Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia

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 betwe...

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Main Authors:	Shaari N.R, Mustapha M.A.
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2018
Online Access:	http://journalarticle.ukm.my/12151/ http://journalarticle.ukm.my/12151/ http://journalarticle.ukm.my/12151/1/03%20Shaari%2C%20N.R.pdf

id	ukm-12151
recordtype	eprints
spelling	ukm-121512018-10-08T13:46:30Z http://journalarticle.ukm.my/12151/ Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia Shaari N.R, Mustapha M.A., 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. Penerbit Universiti Kebangsaan Malaysia 2018-07 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/12151/1/03%20Shaari%2C%20N.R.pdf Shaari N.R, and Mustapha M.A., (2018) Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia. Sains Malaysiana, 47 (7). pp. 1369-1378. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol47num7_2018/contentsVol47num7_2018.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	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.
format	Article
author	Shaari N.R, Mustapha M.A.,
spellingShingle	Shaari N.R, Mustapha M.A., Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia
author_facet	Shaari N.R, Mustapha M.A.,
author_sort	Shaari N.R,
title	Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia
title_short	Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia
title_full	Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia
title_fullStr	Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia
title_full_unstemmed	Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia
title_sort	predicting potential rastrelliger kanagurta fish habitat using modis satellite data and gis modeling: a case study of exclusive economic zone, malaysia
publisher	Penerbit Universiti Kebangsaan Malaysia
publishDate	2018
url	http://journalarticle.ukm.my/12151/ http://journalarticle.ukm.my/12151/ http://journalarticle.ukm.my/12151/1/03%20Shaari%2C%20N.R.pdf
first_indexed	2023-09-18T20:01:58Z
last_indexed	2023-09-18T20:01:58Z
_version_	1777406908825600000

Predicting potential Rastrelliger kanagurta fish habitat using MODIS satellite data and GIS modeling: a case study of Exclusive Economic Zone, Malaysia

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