Prioritization of satellite-derived potential fishery grounds: an analytical hierarchical approach-based model using spatial and non-spatial data

Chandran, Rahul; Jeyaram, A.; Jayaraman, V.; Manoj, Sharmila; Rajitha, K.; Mukherjee, C. K.

doi:10.1080/01431160802577980

Cited by 11 publications

(9 citation statements)

References 3 publications

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“…Pergerakan ikan berenang mengikuti pola arus yang membawa nutrien sehingga mempengaruhi migrasi dan distribusi ikan. Perairan yang menjadi pertemuan massa air yang diakibatkan oleh arus merupakan perairan yang terindikasi subur oleh kelimpahan nutrien dan ikan-ikan yang datang (Chandran et al, 2009). Pengaruh arus terhadap keberadaan ikan juga disampaikan oleh Hobday et al (2009) yang menyebutkan bahwa luasan dan waktu ikan bermigrasi adalah dampak dari skema arus musiman.…”

Section: Gambar 2 Target Strength Terhadap Presentase Jumlah Ikan DIunclassified

Estimating Potential Zones of Pelagic Fish in WPPNRI 711 (Study Case of Natuna Sea)

Hidayat

2019

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The sea resources is the future for the people of Indonesia, especially the fish as a main commodity. One of the potential fish are pelagic fish are spread throughout the waters of the sea of Indonesia. Pelagic fish is one of his life-cycle patterns of fish that move or migrate to foraging and also spawning. Based on habitat and the distance of the migrated fish, pelagic fish are differentiated into small and large pelagic fish. Therefore, the research on the distribution of pelagic fish is very important for Indonesia's economy and the realization of a sustainable fish resources. WPPNRI 711 has choosen to be research location since known as shallow water which has nurient wealth of sea water. The research conducted to analyze estimation of potential zones of pelagic fish in WPPNRI 711 sea of Natuna and its relation to pelagic fishing ground. The data taken during research is fish density. Analysis of spatial data is used to display the information of the regional fisheries. The results show that fish density is highest in WPPNRI 711 Natuna Sea waters was in the waters around island of the Tambelan Islands, Anambas and around.

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Section: Gambar 2 Target Strength Terhadap Presentase Jumlah Ikan DIunclassified

Estimating Potential Zones of Pelagic Fish in WPPNRI 711 (Study Case of Natuna Sea)

Hidayat

2019

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“…During the beginning of SWM, warmer surface area and weak surface wind contributes to development of stratification (Yanagi et al 2001). Due to stratification, areas of relatively stable temperature and high chlorophyll-a may attract feeding pelagic species (Chandran et al 2009). Water stratification creates barrier of nutrient mixing between layers influencing the primary production for fish aggregation areas (Xian et al 2012 Meanwhile, in late SWM, wind change and rain starts to occur.…”

Section: Oceanographic Parameters and Seasonal Variabilitymentioning

confidence: 99%

The Indian Mackerel Aggregation Areas in Relation to Their Oceanographic Conditions

K.¹,

M.A.²,

M.A.³

2019

JSM

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In order to determine the favourable oceanographic conditions which influence fish aggregation areas, the integration of remote sensing and GIS technique was applied. This paper aims to classify the spatial distribution and abundance of R. kanagurta in the South China Seas (SCS) using principal component analysis (PCA) and cluster analysis (CA). Remotely-sensed satellite oceanographic data of chlorophyll-a concentration (chl-a), sea surface temperature (SST) and sea surface height (SSH) together with high catch fish data were used to characterize seasonal abundance of the R. kanagurta. PCA identified two principal components that had eigenvalues >1 (PC1 and PC2) which accounted for 59.3% of the cumulative variance. Factor loading in the PCA proved that all environmental variables used in this study; chl-a (PC1), SSH and SST (PC2) had influenced the CPUE of R. kanagurta. Using CA, two clusters of CPUE abundance were identified. In cluster 1, an average CPUE of 350.7 kg/m³ with highest catch were recorded in January, April, May, July and October. Meanwhile, in cluster 2, an average CPUE of 1033.9 kg/m³ with highest catch were recorded in April, May, September and October. Preferred range for fish aggregations showed SST, SSH and chl-a were observed in between 29-31°C, 1.12-1.28 m and 0.24-0.42 mg/m 3 , respectively. Binary habitat suitability index was used to model the potential aggregation areas. The highest potential fish aggregations areas of R. kanagurta were found located along the coast of Peninsular Malaysia in early and late Southwest monsoon (at accuracy of 83.68% with kappa of 0.7). ABSTRAKIntegrasi antara data penderiaan jauh dan teknik GIS diaplikasi bagi menentukan keadaan oseanografi yang mempengaruhi kawasan pengumpulan ikan. Objektif dalam kajian ini adalah untuk mengelaskan taburan reruang dan kelimpahan R. kanagurta di Laut China Selatan menggunakan analisis komponen prinsipal (PCA) dan analisis kelompok (CA) serta mengenal pasti perhubungan antara taburan ikan dengan keadaan persekitaran. Hubungan antara data taburan klorofil-a (chl-a), suhu permukaan laut (SST) dan ketinggian permukaan laut (SSH) daripada satelit penderiaan jauh serta taburan tangkapan R. kanagurta digunakan untuk mengenal pasti hubungan taburan musiman ikan pelagik. PCA mengenal pasti dua komponen prinsipal yang mempunyai nilai eigen >1 (PC1 dan PC2) dengan nilai peratus kumulatif varians adalah 59.3%. Faktor penentuan dalam komponen prinsipal menunjukkan bahawa parameter persekitaran mempengaruhi data tangkapan ikan. CA menunjukkan dua kelompok tangkapan ikan dengan kelompok 1, nilai purata tangkapan ikan sebanyak 350.7 kg/m³ dengan catatan tangkapan ikan tertinggi pada bulan Januari, April, Mei, Julai, September dan Oktober. Manakala, di dalam kelompok 2, nilai purata tangkapan ikan sebanyak 1033.9 kg/m³ dengan catatan tangkapan ikan tertinggi pada bulan April, Mei, September dan Oktober. Julat kesesusaian cerapan pengumpulan ikan bagi SST, SSH dan chl-a didapati pada suhu 29-31°C, 1.12-1.28 m dan 0.24-0.42 mg/m³. Kawasan be...

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“…However, the coefficient of regression of both parameters showed that chl-a (p=0.000 < 0.05) was more dominant in influencing the catch of R. kanagurta in comparison to SST (p=0.05 ≤ 0.05). Chandran et al (2009) also reported a less significant relationship between small fishes with SST in the Bay of Bengal, India. They also found that pelagic fishes tend to aggregate in regions of high phytoplankton.…”

Section: Potential Fishing Groundmentioning

confidence: 99%

“…The fish tends to aggregate in the coastal area because this area is very productive and high in nutrient due to frequent upwelling (Bellido et al 2008) and river discharge. Nutrients are fundamental for phytoplankton to grow, which in turn can be related to fish production (Chandran et al 2009) and will attract the fish to come. Coastal area where nutrient supply and primary production are high favors food chains.…”

Section: Potential Fishing Groundmentioning

confidence: 99%

“…As a tropical region, the variability of SST in the archipelagic waters of Spermonde is low and relatively stable which causes slight influence of SST, while sufficient food tends to be the main reason influencing the presence of R. kanagurta in this area. Areas of relatively stable temperature and high chl-a concentration may attract feeding pelagic species (Chandran et al 2009). Optimal foraging theory predicts that organisms seek out food items at locations where there is a higher probability of finding prey, hence reducing the energy utilized in searching for prey (Reese et al 2011).…”

Section: Potential Fishing Groundmentioning

confidence: 99%

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Determination of Potential Fishing Grounds of Rastrelliger kanagurta Using Satellite Remote Sensing and GIS Technique

Nurdin

Mustapha²,

Lihan³

et al. 2015

JSM

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Prioritization of satellite-derived potential fishery grounds: an analytical hierarchical approach-based model using spatial and non-spatial data

Cited by 11 publications

References 3 publications

Estimating Potential Zones of Pelagic Fish in WPPNRI 711 (Study Case of Natuna Sea)

Estimating Potential Zones of Pelagic Fish in WPPNRI 711 (Study Case of Natuna Sea)

The Indian Mackerel Aggregation Areas in Relation to Their Oceanographic Conditions

Determination of Potential Fishing Grounds of Rastrelliger kanagurta Using Satellite Remote Sensing and GIS Technique

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