Assessment of coastal vulnerability index using [remote sensing] and [geographical information system] / Muhamad Husni Othman

Othman, Muhamad Husni (2018) Assessment of coastal vulnerability index using [remote sensing] and [geographical information system] / Muhamad Husni Othman. Degree thesis, Universiti Teknologi MARA, Perlis.


The main objective of the present study is to develop a coastal vulnerability index (CVI) for the Pahang coastline that starting from Cherating to Tanjung Agas, Kuala Pahang. That area has been divided into 18 regions that called as a management unit. This study incorporated six variables to assess the CVI for the study area. These six variables consist of geomorphology, shoreline change rate, coastal slope, average tides range, significant wave height and sea level rise. The ranking is on a linear scale from 1 to 5 in order of increasing vulnerability; value 1 represents the lowest risk ranking assigned to the coastline whereas value 5 ranks the coastline with the highest risk. A total of 85.4 km of coastline was evaluated and of this, 18.9% of the mapped shoreline is classified as being extreme vulnerability, 42.7% of Pahang Coast shoreline is classified as high vulnerability and 12.1% as moderate vulnerability. The implementation of the Management Plan would dependent on the co-operations of the government departments and agencies, private sector and the public


Item Type: Thesis (Degree)
Email / ID Num.
Othman, Muhamad Husni
Email / ID Num.
Saad, Siti Nor Maizah
Subjects: G Geography. Anthropology. Recreation > G Geography (General) > Geographic information systems
G Geography. Anthropology. Recreation > GB Physical geography > Geomorphology. Landforms. Terrain
T Technology > TD Environmental technology. Sanitary engineering > Remote sensing
Divisions: Universiti Teknologi MARA, Perlis > Arau Campus > Faculty of Architecture, Planning and Surveying
Programme: Bachelor Surveying Science and Geomatics (Honours)
Keywords: Coastal vulnerability index (CVI), geographical information system (GIS), remote sensing
Date: 2018
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