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Climate change impact on the environment makes the coastal areas vulnerable and demands the evaluation of such susceptibility. Historical changes in the shoreline positions and inundation based on projected sea-level scenarios of 0.5 and 1 m were assessed for Nagapattinam District, a low-lying coastal area in the southeast coast of India, using high-resolution Shuttle Radar Topography Mission data; multi-dated Landsat satellite images of 1978, 1991, 2003, and 2015; and census data of 2011. Image processing, geographical information system, and digital shoreline analysis system methods were used in the study. The shoreline variation indicated that erosion rate varied at different time scales. The end point rate indicated the highest mean erosion of - 3.12 m/year, occurred in 73% of coast between 1978 and 1991. Weighted linear regression analysis revealed that the coast length of 83% was under erosion at a mean rate of - 2.11 m/year from 1978 to 2015. Sea level rise (SLR) impact indicated that the coastal area of about 14,122 ha from 225 villages and 31,318 ha from 272 villages would be permanently inundated for the SLR of 0.5 and 1 m, respectively, which includes agriculture, mangroves, wetlands, aquaculture, and forest lands. The loss of coastal wetlands and its associated productivity will severely threaten more than half the coastal population. Adaptation measures in people participatory mode, integrated into coastal zone management with a focus on sub-regional coastal activities, are needed to respond to the consequences of climate change.

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Land resources utilized for aquaculture development have raised many environmental issues worldwide. But no detailed information is available about the land-use changes due to aquaculture in comparison with other land use modifications. Hence, the land-use changes and predictions have been explored in India's leading aquaculture region using multitemporal satellite images , spatial techniques, and land change modeling. Agriculture was the largest proportionate land use in the study area and consistently used for aquaculture and buildings. There were no aquaculture farms in 1986; however, their area had expanded to 12,575 ha by 1996 and further increased to 38,564 ha (207%) in 2006. It then reduced in area by 36% in 2016. Agricultural lands have been used for 74%, 66%, and 15% of aquaculture development

The development of unplanned shrimp aquaculture has caused many environmental issues and multiuser conflicts worldwide due to the lack of ecosystem characteristicsbased comprehensive methodology for identifying suitable areas for aquaculture development. This study was conducted to identify proper zones for P. Vannamei farming using the analytical hierarchy process-based spatial analysis. Seventeen thematic layers were grouped into four fundamental requisite for P. vannamei aquaculture, namely, land class, water (pH, temperature, salinity, dissolved oxygen, turbidity, total ammonia nitrogen, nitrate, and phosphate), soil (pH, electrical conductivity, organic carbon, and texture), and resource availability (distance to road, source water, hatchery, and processing facility). The pairwise comparison matrix and the weighted linear combination approach were used. The suitability scores were classified on a scale from 1 (unsuitable) to 4 (most suitable). The spatial restriction rules excluded the regulated areas, including agriculture, mangroves, forest, settlements, water bodies, regions near the high tide line. The entire study area is favorable for P. vannamei culture in terms of water, soil, and infrastructure; however, land availability is restricted to 35,032 ha. Of the available area, 24,420 ha was found most suitable, and 10,603 ha was suitable for P. vannamei culture. The major water bodies, namely, the Buckingham Canal, Kandaleru River, and Penneru River, can support 34, 23, and 25% of the shrimp culture area. The final area outputs were compared with ground truth survey data and found to be consistent. The geospatial application of this methodology provides an integrated site evaluation for P. vannamei shrimp culture taking into environmental conditions and regulations.

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The World's most extensive mangrove region, the Sundarbans ecosystem, is highly biodiverse but severely stressed. Past, present, and future potential changes in Sundarbans mangroves have been assessed from multi-temporal satellite data of 1980, 2000, and 2020, elevation data, and topographical maps using geospatial techniques, digital shoreline analysis system, land change modelling, and ground truth verification. The mangrove loss was 16,025 ha between 1980 and 2020 and is predicted to be 22,286 ha between 2020 and 2050. Major changes were observed in mangroves, waterbodies, mudflats, agriculture, and aquaculture. The shoreline change by endpoint rate indicated the erosion rate by 5.81 m yr À1 in 2000-2020 compared to À0.90 m yr À1 in 1980-2000. The weighted linear regression indicated the average erosion and accretion rate of À5.96 m-yr À1 and 4.92 m yr À1 , respectively, with erosion in 76% of transects and accretion in the remaining 24% between 1980 and 2020.A sea-level rise by 1 m will inundate 17,486 ha of mangroves. The finding revealed the dynamic nature of mangroves, past and expected future loss, the severely eroding transects, hotspots, and the consequences of mangrove loss on depending the population. As fringe mangroves will be at greater risk, speedy measures are needed to stabilize the highly eroding regions.climate change vulnerability, geographical information system (GIS), natural and anthropogenic factors, sea-level rise, shoreline change, Sundarban mangroves | INTRODUCTIONMangroves are carbon-rich ecosystems that thrive in intertidal coastal saline zones or brackishwater. They protect the coast from hurricanes, tsunamis, and shoreline erosion, serve as breeding grounds for many shrimps and finfishes, offer medicine, firewood, food, and building construction materials for the local population (Dasgupta et al., 2019;Giri et al., 2007;Menéndez et al., 2020). Despite their importance for maintaining biodiversity, coastal ecology, and supporting local livelihoods, mangroves are greatly threatened across the globe (Friess et al., 2019). The development of satellite, remote sensing, and geospatial analysis software have helped researchers and environmentalists to assess mangrove dynamics and deforestation. Due to timeseries data generation capability, remote sensing science has become

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