UPM Institutional Repository

Satellite Fish Forecasting in Tropical Waters


Citation

Tan, Chun Knee (2002) Satellite Fish Forecasting in Tropical Waters. Masters thesis, Universiti Putra Malaysia.

Abstract

South China Sea off the east coast of Peninsular Malaysia is shallow, semi-enclosed tropical sea. Most of the fishing activities in this area are concentrated in the inshore waters where marine resources are optimally exploited. However, the offshore waters still harbour a potential for fishery development. This study was carried out to assist the nation to develop offshore fisheries through sustainable development of the fisheries resources in the Malaysian Exclusive Economic Zone (EEZ) and thus harvest the fishery resources effectively and sustainably. The integration of remote sensing and GIS modeling has provided a powerful tool in fish forecasting. Understanding the relationship between oceanographic conditions and fish behavior can lead towards forecasting of fish migration and aggregation. Fish forecasting technology has been applied successfully in many countries. Findings of this study showed that some of the forecasting methods used in temperate water were unsuitable to be applied in this region. A fish forecasting model was developed in this study. The model was primarily based on the description of oceanographic phenomena from two major parameters, namely sea surface temperature and chlorophyll a. An oceanography and acoustic survey was conducted in year 2000 to verify the Potential Fishing Zone forecast. The survey's results showed that abundance of fish was located close to the upwelling boundaries, which agreed with the forecast results. For the ease of fish forecasting using GIS, ArcView interface was customized and named as the Tropical Fish Forecasting System (TroFFS).


Download File

[img] PDF
FK_2002_21_A.pdf

Download (729kB)

Additional Metadata

Item Type: Thesis (Masters)
Subject: Fisheries
Call Number: FK 2002 21
Chairman Supervisor: Associate Professor Dr. Shattri Bin Mansor
Divisions: Faculty of Engineering
Depositing User: Laila Azwa Ramli
Date Deposited: 11 May 2011 08:03
Last Modified: 11 May 2011 08:05
URI: http://psasir.upm.edu.my/id/eprint/10654
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item