Conference Papers
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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.Item Identification of Road Traffic Crash Blackspots on National and State Highways in Trivandrum, India Using Kernel Density Estimation(Springer Science and Business Media Deutschland GmbH, 2025) Anil, A.B.; Sam, S.E.; Suresha, S.N.The paper presents a comprehensive study on road traffic accidents (RTAs) in the Trivandrum district of Kerala, India, emphasizing the high incidence of fatalities and injuries, particularly on National and State Highways. The study utilizes Geographic Information System (GIS) technology to analyze spatial and temporal patterns of RTAs, employing Kernel Density Estimation (KDE) to identify accident as Blackspots, in the Thiruvananthapuram district. The study spans three years, from 2020 to 2022. It includes detailed crash data, including collision types, accident severity, weather conditions, road types, and junctions, revealing insights such as the prevalence of head-to-head collisions and the influence on accident rates. The Severity Index (SI) is introduced as a metric to quantify accident gravity. The research aims to identify blackspots for improving safety measures, ultimately contributing to the well-being of road users in Kerala. The findings underscore the urgent need for targeted road safety measures and infrastructure improvements to mitigate the risk of RTAs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.Item Accident Prediction Model for Horizontal Curves on State Highways Using Spatial Variation(Springer Science and Business Media Deutschland GmbH, 2025) Pandey, S.K.; Mulangi, R.H.; Sanganaikar, R.S.; Babu, K.R.N.N.Accidents have become one of the primary cause of fatalities on highways. Road accidents are one of the significant issue around the globe, but in context of India, the severity is more due to immense growth in road networks and traffic capacity. Curve are at higher range of potential risks of accidents because of inadequate sight distance and speed measures. This study aims to develop accident prediction model using regression analysis. Location selected for study was State Highway-1 in Udupi district, Karnataka. Ten curves are selected on the road and comparative study of model prepared is checked to verify the model reliability. Datasets used for model calibration and development is Highway Geometric data, past accidents records, and spot speed of vehicles. Geometric data for the road sections are obtained from satellite imageries, and GIS data and speed data are collected using speed camera. Model generation was done using statistical computing by using multi-linear regression. The model showed that curve details and speed reduction between successive features were strongly related to accident frequency. Sharper curves are more tend to accidents, and speed reduction is higher at curves with smaller radius. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.Item Comparative Analysis of Braiding Intensity of Kosi River Using Remote Sensing and GIS(Springer Science and Business Media Deutschland GmbH, 2025) Aman, A.L.; Dwarakish, G.S.The Kosi river is one of the major tributaries of river Ganga which is well known for change of its course. It originates from Tibet and after travelling through Himalaya and plains of Bihar, it joins river Ganga. The river carries huge sediment and, s accumulation of sediment causes formation of sand bars in the river. The downstream region of Birpur barrage is highly affected by this shifting tendency of the river. The satellite images of the river for year 1992, 2004 and 2016 were obtained to analyze the evolution in braiding of the river for two decades. The braiding intensity was measured by using the different braiding indices given by Brice, Rust and Sharma and compared in this study. The study area has been divided into four reaches and the braiding intensity for each of them were calculated. The braiding intensity by Brice varies from 2.38 to 4.93, from 1.06 to 1.75 as given by Rust and 2.45 to 6.5 by Sharma. The calculated braiding intensity indicates the overall decrease of braiding in the area. This study will be helpful to get an idea about the change in braiding intensity of the Kosi River in the downstream side of Birpur Barrage and about future changes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.