Multiple ocean parameter-based potential fishing zone (PFZ) location generation and validation in the Western Bay of Bengal.

A new conceptual framework based on satellite data, including chlorophyll (CHL), sea surface temperature (SST) fronts, relative winds, current vectors, Ekman transport, and eddies, has been developed to identify potential fishing zones (PFZ) in the Bay of Bengal (BoB). The framework aims to provide persistent forecasts, even under cloudy conditions, based on feature propagation. The validation of the PFZ was carried out using fish catch data collected by the Fishery Survey of India (FSI) between 2016 and 2018. Hooking rates (HR) from longlines and catch per unit effort (CPUE) from trawl nets were used to analyse the data points in hook rate categories (1.0-3.0 and > 3.0) and CPUE categories (50-100 kg and > 100 kg) and interpret them with the PFZ maps. The analysis showed that the high fish catch locations were consistent with persisting features in the BoB, such as high chlorophyll patches, SST fronts, and cyclonic eddies. The high fish catch locations based on hook rate and high CPUE were found to be collocated with the high chlorophyll persisting features and thermal gradients in the BoB. The regression analysis shows that availability of the food (CHL) had the strongest correlation with fish catch, followed by the comfort condition (fronts and eddies).

Seasonal variation in photosynthetic rates and satellite-based GPP estimation over mangrove forest.

In view of increasing anthropogenic influences and global changes, quantification of carbon assimilation through photosynthesis has gained tremendous significance. Precise estimation of Gross Primary Productivity (GPP) is essential for several ecosystem models and is typically done using coarser scale satellite data. The mangrove ecosystem, which offers significant protection to the coastal environment, is one of the critical habitats from a global change point of view. Light use efficiency (LUE) was measured using diurnal in situ photosynthetic rate observations for 13 dominant mangrove species for 3 seasons at each of the three mangrove dominant test-sites situated along the east and west coast of India. Variations in photosynthetic rates among these species were studied for 3 seasons that indicated varying responses of mangrove ecosystem at each site. Among all species, Rhizophora mucronata and Sonneratia apetala indicated higher values at two of the test-sites. IRS Resourcesat-2 LISS-IV datasets were used for the estimation of GPP. Mean GPP for all the sites varied from 1.2 to 7.7 g C m-2 day-1 with maximum value of 14.4 g C m-2 day-1. Mean values of GPP varied across the sites, based on its maximum LUE values and available photosynthetically active radiation (PAR). The results provide GPP values at much better spatial resolution for a threatened habitat like mangroves that typically survive in a narrow habitat along the coasts.

Monitoring of Chilika Lake mouth dynamics and quantifying rate of shoreline change using 30 m multi-temporal Landsat data.

Coastal erosion is one of the major and serious concerns for coastal communities residing in the low lying areas, especially near to estuary delta regions. These regions see lots of anthropogenic activities such as economic development, infrastructure and human settlement especially in rapidly developing countries such as India. Shoreline change is a natural process that occurs in coastal areas. But due to the stresses happening in the coast because of anthropogenic activities, understanding how shorelines change over time is important for sustainable management of coast. A crucial aspect of shoreline change monitoring is to identify the location and change over time which can be achieved by developing monitoring strategies using satellite remote sensing data. Performing shoreline change analysis using long term satellite records will help us to understand how shorelines respond to coastal development over time. In the present study we investigate shoreline erosion and accretion rate using three temporal Landsat scenes acquired over a thirty year period for the years 1988, 2000 and 2017. Digital Shoreline Change Analysis System (DSAS) an extension of ArcGIS software was used to compute rate of change statistics by calculating End Point Rate (EPR) values. We observed that Chilika coast is experiencing both erosion and accretion process with very high erosion rate of -13.6 m/yr and accretion of 13.5 m/yr, at Chilika Lake mouth. The average erosion and accretion rate of -1.13 m/yr and 1.41 m/yr were recorded for the study region.