Faculty Publications
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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 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 Terrestrial chemical spill information system through remote sensing, GIS and V.B. 6.0(2008) Dwarakish, G.S.; Angel, J.S.; Srinikethan, G.; Natesan, U.India has made remarkable progress in creating a modern and diversified industrial base, since its independence. Most of the refineries, petrochemical and fertilizer industries are located in the coastal zone and catered by 12 major ports along the 7500 km length of Indian coastline. Since, transportation of crude oil and POL products from ports to refineries are mostly by pipelines, rail/road, besides some quantity by barge/ships along the coast, there will be chances of oil spill/leakage. Managing these events before and during their occurrence is imperative to the protection of people and natural resources. The present study was carried out with a view to develop Terrestrial Chemical Spill Information System [TCSIS], using Remote Sensing [RS], GIS and VB 6.0., for the Mangalore coastal zone industrial area of Dakshina Kannada district, Karnataka state, along West Coast of India. The study area lies between 74°45′00″ to 74°52′30″E longitude and 12°52′30″ to 13°00′00″N latitude. The database of TCSIS consists of both conventional data and RS data, and analysed using ERDAS Imagine 9.0 and ArcGIS 8.3 software. Different thematic maps prepared include LU/LC map, drainage map, road and pipeline network map, slope map, Digital Elevation Model, relative risk maps and pipeline route for the transportation of hazardous chemicals from port to refinery. The TCSIS module developed using RS, GIS and V.B. 6.0, characterizes the ability of a spilled chemical to immediately impact human health, natural resources, and incorporates these into an overall measure of terrestrial chemical risk and aids in planning, preventing and responding to a terrestrial chemical spill. © 2008 SPIE.Item Lossless compression of digital mammography using fixed block segmentation and pixel grouping(2008) Kumar, R.; Koliwad, S.; Dwarakish, G.S.A mammography is a specific type of imaging that uses low-dose x-ray system to examine breasts. This is an efficient means of early detection of breast cancer. High resolution is a common characteristic of such images. Archiving and retaining these data for at least three years is expensive, difficult and requires sophisticated data compression techniques. In this paper an efficient method is proposed for lossless compression of mammography images. After performing de-correlation of the image using two efficient predictors, the residue image is divided into 4x4 blocks. The blocks with all-zero pixels are identified using one bit code. Later, Second order of pixel grouping is employed to the remaining blocks to increase the coding efficiency. Such blocks are coded using Base offset method. Special techniques are used to save the header information. The method is tested using 25 mammograms from the MIAS database, each having a resolution of 1024x1024 pixels with 8 bits/pixel. Experimental results indicate better compression ratio when compared to JPEG 2000, JPEG-LS, PNG and JBIG. © 2008 IEEE.Item Modified self - Adaptive Plateau Histogram Equalization with mean threshold for brightness preserving and contrast enhancement(2013) Raju, A.; Dwarakish, G.S.; Venkat Reddy, D.Histogram Equalization (HE) is a simple, effective and widely used contrast enhancement technique as it can automatically define the intensity transformation function based on statistical characteristics of the image, but it tends to change the mean brightness of the image to the middle level of the gray level range. HE also produces saturation effects by extremely pushing the intensities towards the right or the left side of the histogram. To surmount these drawbacks, Clipping or Plateau Histogram Equalization techniques for brightness preserving and contrast enhancement have been proposed, but, these are not suitable for automatic systems because of manual selection of threshold level. Self-Adaptive Plateau Histogram Equalization (SAPHE) selects the threshold level automatically, but the process is relatively complicated and sometimes fails in execution. To overcome these drawbacks, a Modified Self - Adaptive Plateau Histogram Equalization with Mean threshold (Modified SAPHE-M) is proposed in this paper and compared the experimental results with Histogram Equalization (HE), Self-Adaptive Plateau Histogram Equalization (SAPHE) and Modified Self-Adaptive Plateau Histogram Equalization (Modified SAPHE) by using image quality measures such as Absolute Mean Brightness Error (AMBE) and Peak-Signal to Noise Ratio (PSNR). © 2013 IEEE.Item Satellite image contrast enhancement algorithm based on Plateau Histogram Equalization(Institute of Electrical and Electronics Engineers Inc., 2014) Raju, R.; Dwarakish, G.S.; Venkat Reddy, D.The quality of remotely sensed satellite images depends on the reflected electromagnetic radiation from earth surface features. Lack of consistent and similar amounts of energy reflected by different features from earth surface, results a low contrast satellite image. Enhancement of contrast is needed for satellite images to identify and extract objects from images, where features are essential in studying earth applications. In this paper, a new contrast enhancement technique for satellite images based on clipping or plateau histogram equalization has been proposed. The technique adopted Bi-Histogram Equalization with Plateau Limit (BHEPL) for image decomposition and Self-Adaptive Plateau Histogram Equalization (SAPHE) for threshold calculation. The proposed method has been compared with existing methods such as Histogram Equalization (HE), Brightness Preserving Bi-Histogram Equalization (BBHE), Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE), Dynamic Histogram Equalization (DHE), Bi-Histogram Equalization with Plateau Limit (BHEPL) and Self-Adaptive Plateau Histogram Equalization (SAPHE) with image quality measures such as Absolute Mean Brightness Error (AMBE) and Peak-Signal to Noise Ratio (PSNR). © 2014 IEEE.Item Weekly prediction of tides using neural networks(Elsevier Ltd, 2015) Salim, A.M.; Dwarakish, G.S.; Liju, K.V.; Thomas, J.; Devi, G.; Rajeesh, R.Knowledge of tide level is essential for explorations, safe navigation of ships in harbour, disposal of sediments and its movements, environmental observations and in many more coastal engineering applications. Artificial Neural Network (ANN) is being widely applied in coastal engineering field for solving various problems. Its ability to learn highly complex interrelationships based on the provided data sets, along with less amount of data requirement, makes it a powerful modelling tool. The present work is related to predicting the hourly tide levels at Mangalore, Karnataka, using a week's hourly tidal levels as input. The data has been obtained from NMPT, Mangalore and is made use of in predicting tide level using Feed Forward Back Propagation (FFBP) and Non-linear Auto Regressive with eXogenous input (NARX) network. FFBP network yielded correlation coefficient value of 0.564 and NARX network yielded very high correlation coefficient of the order 0.915 for predictions of yearlong hourly tide levels. The study proves that ANN technique can be successfully utilized for the prediction of tides at Mangalore. © 2015 Published by Elsevier Ltd.Item Assessment of spatial variability of soil physical and hydraulic properties in Netravati catchment, Karnataka State, India(Institute of Electrical and Electronics Engineers Inc., 2015) Ganasri, B.P.; Dwarakish, G.S.Site specific management and precision agriculture seeks to identify and analyze variability in soil properties. Runoff prediction and sediment yield estimation using distributed hydrologic modeling requires spatially distributed soil data especially saturated hydraulic conductivity, water content and particle size distribution. Therefore, soil data becomes one of the major inputs in any watershed management studies. The present study was conducted to analyse spatial variability in soil physical and hydraulic properties in Netravati river basin, Karnataka State, India. The spatial interpolation of soil properties was carried out by using three methods such as Ordinary Kriging (OK), Inverse Distance Weighting (IDW) and Radial Basis Function (RBF). Results indicate that soil properties such as %sand, %silt and %clay are highly variable in nature with standard deviation value of 16.08, 13.27 and 8.82. The OK method is efficient in predicting sand, silt, clay and saturated hydraulic conducted. IDW and RBF methods predicted organic matter content and bulk density with acceptable error of 1.084%, 1.09% and 0.05gm/cc, 0.04gm/cc respectively. © 2015 IEEE.