Faculty Publications
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Item Monitoring Spatial and Temporal Scales of Shoreline Changes in the Cuddalore Region, India(Elsevier, 2018) Subbarayan, S.; Kulithalai Shiyam Sundar, K.S.S.; Vishnuprasath, S.R.Coastal zones are constantly undergoing changes in shape and environment due to natural processes and anthropogenic interventions. The study of shoreline change has become a matter of great concern in recent years. The measurement of shorelines is a key factor in coastal zone construction. A shoreline change study was carried out for a 33-km stretch of the Cuddalore coast between Gadilam and the Vellar River. Satellite images (2000, 2005, 2010, and 2015) were taken as an input dataset in a GIS platform. Automatic shoreline delineation was attempted by a masking technique using ENVI software. In this study, the modification of normalized difference water index (MNDWI) method extracted the raster shoreline-based contrast value of coastal pixels and thresholding techniques for segmenting water and land regions. DSAS software and reference digitized shoreline boundary data were used for the analysis of shoreline changes. End point rate (EPR) and net shoreline movement determination showed the northern part of the Uppanar River mouth under erosion (region A to C and E) and sediment deposition at an accretion rate of 7.6. m/year from EPR and 114. m from NSM. The maximum shoreline erosion rate was -. 3.8. m/year from EPR and -. 57. m from NSM. From these attempts and results, a methodical approach for detection and monitoring of shoreline changes on spatial and temporal scales of interest have been suggested. © 2019 Elsevier Inc. All rights reserved.Item Study of dynamic changes through geoinformatics technique: A case study of Karwar coast, west coast of India(Springer, 2019) Yadav, A.; Dodamani, B.M.; Dwarakish, G.S.Shoreline is one of the geo-indicators of the coastal zone. Coastal zone is subjected to threats due to change in shoreline. Shoreline change leads to modification and causes for damages of properties, infrastructure around the shoreline region. These modifications, changes of land expands too many issues of the environment under the coastal zone. The present study was carried out by employing remote sensing and GIS techniques for the coastal regime of Karwar, India. LANDSAT-8 remote sensing data was integrated with the GPS data collected during the field survey. The satellite data is processed and analyzed using ERDAS IMAGINE 2014 tool and ArcGIS 10.3 tool, respectively. High Water Line (HWL) is considered for the extraction of shoreline. The visual interpretation of satellite imageries is carried out to distinguish the HWL. Net Shoreline Movement (NSM) was evaluated by adopting Digital Shoreline Analysis System (DSAS) tool. Statistical methods such as Weighted Linear Regression (WLR), Linear Regression Rate (LRR) and End Point Rate (EPR) were used to estimate the changes of shoreline. The present study reveals that shorelines of Karwar Coast, Ravindranath Taghore beach experiences an average erosion rate is −4.61 m/year (EPR), −1.49 m/year (LRR), and 0.19 (WLR) and Devbagh beach experiences an average erosion rate is −9.74 m/year (EPR), −7.53 m/year (LRR), and −11.55 m/year (WLR). © Springer Nature Singapore Pte Ltd. 2019.Item Monitoring Spatial and Temporal Scales of Shoreline Changes in the Cuddalore Region, India(Elsevier, 2019) Subbarayan, S.; Kulithalai Shiyam Sundar, K.S.S.; Vishnuprasath, S.R.Coastal zones are constantly undergoing changes in shape and environment due to natural processes and anthropogenic interventions. The study of shoreline change has become a matter of great concern in recent years. The measurement of shorelines is a key factor in coastal zone construction. A shoreline change study was carried out for a 33-km stretch of the Cuddalore coast between Gadilam and the Vellar River. Satellite images (2000, 2005, 2010, and 2015) were taken as an input dataset in a GIS platform. Automatic shoreline delineation was attempted by a masking technique using ENVI software. In this study, the modification of normalized difference water index (MNDWI) method extracted the raster shoreline-based contrast value of coastal pixels and thresholding techniques for segmenting water and land regions. DSAS software and reference digitized shoreline boundary data were used for the analysis of shoreline changes. End point rate (EPR) and net shoreline movement determination showed the northern part of the Uppanar River mouth under erosion (region A to C and E) and sediment deposition at an accretion rate of 7.6m/year from EPR and 114m from NSM. The maximum shoreline erosion rate was −3.8m/year from EPR and −57m from NSM. From these attempts and results, a methodical approach for detection and monitoring of shoreline changes on spatial and temporal scales of interest have been suggested. © 2019 Elsevier Inc. All rights reserved.Item Geospatial and Hydrogeochemical Insights for Monitoring Water Quality and Salinity in Coastal Regions of Southern Karnataka, India(Springer Science+Business Media, 2025) Suryawanshi, V.; Ramesh, H.; Nasar, T.Coastal areas face significant challenges due to the depletion of groundwater and seawater intrusion into freshwater aquifers. Additionally, insufficient monitoring of freshwater quality is a major concern for consumers. In Karnataka’s Dakshina Kannada district, groundwater is crucial for meeting the needs of the community, industry, and agriculture. This study investigates the impact of excessive use, human activities, and agricultural chemicals on groundwater quality, with a focus on the hydrogeochemistry of the Natravathi and Gurapura catchments. The study analyzed 32 groundwater samples collected seasonally from 2021 to 2022 for 18 physiochemical parameters. The Water Quality Index (WQI) was determined using factors such as pH, Dissolved Solids, Oxidatio Reduction Potentisl, Electrical Conductivity, Total Hardness, Total Dissolved Solids, Calcium, Chlorides, Potassium, and Sodium. WQI scores ranged from 0 to 52 post-monsoon and 0 to 42 pre-monsoon. An ArcGIS-based spatial distribution map was created to show temporal changes in groundwater quality. Post monsoon measurements showed significant cations ranging from 4.25 to 64.54 mg/l, calcium from 40 to 520 mg/l, chloride from 40 to 200 mg/l, and potassium from − 8.05 to 15.44 mg/l. Pre-monsoon measurements indicated sodium levels from 28 to 208 mg/l, calcium from 240 to 840 mg/l, chloride from 19.99 to 159.9 mg/l, and potassium from 0 to 61.79 mg/l. WQI results for the post-monsoon season showed 36% of sampling sites as excellent, 52% good, 8% poor, and 4% very poor, while pre-monsoon results indicated 13% excellent, 46% good, and 42% poor. The research reveals higher toxin concentrations in drinking water during pre monsoon period compared to post monsoon, with increased salinity in freshwater aquifers making the water unsuitable for consumption. © 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Dynamic land use and coastline changes in active estuarine regions - A study of sundarban delta(International Society for Photogrammetry and Remote Sensing, 2014) Thomas, J.V.; Arunachalam, A.; Jaiswal, R.; Diwakar, P.G.; Kiran, B.Alteration of natural environment in the wake of global warming is one of the most serious issues, which is being discussed across the world. Over the last 100 years, global sea level rose by 1.0-2.5 mm/y. Present estimates of future sea-level rise induced by climate change range from 28 to 98 cm for the year 2100. It has been estimated that a 1-m rise in sea-level could displace nearly 7 million people from their homes in India. The climate change and associated sea level rise is proclaimed to be a serious threat especially to the low lying coastal areas. Thus, study of long term effects on an estuarine region not only gives opportunity for identifying the vulnerable areas but also gives a clue to the periods where the sea level rise was significant and verifies climate change impact on sea level rise. Multi-temporal remote sensing data and GIS tools are often used to study the pattern of erosion/ accretion in an area and to predict the future coast lines. The present study has been carried out in the Indian Sundarbans area. Major land cover/ land use classes has been delineated and change analysis of the land cover/ land use feature was performed using multi-temporal satellite images (Landsat MSS, TM, ETM+) from 1973 to 2010. Multivariate GIS based analysis was carried out to depict vulnerability and its trend, spatially. Digital Shoreline change analysis also was attempted for two islands, namely, Ghoramara and Sagar Islands using the past 40 years of satellite data and validated with 2012 Resourcesat-2 LISS III data.Item Modelling hydrologic regime of Lakshmanatirtha watershed, Cauvery river(Institute of Electrical and Electronics Engineers Inc., 2014) Ramachandra, T.V.; Nagar, N.; Vinay, S.; Aithal, B.H.Basic amenities such as clean water, air and food are essential not only for human livelihood but also for the surrounding biotic habitats in the environment for sustainable development. Due to the human habitation, and the anthropogenic activities, large scale change in land use has affected the hydrologic regime across watersheds. The water resource availability in a catchment depends upon the integrity of the land use, terrain and meteorological parameters such as rainfall, temperature, etc. The land use of the catchment plays an important role in maintaining the water flow in the rivers or streams as either surface or subsurface runoff (Pipeflow and Baseflow), holding water in the sub strata's, recharging the aquifers and hence catering the water demands as per the human and environmental needs. The study was conducted in order to understand the dynamics of land use and its implication on the catchment capabilities in catering the demands of environment (forests), agriculture, domestic and livestock needs on Lakshmanatirtha catchment of the Cauvery river basin which has an area of 3969 km2. The land use assessment using remote sensing and GIS showed the catchment is dominated (61.94%) by agriculture and horticulture, followed by forests with as area of 14.3% followed by other land uses. The Ghats (uplands) of the catchment is dominated by forests where as the plains are with agriculture and horticulture activities. Hydrologic assessment is done using the land use and the meteorological data was carried out at watershed level. The assessment showed that out of five watersheds, four of the watersheds had very high deficiency of water for over 3 months, and one of the watersheds had no deficit. The deficiency of water indicated that the watersheds were not able cater the both the human and environmental needs but also the streams were devoid of water flow which explains the deficiency in maintaining ecological flow. © 2014 IEEE.Item Drought monitoring for RABI season in upper Krishna river basin using remote sensing and GIS(Asian Association on Remote Sensing Sh1939murai@nifty.com, 2015) Chandran, C.; Dodamani, B.M.; Reddy, K.; Naseela, E.K.In this study, the upper Krishna river basin, lying in the state of Maharashtra has been chosen as study area. Two drought indices, SPI and NDVI, representing meteorological and agricultural droughts respectively, were calculated and analysed for the study area for a study period of 2000-2012. Using ArcGIS maps of the two types of droughts have been created to represent the spatial extent of the droughts. Further analysing the two indices, relevant relationships have been obtained between them.Item Hybrid intelligent bayesian model for analyzing spatial data(Springer Verlag service@springer.de, 2018) Velmurugan, J.; Venkatesan, M.Spatial data mining refers to the extraction of Geo Spatial Knowledge, maintaining their spatial relationships, along with other interesting patterns not explicitly stored in spatial datasets. The overall objective of this research work is to apply GIS based data mining classification modeling techniques to assess the spatial landslide risk analysis in Nilgris district, Tamilnadu, India. Landslide is one of the most important hazards that affect different parts of India in the every year. Landslides cover broad range impact on the people of the affected area in terms of the devastation caused to material and human resources. Landslide is generated by various factors such as rainfall, soil, slope, land use and land covers, geology, etc. Each landslide factor has a different level of values. The ranking of values and assignment of weight to the landslide factor gives good classification of landslide risk level. Data science and soft computing play major role in landslide risk analysis. The rank and weight are assigned to the landslide factor and its different levels using classification data science techniques. In this paper, we proposed a new model with integration of rough set and Bayesian classification called Hybrid Intelligent Bayesian Model (HIBM) to analyze the possibilities of various landslide risk level. The proposed model is compared with real-time data, and performance is validated with other data science models. © 2018, Springer Nature Singapore Pte Ltd.Item Environmental Engineering for Ecosystem Restoration—An Introduction(Springer Science and Business Media Deutschland GmbH, 2024) Vinod Chandra Menon, N.; Kolathayar, S.; Sreekeshava, K.S.; Bhargavi, C.This extensive volume addresses a range of environmental challenges and explores sustainable solutions across various domains. The research encompasses studies on paper consumption trends, thermal energy storage systems in green buildings, health risks associated with long-term noise exposure in urban areas, and passive design principles for buildings in cold and arid climates. The volume also delves into GIS-based assessments for ecosystem restoration, including groundwater quality in a smart city and spatiotemporal variability of short-term meteorological drought in semi-arid regions. Natural risk and vulnerability studies cover topics such as landslide vulnerability and the impact of changing climate on rainfall. Land use and land cover maps are analyzed for spatio-temporal changes using remote sensing and GIS tools. In the realm of industrial assessment, the volume addresses the treatment of dye-based effluents from various industries, focusing on electrochemical systems and adsorption analysis. Soft computing and numerical methods are applied to assess saltwater intrusion in inland aquaculture areas and predict ammonia levels in aquaculture. The volume also explores hydraulic structures' role in flood mitigation, with a focus on energy dissipation using a rigid stepped spillway. Groundwater suitability for irrigation is evaluated using electrical resistivity techniques. Solid waste management and green materials are extensively discussed, covering life cycle assessment in the silk textile industry, carbon footprint assessment of green concrete liners, and the effects of fly ash on concrete properties. Water quality assessment studies include analyses of borewell water for drinking purposes, groundwater quality modeling using artificial neural networks, and the application of phytoremediation for sullage treatment. The volume concludes with discussions on solid waste management in rural areas, with a focus on adaptation strategies, and quantification of water efficiencies in residential buildings. The study contributes to understanding environmental challenges and provides valuable insights for policymakers, researchers, and practitioners. Key themes include sustainable practices, environmental impact assessment, and the development of innovative technologies for waste treatment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item Efficient Parallel Algorithm for Detecting Longest Flow Paths in Flow Direction Grids(Institute of Electrical and Electronics Engineers Inc., 2025) Jayarukshi, K.; Agarwal, S.; Girish, K.K.; Goudar, S.; Bhowmik, B.High-performance computing (HPC) has transformed the capacity to address complex computational tasks across various scientific fields by enabling the efficient processing of large datasets and intricate simulations. In hydrological modeling, a critical task is identifying the longest flow channel within a catchment, which is essential for understanding water flow patterns and managing resources. However, existing geographic information system (GIS) algorithms for flow path identification often suffer from inefficiencies and inaccuracies. To address these challenges, this paper introduces innovative parallel methods utilizing Open Multi-Processing (OpenMP), a widely-used API that supports multi-platform shared-memory parallel programming. This approach optimizes the analysis of flow direction data, resulting in faster and more accurate identification of flow channels. The results demonstrate that the proposed method outperforms current approaches, offering substantial improvements in both performance and precision. These advancements have the potential to significantly enhance hydrological modeling practices and water resource management. © 2025 IEEE.