Predicting potential rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling

A case study of exclusive economic zone, Malaysia

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Remote sensing and GIS are robust tools in detection of fishing grounds which is important in providing fish sustainability for human being. This recent tool allows fishing grounds detection at minimal cost and optimizes effort. The objectives of this study were to investigate the relationship between R. kanagurta fishing grounds with environmental factors and to determine its potential fishing grounds. MODIS derived satellite data of Chl-a and sea surface temperature (SST) and fisheries catch data of 2008 and 2009 were analyzed using suitability index (SI) and generalized additive model (GAM) in the Exclusive Economic Zone (EEZ) off the East Coast of Peninsular Malaysia. Distribution of R. kanagurta was associated with preferred range of 0.20 to 0.30 mg/m3 for Chl-a and 29 to 30°C for SST. GAM indicated that these parameters influenced fish distribution (p<0.001). Potential fishing ground maps derived from the SI and GAM model indicated accuracy at 75% with kappa of 0.7 and accuracy at 87.6% with kappa of 0.8, respectively. This study indicated the capability of GAM as an exploratory tool to map the potential fishing grounds of R. kanagurta in the EEZ waters.

Original languageEnglish
Pages (from-to)1369-1378
Number of pages10
JournalSains Malaysiana
Volume47
Issue number7
DOIs
Publication statusPublished - 1 Jul 2018

Fingerprint

Exclusive Economic Zone
MODIS
satellite data
GIS
habitat
fish
modeling
sea surface temperature
catch statistics
fishing ground
environmental factor
fishery
sustainability
remote sensing
coast
cost

Keywords

  • Fisheries spatial prediction
  • Generalized additive model
  • MODIS
  • Suitability index model

ASJC Scopus subject areas

  • General

Cite this

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abstract = "Remote sensing and GIS are robust tools in detection of fishing grounds which is important in providing fish sustainability for human being. This recent tool allows fishing grounds detection at minimal cost and optimizes effort. The objectives of this study were to investigate the relationship between R. kanagurta fishing grounds with environmental factors and to determine its potential fishing grounds. MODIS derived satellite data of Chl-a and sea surface temperature (SST) and fisheries catch data of 2008 and 2009 were analyzed using suitability index (SI) and generalized additive model (GAM) in the Exclusive Economic Zone (EEZ) off the East Coast of Peninsular Malaysia. Distribution of R. kanagurta was associated with preferred range of 0.20 to 0.30 mg/m3 for Chl-a and 29 to 30°C for SST. GAM indicated that these parameters influenced fish distribution (p<0.001). Potential fishing ground maps derived from the SI and GAM model indicated accuracy at 75{\%} with kappa of 0.7 and accuracy at 87.6{\%} with kappa of 0.8, respectively. This study indicated the capability of GAM as an exploratory tool to map the potential fishing grounds of R. kanagurta in the EEZ waters.",
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