EXPLORING SPATIO-TEMPORAL WAVE PATTERN USING UNSUPERVISED TECHNIQUE

Author:

Rohana N. A.,Yusof N.,Uti M. N.,Din A. H. M.

Abstract

Abstract. The sea waves are the up and down movements of water in the sea. The various heights of sea waves are known as significant wave heights. Each type of wave has their own characteristics based on their significant wave heights. The aim of this research is to explore spatio-temporal wave patterns and their effects on Tok Jembal coastal areas. For this study, the monthly wave data were obtained from the satellite altimeters that have been processed using Radar Altimeter Database System (RADS). The Self Organizing Map (SOM) method was used to extract the spatio-temporal wave height patterns from the monthly wave height data. From the clustering results, six number of clusters were extracted and then each of these clusters was categorized into specific type of wave heights. In addition, time series of Landsat satellite images were used to observe the coastal changes at Tok Jembal areas. Finally, we analyzed the effects of spatio-temporal wave patterns towards the occurrences of coastal erosion along the coastal areas. This study has discovered that the wave heights along the coastal areas fall in slight category and showed less effects on the erosion. From the visual interpretation of time- series images (10 years gap) also proved that the erosion can be considered as moderate. Overall, this study could benefit the coastal management especially for shoreline monitoring where early action can be taken when there are signs of erosion along the coast.

Publisher

Copernicus GmbH

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3