Faculty Publications
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Item Comparative study of ocean wave spectrum using ENVISAT SAR data and wave rider buoy data(2006) Pai, J.; Kumar, R.; Sarkar, A.; Hegde, A.V.; Dwarakish, G.S.A comparative study of ENVISAT ASAR data and corresponding wave rider buoy data has been attempted. An algorithm has been developed to retrieve Ocean Wave Spectrum from SAR data. The resulting spectrum is compared with the wave rider buoy measured wave spectrum. To compute the 2-D image spectrum from multi-look SAR data, various corrections to the original SAR data has been applied. Thereafter, Modulation Transfer Function has been computed and utilized to convert image spectrum to the Ocean Wave Spectrum. This final ocean wave height spectrum is used to estimate the ocean wave spectral parameters and has been compared with the in-situ measurements and model derived wave spectrum. An attempt has also been made to process the Single Look Complex (SLC) data to reduce the speckle noise in the SAR data using Fast Fourier Transform (FFT).Item Integrated coastal zone management plan and coastal zone information system for Mangalore Coast, West Coast of India(2006) Dwarakish, G.S.; Shetty, D.; Rajarama; Pai, J.; Natesan, U.In the present study, Integrated Coastal Zone Management Plan (ICZMP) has been developed for Mangalore Coast in Karnataka, along the West Coast of India, by analyzing the remotely sensed data and conventional data. The various data products used in the present study includes, IRS-1C LISS-III+PAN and IRS-P6 LISS IV remotely sensed data, Naval Hydrographic Chart and Survey of India (SOI) toposheets. Different thematic maps prepared in the present study includes, land use/ land cover map, bathymetry map, shoreline configuration map, transportation and drainage network maps, GPS survey map, CRZ map, contour map, DEM, inundation map and coastal erosion vulnerability map. The results of the present study are encouraging. Some of the specific conclusions of the study are; eight coastal vulnerability sites have been identified, significant increase in the built-up area and decrease in the agricultural land, no large scale erosion or deposition in the vicinity of coastal structures such as seawalls, breakwaters and entrance channel of New Mangalore Port Trust and the beaches along the Mangalore Coast are maintaining dynamic equilibrium. To get the online information about all these, Coastal Zone Information System (CZIS) has been developed through V. B. 6. 0. using results of various data analyses.Item Integrated coastal zone management plan for udupi coast using RS, GIS and GPS(2007) Dwarakish, G.S.; Vinay, S.A.; Dinakar, S.M.; Pai, J.; Mahaganesha, K.; Natesan, U.Coastal areas are under great pressure due to increase in human population and industrialization/commercialization and hence these areas are vulnerable to environmental degradation, resource reduction and user conflicts. In the present study an Integrated Coastal Zone Management Plan (ICZMP) has been developed for Udupi Coast in Karnataka, along West Coast of India. The various data products used in the present study includes IRS-IC LISS-III + PAN and IRS-P6 LISS III remotely sensed data, Naval Hydrographic Charts and Survey of India (SOI) toposheets, in addition to ground truth data. Thematic maps such as land use/ land cover map, bathymetry map, shoreline configuration map, transportation and drainage network maps, GPS survey map, CRZ map, contour map, DEM, inundation map, critical erosion area map were prepared. A Coastal Vulnerability Index has also been calculated for the study area to know the resistance of study area to sea level rise and is demarcated into four categories; Very high, High, Moderate and Low vulnerability, and a vulnerability map has been prepared. The results of the present study are encouraging. Some of the specific conclusions of the study are; about 50% study area is prone to erosion, river mouths along study area show shifting tendency towards south, and the beaches along the Udupi Coast are maintaining dynamic equilibrium. Coastal Zone Information System (CZIS) has been developed through V.B.6.0 using results of various data analysis.Item Determination of mixed layer depth from C-Band Synthetic Aperture Radar (SAR)(2010) Pai, J.; Kumar, R.; Sarkar, A.; Hegde, A.V.; Dwarakish, G.S.Oceanic internal waves are frequently observed on the continental shelf during the summer season, when the ocean is stratified. The appearance of internal wave phenomena in remote sensing images has been increasing the curiosity to observe internal wave at specific area in the world. Studies reveal that Synthetic Aperture Radar has a capability to detect internal waves. In the present study, ENVISAT Advanced Synthetic Aperture Radar (ASAR) image acquired on October 4, 2003, was used to determine Mixed Layer Depth (MLD) off Bay of Bengal of Indian Ocean region. The image showed several prominent trains of internal waves, with several wave packets in each train. The ocean was assumed to be a two layer system, and that the local semidiurnal tide is the generating force for the internal waves. By assuming that the local semidiurnal tide period is the generating source for these waves, and by measuring the distance between the wave packets, it is possible to derive the group velocity of the internal waves from Synthetic Aperture Radar (SAR) images directly. The mixed -layer depth is then derived by assuming the ocean as a two-layer finite depth model. The group velocity measured from the SAR image and the simulated group velocity by the two layer finite depth model was matched to get the mixed layer depth. The estimated mixed layer depth was 21m. This value show reasonably good agreement with the actual depth of 19.5m of in-situ ARGO buoy. © 2010 by IJI (CESER Publications).Item Addressing Spatial Variability in Estimating Cover Management Factor of Soil Erosion Models using Geoinformatics: A Case Study of Netravati Catchment, Karnataka, India(SAGE Publications Ltd, 2025) Makhdumi, W.; R, S.H.; Dwarakish, G.S.; Pai, J.Soil erosion is a significant threat to both agricultural productivity and natural resources. The most commonly applied soil erosion models are the Universal Soil Loss Equation (USLE) and its revised version (RUSLE), which rely heavily on the Cover Management factor (C factor) as a critical input parameter. This study aims to improve the accuracy of C factor estimates for the Netravati catchment present in the Western Ghats and Coastal Plains of India by using the Random Forest Algorithm and Sentinel 2 satellite data. The research examined five commonly used Normalized Difference Vegetation Index (NDVI) based C factor estimating equations and found that they inadequately represented local vegetation dynamics in the study area. To address this, a high-resolution Land Use Land Cover (LULC) map was generated using the Random Forest algorithm and in situ C factor values were assigned to LULC classes. A regression analysis between Sentinel 2-derived NDVI and the actual C factor yielded a novel equation. The proposed equation estimated C factor values ranging from 0.056 to 0.99, which closely align with actual observations and outperforming existing methods. The model’s performance was evaluated using statistical metrics, including a correlation coefficient of 0.984, mean absolute error of 0.048, root mean square error of 0.058, and Kling-Gupta efficiency of 0.921, indicating superior accuracy compared to existing methods. This study presents a region-specific approach for estimating the C factor, serving as a reliable tool for improving soil erosion predictions in the Western Ghats and Coastal Plains of India. Apart from highlighting the need for local parameterisation, the results have important implications for soil conservation planning, erosion risk management, and sustainable land use practices in the region. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).Item Shoreline change detection using DSAS and Land use/Land cover change analysis of Mangalore coast, southwest coast of India(Elsevier B.V., 2025) Bharath, N.; Swathi, K.K.; Dwarakish, G.S.; Shivanna; Pai, J.This study presents an integrated assessment combining Digital Shoreline Analysis System (DSAS) and multi-temporal Land Use/Land Cover (LU/LC) analysis to quantitatively link shoreline change and land use dynamics along the Mangalore coast, extending 26 km from Talapady in the south to Surathkal in the north. The objectives of the study were 1) to calculate the shoreline change rates for short and long periods along the study area with the help of the DSAS v5.1 tool in ArcGIS, and 2) to calculate LU/LC dynamics using remote sensing data from 1997 to 2022, including accuracy assessment of classifications. The shorelines were extracted by using conventional data (toposheet) and remote sensing data with multi-dated satellite images of Landsat 5, 7, 8 and 9 along with Resourcesat- LISS-?. The shoreline change rates are detected through two statistical methods: Endpoint rate-EPR(m/yr) and Linear regression rate-LRR(m/yr). The change analysis reveals that the coastline is highly eroded about ?3.24 m/yr (EPR) in the year 2000, and highly accreted about +3.99 m/yr (EPR) in 2009 compared to the 1970 shoreline. The long-term change analysis reveals that the coastline shows an average accretion rate of about 1.89 m/yr (LRR). Key limitations include potential errors in shoreline digitisation and spatial resolution constraints, which may impact rate precision. The study emphasises the urgent need for integrated coastal zone management to balance development pressures with environmental sustainability near the Ullal and Bengre regions, and highlights implications for achieving Sustainable Development Goal targets related to climate action and sustainable coastal ecosystems. © 2025 The AuthorsItem Coastal vulnerability assessment of the Kasaragod Coast in Kerala, West Coast of India(Springer Nature, 2025) N A, A.; Makhdumi, W.; G S, D.; Pai, J.Coastal zones are transition zones between the land and sea, characterised by unique coastal ecosystems and natural resources, making them the focal point of human activities. Vulnerability assessments have been carried out along several coastal zones across the world. These assessments help coastal scientists, engineers, and policymakers prepare plans and devise mitigation measures to safeguard the environment and coastal population against climate change and coastal hazard impacts. The present study evaluates the vulnerability of the Kasaragod coast in Kerala, the west coast of India, due to sea-level rise. Eleven variables, viz. relative sea-level change, mean significant wave height, tidal range, geomorphology, shoreline change rate, regional elevation, coastal slope, population, road/railway networks, tourist sites and land use/land cover are considered in the estimation of the Coastal Vulnerability Index (CVI). The resulting CVI values were categorized into low, moderate, high and very high vulnerability classes. Based on this classification, 41.33% of the Kasaragod sub-district and 13.26% of the Hosdurg sub-district fall under the ‘very high’ vulnerability category. A significant decrease in vulnerability was observed along the Kasaragod sub-district when socioeconomic variables were excluded from the CVI calculation. However, in the Hosdurg sub-district exclusion of the socioeconomic variables led to increased vulnerability along the coast. The vulnerability maps developed in this study provide a crucial tool for identifying highly vulnerable coastal stretches and guiding effective strategies to safeguard the Kasaragod coast and its communities. © The Author(s) 2025.