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Identification of fishing ground using local knowledge and remote sensing data

Rosli, Mohamad Rahimi (2017) Identification of fishing ground using local knowledge and remote sensing data. Masters thesis, Universiti Teknologi Malaysia, Faculty of Geoinformation and real estate.

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Abstract

Accurate identification of potential fishing ground is very important to help local fishermen carrying out fishing activities. Objectives of this study are, i) to identify the potential fishing ground using fishermen’s local knowledge, ii) to identify the potential fishing ground using information derived from remote sensing satellite data, and iii) to compare results obtained from first and second objectives. This study has been carried out in east coast of Johor. The data used in this study consist of the local knowledge used by the fishermen in carrying out fishing activities. This information can be obtained from questionnaires survey that have been carried out at eleven fishing villages around the district of Mersing and Kota Tinggi. Seventy samples (10% the total number of local fishermen) were chosen randomly. Moderate Resolution Imaging Spectroradiometer (MODIS) data were utilized to derive two marine environmental parameters; Sea Surface Temperature (SST) and Chlorophyll-a concentration (Chl-a), which were used to identify the potential fishing ground. Fishing ground identified using both local knowledge and remote sensing technique were then analyzed qualitatively and quantitatively. Correlation analysis between SST and Chl-a with distance and total catch as identified by local fishermen were carried out. SST has a correlation coefficient, R = -0.6378 with the distance and R = 0.4511 with the total catch, while Chl-a has a correlation coefficient, R = -0.1523 and R = 0.4195 with the distance and total catch respectively. These results show that fishing grounds identified by local fishermen were mostly near to coastal area and having high value of SST and Chl-a distribution which is favorable condition for a fishing ground.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Sains (Remote Sensing)) - Universiti Teknologi Malaysia, 2017; Supervisor : Assoc. Prof. Dr. Ab. Latif Ibrahim
Subjects:G Geography. Anthropology. Recreation > G Geography (General) > G70.39-70.6 Remote sensing
Divisions:Geoinformation and Real Estate
ID Code:78812
Deposited By: Fazli Masari
Deposited On:17 Sep 2018 12:13
Last Modified:17 Sep 2018 12:13

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