the wave-field images. However, the influence from the edges of the wave-field image should be considered in analysis. The calculated results from the simulated wave fields and from the natural wave-field images reveal that the non-homogeneity index is influenced by the bathymetry inside the area of the ocean-wave image. It conforms to the character of the natural wave non-homogeneity. After discussing the wave characteristics from the wave-field image with a high non-homogeneity index, an inhomogeneous algorithm is recommended for obtaining accurate and reasonable wave results from the wave image.

Significant wave height

10.1080/01431160903547957

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Citations (10)

Numerical assimilation in nearshore spectral wave model

Oceans (2009)

Yang-Ming Fan Kuo-Ching Jao Chia Chuen Kao Dong-Jiing Doong Li-Chung Wu

The purpose of this study is to enhance the accuracy of numerical wave forecast with data assimilation. A technique-spectral data assimilation combine model results with measured data. Using measured data to correct model results immediately and then to do wave forecast. We adopt sequential data assimilation to do data assimilation. In the process of data assimilation, the optimal interpolation of partition from Voorrips, etc. is adopted and improved. And the analytic data is from data buoy. Expect to set up the technique of spectral data assimilation. And then discuss the result which using spectral data assimilation to typhoon numerical wave model in order to verify the accuracy of spectral data assimilation model and analyze the wave character Taiwan water.

Typhoon

Buoy

Assimilation (phonology)

Data set

Interpolation

10.23919/oceans.2009.5422369

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Citations (1)

Two-dimensional continuous wavelet transform of simulated spatial images of waves on a slowly varying topography

Ocean Engineering (2008)

Laurence Zsu-Hsin Chuang Li-Chung Wu Dong-Jiing Doong Chia Chuen Kao

Continuous wavelet transform

10.1016/j.oceaneng.2008.02.008

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Citations (29)

UAV mapping of surface wave spectra under influence of bathymetry

Cho Teng Liu Dong-Jiing Doong Chi‐Jung Chang

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Accumulation of Coastal Driftwood After a Typhoon

The Twenty-first International Offshore and Polar Engineering Conference (2011)

Hui Chieh Chuang Dong-Jiing Doong

In 2009, a typhoon named Morakot moved onto Taiwan and brought torrential rains that washed down huge amount of driftwood into the sea and accumulation at the coastal areas. By the analysis of satellite images, it is found that 83.2% coastlines of Taiwan were occupied by driftwood after Morakot. The amount of driftwood cleaned-up is 1.03 million tons containing 38.7×10 (37.6%) tons were from coastal harbors, foreshores and backshores. The amount of driftwood left from Morakot is more than 100 times the estimate after historical typhoons and may be the world’s great record. The Morakot-induced driftwood has harmed the tourism and fishing industries, endangered the navigation and oceanic activities, brought large impacts to the marine environment and ecosystem, and resulted in huge economic lost.

Typhoon

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Citations (1)

Figure 7) Current velocity measurements at different depth levels at Longdong Buoy in July 2008

Dong-Jiing Doong

Buoy

10.1594/pangaea.894998

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Numerical simulations of in-situ freak waves in variable depth conditions

EGU General Assembly Conference Abstracts (2013)

Anna Kokorina Tatiana Talipova Dong-Jiing Doong Alexey Slunyaev Efim Pelinovsky

FREAK

Rogue wave

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Simulation of coastal floodings during a typhoon event with the consideration of future sea-level rises.

EGU General Assembly Conference Abstracts (2017)

Shu-Huei Jhang Wen Chih-Chung Dong-Jiing Doong Tsai Cheng-Han

Typhoon

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Classification and Possible Causes of the Freaque Waves Occurred in Taiwanese Coastal Ocean

EGU General Assembly Conference Abstracts (2015)

Dong-Jiing Doong Paul C. Liu Cheng‐Han Tsai Jen-Chih Tsai

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Application of the wavelet transform and inverse wavelet transform to analyze the ocean wave signals from data buoys

OCEANS'10 IEEE SYDNEY (2010)

L.-C. Wu Chi‐Chou Kao Dong-Jiing Doong

The ocean wave acceleration signal measured from the data buoy system is a key to derive wave features. It is well-recognized that most of the geophysical quantities are usually non-stationary, so are wave acceleration signals. This study applies a method, based on the theory of the continuous wavelet transform and its inverse, to derive the ocean wave scalogram and sea surface elevation from wave acceleration signals. Irregular wave signals are used to verify the practicality of the wavelet algorithm. After analyzing the natural wave acceleration signals, the wave scalogram presents instant wave nonlinearities at some short-time duration from the wave time series records.

Buoy

Continuous wavelet transform

SIGNAL (programming language)

10.1109/oceanssyd.2010.5603544

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