Faculty Publications
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Item Assessment of Changes inWetland Storage in Gurupura River Basin of Karnataka, India, Using Remote Sensing and GIS Techniques(Springer Science+Business Media, 2018) Kundapura, S.; Kommoju, R.; Verma, I.In view of the significant importance of wetlands in the ecosystem and regional economy, an attempt has been made to analyze the impact of land use/land cover dynamics and other contributing factors on spatial status of Gurupura river basin wetland ecosystem located in Karnataka region. The impact assessment has been carried out by analyzing the multi-temporal changes in the storage capacities of wetlands in the watershed, by using remote sensing data of LISS-III. The multi-temporal land use/land cover statistics will reveal the significant changes that have taken place over time in the watershed. The runoff generated can be easily calculated from this information which gives an idea of the total input into the system. In response to these upstream watershed changes, wetland has exhibited changes in spatial extension, structure, and hydrological characteristics. As a consequence of continuously changing land use/land cover characteristics and unpredictability of the monsoon, the wet land ecosystems have exhibited considerable changes in spatial extent and their storage capacities. Overall, there has been degradation in the storage capacities of the wetland ecosystems of the region causing a multitude of adverse effects such as increase in floods and submergence of mainland. © Springer Nature Singapore Pte Ltd. 2019.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 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 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 A Framework for Quality Enhancement of Multispectral Remote Sensing Images(Institute of Electrical and Electronics Engineers Inc., 2018) Suresh, S.; Das, D.; Lal, S.Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images. © 2017 IEEE.Item Optimal Band Selection Using Generalized Covering-Based Rough Sets on Hyperspectral Remote Sensing Big Data(Springer Verlag service@springer.de, 2019) Kelam, H.; Venkatesan, M.Hyperspectral remote sensing has been gaining attention from the past few decades. Due to the diverse and high dimensionality nature of the remote sensing data, it is called as remote sensing Big Data. Hyperspectral images have high dimensionality due to number of spectral bands and pixels having continuous spectrum. These images provide us with more details than other images but still, it suffers from ‘curse of dimensionality’. Band selection is the conventional method to reduce the dimensionality and remove the redundant bands. Many methods have been developed in the past years to find the optimal set of bands. Generalized covering-based rough set is an extended method of rough sets in which indiscernibility relations of rough sets are replaced by coverings. Recently, this method is used for attribute reduction in pattern recognition and data mining. In this paper, we will discuss the implementation of covering-based rough sets for optimal band selection of hyperspectral images and compare these results with the existing methods like PCA, SVD and rough sets. © 2019, Springer Nature Singapore Pte Ltd.Item An efficient image retrieval system for remote sensing images using deep hashing network(Springer, 2020) Valaboju, S.; Venkatesan, M.Due to the huge increase in volumes of remote sensing images, there is a requirement for retrieval systems which maintain the retrieval accuracy and efficiency which requires better learning of features and the binary hash codes which better discriminate the images of different classes of images. The existing retrieval systems for remote sensing images use CNNs for feature learning which fails to preserve the spatial properties of an image which in turn affect the quality of binary hash code and the retrieval performance. This Paper tries to address the above goals by using (1) Extracting Hierarchical features of convolutional neural network and using them to sequential learning to better learn the features preserving spatial and semantic properties. (2) Use lossless triplet loss with two more loss functions to generate the binary hash codes which better discriminate the images of different classes. The proposed architecture consists of three phases: (1) Fine-tuning a pre-trained model. (2) Extracting the hierarchical features of convolutional neural network. (3) Using those features to train the deep learning-based hashing network. Experiments are conducted on a publicly available dataset UCMD and show that when hierarchial convolutional features are considered there is a significant improvement in performance. © Springer Nature Singapore Pte Ltd 2020.Item High-resolution mapping of soil properties using aviris-ng hyperspectral remote sensing data—a case study over lateritic soils in mangalore, india(Springer Science and Business Media Deutschland GmbH, 2021) Chitale, M.M.; Kundapura, S.Quick and accurate mapping of properties of soil is considered to be critical for agriculture and environmental management. Rapid assessment of soil properties is a daunting task in monitoring the environment. The conventional field sampling is a laborious as well as time-consuming job. The conventional methods are restricted to a specific region but there is a need to analyses the soil properties at landscape levels. Hence, this study emphasises on hyperspectral remote sensing which to some extent helps in rapid assessment of the properties. The hyperspectral data used for the study is AVIRIS-NG data. The study explored the potential of AVIRIS-NG hyperspectral data in mapping soil properties which were analysed by in situ laboratory methods and compared with them by geostatistical method of spatial interpolation. Hence, the method adopted for this purpose is the study on spatial variability of soil properties by using Kriging interpolation technique. Also, a review study is carried out on the visible and near-infrared analysis (VNIRA), multiple regression analysis approach and spectral angle mapper supervised classification technique on the high-resolution AVIRIS-NG Hyperspectral data, which will yield as an empirical model for predicting the soil property in question from both wet chemistry and spectral information of a representative set of samples and classifies the data accordingly. © Springer Nature Singapore Pte Ltd 2021.Item Recent Advances in Earthquake Engineering—An Introduction(Springer Science and Business Media Deutschland GmbH, 2022) Chian, S.C.; Kolathayar, S.This chapter summarizes the contents of the book volume on Recent Advances in Earthquake Engineering which discusses various relevant topics such as Seismic ground motion studies, Structural and geotechnical vulnerability assessment, Retrofitting and rehabilitation, Review of building codes, as well as more recent technological introduction of geospatial tools and geographical information systems. Cascading disasters such as fire hazards following an earthquake are also discussed in this volume. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.