Journal of the Marine Biological Association of India

Influence of satellite-derived oceanographic characteristics on sea truth fishery data of Indian mackerel, Rastrelliger kanagurta

Volume 64 Issue 1

Shubhankar D. Burman, A. P. Dineshbabu, Sujitha Thomas, T. Shailaja Salian and Mini Raman

doi:10.6024/jmbai.2022.64.1.2283-03

Abstract

The study aimed to identify the most relevant variable from remote sensing data that may be utilized to forecast species-specific fish availability. Because of the schooling habits and reliance on surface productivity, the Indian mackerel, Rastrelliger kanagurta, has been suggested as a prospective species for such investigations in tropical waters. The current study showed how a geographic database can aid in focusing attention on key oceanic characteristics that can serve as the most dependable predictors of fish abundance. Generalized Additive Model (GAM) on the GIS platform was used to analyze satellite-derived Chlorophyll (Chl.) data, Sea Surface Temperature (SST) data and geo-referenced catch weights of Indian Mackerel. When comparing moderate and low catch weighting to high catch weighting, the Chl. content was highly significant. SST was important when the catch weighting was high, but not when the catch weighting was moderate or low.

Keywords

Remote sensing, GIS, GAM Model, Indian mackerel, Rastrelliger kanagurta, species distribution analysis

Date : 18-05-2022