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 Assessment of Soil Loss in Wet Tropical Region: A Case Study in Kumaradhara Basin, Western Ghats, India(Springer Nature, 2024) Roopa, N.; Ramesh, H.; Dhanush, B.M.; Meghana, C.S.Degradation of land resources and soil erosion are major issues affecting the productivity of the land. To design appropriate regional land management approaches using field data, an evaluation is a requirement to ascertain the extent and severity of soil degradation. Western Ghats of India is one of 34 global biodiversity hotspots, and habitat degradation has been causing havoc in this area for decades. The Kumaradhara River is a dominant part of wet tropical forested land on the Western side of the Western Ghats. The Hongadahalla and Kadumanehalla Rivers are tributaries of the Kumaradhara River. Mookanamane, Bidahalli, and Marenahalli are sub-catchments covering parts of the rivers Hongadahalla, and Kadumanehalla, having catchment areas of 41 km2, 33 km2, and 64 km2, respectively. The primary goal of the current study is to use the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information Systems (GIS) to estimate annual erosion rates and develop a soil loss map for the year 2021 for the mountainous watershed of Kumaradhara. The geo-environmental data were collected from Indian Meteorological Department, Earth Explorer, and the National Bureau of Soil Survey and Land Use Planning. The impacts of rainfall erosivity, soil erodability, slope length and steepness, cover management, and conservation practice variables on mean annual soil loss in the study were calculated using GIS data layers. The quantitative results and analysis of soil erosion estimated by the RUSLE model ranged from 29.56 to 7992.89 t ha−1 year−1 in Mookanamane, 25.6 to 20,494.12 t ha−1 year−1 in Marenahalli, and 21.6 to 15,265.25 t ha−1 year−1 in Bidahalli. It has been observed that the risk of soil erosion in forests is low in the study area, whereas the risk of soil erosion on barren land is moderate. The study results shall create terrain management and planning strategies in environmentally sensitive mountainous areas. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Item Importance of geology and soil survey for mobile communication site planning using RS/GIS technology(2010) Naveenchandra, B.; Lokesh, K.N.; Usha; Gangadhara Bhat, H.G.Geology and Soil survey constitutes a valuable resource inventory linked with the survival of life on the earth. The technological advancements in the field of remote sensing and Geographical Information System have been a boon for such surveys. The present paper describes the role of Remote sensing and Geographical Information System (GIS) technologies for geological mapping and characterizing the importance of soils at various scales for identification of suitable sites for mobile communication network. Cellular network design is becoming more and more important since the network quality is highly dependent on the distribution of base stations. To design a cellular network for a particular region efficiently and accurately, the site suitability is an important determination. The country's mobile services market is forecast to grow by a compound annual rate of 28.3% in next five years. India is a vibrant market from communications point of view. The subscriber base in the wireless market in India, the world's fastest growing telecom market reached another milestone when it surpassed 200 million subscribers in Aug 2008. At present there are around 54000 cell sites operated by different GSM/CDMA operators. This number would further go up to 80,000 in next couple of years. To serve an increasing number of users requires an increasing number of base stations. Thus, operators must carefully plan the deployment and configurations of radio base stations to support voice and data traffic at a level of quality expected by customers. The present study carried out in the Udupi district of Karnataka State based on IRS 1C/1D LISS-III and CARTOSAT-1 satellite data. Various thematic maps like geology, soil, geomorphology, slope and land use/land cover with DEM has helped in understanding the terrain in a better way. The multi spectral satellite data in conjunction with SuperGIS, SuperPad and Getac GPS hardware have helped to formulate suitable plans and strategies for an effective Telecom planning and development in Udupi district. © 2010 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.Item Vegetation dynamics in a tropical river basin inferred from MODIS satellite data(2013) Laxmi, K.; Nandagiri, L.The objective of this study was to analyze temporal and spatial dynamics of vegetation and land use/land cover (LU/LC) characteristics in a humid tropical river basin originating in the forested Western Ghats mountain ranges using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. Both intra-annual and inter-annual variations in the parameters related to vegetation were analyzed in the Netravathi river basin (3314 km2) which is located in Karnataka State, India. MODIS data products on Land Surface Temperature and Reflectance were used as input to map the pixel-wise variations in albedo, Normalized Difference Vegetation Index (NDVI), Fraction of Vegetation (Fr) and Land Surface Temperature (LST) for two dates each (summer and winter) during the years 2002 and 2006. The fact that 2002 experienced a relatively wet summer followed by a relatively dry winter and 2006 experienced opposite conditions, proved useful in interpreting variations as influenced by wetness conditions. Overall results indicated significant variability in the parameters for major LU/LC classes of evergreen /semievergreen forest, scrub forest and agriculture. While albedo values appeared quite sensitive to wetness conditions, NDVI (and Fr) exhibited significant seasonal changes for some LU/LC classes but remained largely unaffected by wetness conditions. LST values corrected for elevation effects (LST*) were influenced by both LU/LC and wetness conditions. Differences in LST* values were as high as 70K between summer and winter of 2006 for some LU/LC classes. Lowest temperatures were recorded for the evergreen/ semievergreen forest class. Similar inferences could be drawn when variations in parameters were analyzed for 20 selected pixels located at different elevations and possessing each of the eight LU/LC classes. The methodology proposed in this research may prove to be useful in regional scale monitoring and mapping of tropical forests and other LU/LC categories in a convenient and cost-effective manner. MODIS satellite data products used in this study provides information on surface characteristics at a reasonable resolution. This permits identification of not only differences in LU/LC classes but also on changes in surface characteristics as influenced by season and wetness conditions. © 2013 CAFET-INNOVA TECHNICAL SOCIETY.Item Hydrological responses to land use/land cover change in Tikur Wuha Watershed in Southern Ethiopia(Springer Science and Business Media Deutschland GmbH, 2022) Ketema, A.; Dwarakish, G.S.; Makhdumi, W.Due to its diverse environmental impacts, change in land use/ land cover (LU/LC) has become a global concern. LU/LC change is a critical factor that directly impacts watershed hydrology. The study intends to assess the LU/LC dynamics and their impacts on the streamflow of the Tikur Wuha watershed (TWW) in Ethiopia. LU/LC change was assessed using Landsat images. Each image is classified using a maximum likelihood algorithm of the supervised classification method. The Soil and Water Assessment Tools (SWAT) model were used to examine the impact of LU/LC change on streamflow. The overall accuracy of the LU/LC maps ranged from 77.50 to 87.33%. The findings demonstrated an increase in built-up and cultivated areas and a decrease in shrubland, grassland, swampy areas, and water bodies. The calibration and validation results showed a reasonable performance rate of the SWAT model. The LU/LC changes, which occurred between 1978 and 2017, had increased the average annual streamflow by 8.12%, 9.78%, and 14.77% between 1978 and1988, 1978 and 1998, 1978 and 2017. The Kiremt season flow increased by 9.80% during the first half of the study period (1978–1998) and by 5.41% in the second half (1998–2017). It is risen by 15.74% in 2017 compared to in 1978. The observed changes in the streamflow have resulted from LU/LC changes in the TWW. The study suggests that quick action is required to manage the LU/LC shift and execute land use planning to ensure water availability in the watershed. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Item Dual attention guided deep encoder-decoder network for change analysis in land use/land cover for Dakshina Kannada District, Karnataka, India(Springer Science and Business Media Deutschland GmbH, 2023) Naik, N.; Chandrasekaran, K.; Sundaram, V.M.; Prabhavathy, P.The Earth is frequently changed by natural occurrences and human actions that have threatened our environment to a certain extent. Therefore, accurate and timely monitoring of transformations at the surface of the Earth is crucial for precisely facing their harmful effects and consequences. This paper aims to perform a change detection (CD) analysis and assessment of the Dakshina Kannada region, being one of the coastal districts of Karnataka, India. The spatial and temporal variations in land use and land cover (LULC) are being monitored and examined from the data received as LULC maps from the National Remote Sensing Agency, Indian Space Research Organization, India. The time-series data from advanced wide-field sensor (AWiFS) Resourcesat2 satellite as LULC maps (1:250k) are analyzed using a deep learning approach with an encoder–decoder architecture with dual-attention modules for the change analysis. The model provides an overall accuracy and meanIOU(intersection over union) of 94.11% and 74.1%. The LULC maps from 2005 to 2018 (13 years) are utilized to decide the variations in the LULC, including urban development, agricultural variations, vegetation dynamics, forest areas, barren land, littoral swamp, and water bodies, current fallow, etc. The multiclass area-wise changes in terms of percentage show a decline in most LULC classes, which raises a point of concern for the environmental safety of the considered area, which is highly exposed to coastal flooding due to increased urbanization. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Item Assessing the Impacts of Land Use, Land Cover, and Climate Change on the Hydrological Regime of a Humid Tropical Basin(American Society of Civil Engineers (ASCE), 2023) Abraham, A.; Kundapura, S.Climate change and land use land cover (LULC) change are two major factors influencing river basin hydrology. This study explored these drivers' isolated and combined impacts on the ecologically relevant flow in the Achencoil basin, Kerala, India. The LULC classification in the study is carried out with the Random Forest (RF) algorithm in the Google Earth Engine (GEE) platform, and Land Change Modeler (LCM) is incorporated for change detection and projection. The future climate data from the National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) is used for climate change impact assessment. The Soil and Water Assessment Tool (SWAT) is employed to simulate streamflow under LULC and climate change scenarios. The historical and projected future LULC change in the basin revealed an increase in the built-up and barren land, with a significant decrease in agricultural and forest areas. The results show that the projected future precipitation will decrease under the RCP 4.5 and increase under the RCP 8.5 scenario. The projected average maximum and minimum temperature are expected to increase under both scenarios in the basin. The LULC 2050 scenario shows the most significant rise in average annual streamflow, at 7.5%. Whereas in the climate change scenarios, the average annual flow decreases under RCP 4.5 and increases under RCP 8.5. The combined impacts of climate change and LULC change are relatively higher than the isolated effects of these drivers in the basin. The study outcomes are expected to help policymakers consider the effect of climate change and LULC change on the river's hydrology so as to implement the management activities that account for the riverine ecosystem. © 2023 American Society of Civil Engineers.Item Multi-spatial-scale land/use land cover influences on seasonally dominant water quality along Middle Ganga Basin(Springer Science and Business Media Deutschland GmbH, 2023) Krishnaraj, A.; Honnasiddaiah, R.Studying spatiotemporal water quality characteristics and their correlation with land use/land cover (LULC) patterns is essential for discerning the origins of various pollution sources and for informing strategic land use planning, which, in turn, requires a comprehensive analysis of spatiotemporal water quality data to comprehend how surface water quality evolves across different time and space dimensions. In this study, we compared catchment, riparian, and reach scale models to assess the effect of LULC on WQ. Using various multivariate techniques, a 14-year dataset of 20 WQ variables from 20 monitoring stations (67,200 observations) is studied along the Middle Ganga Basin (MGB). Based on the similarity and dissimilarity of WQPs, the K-means clustering algorithm classified the 20 monitoring stations into four clusters. Seasonally, the three PCs chosen explained 75.69% and 75% of the variance in the data. With PCs > 0.70, the variables EC, pH, Temp, TDS, NO2 + NO3, P-Tot, BOD, COD, and DO have been identified as dominant pollution sources. The applied RDA analysis revealed that LULC has a moderate to strong contribution to WQPs during the wet season but not during the dry season. Furthermore, dense vegetation is critical for keeping water clean, whereas agriculture, barren land, and built-up area degrade WQ. Besides that, the findings suggest that the relationship between WQPs and LULC differs at different scales. The stacked ensemble regression (SER) model is applied to understand the model’s predictive power across different clusters and scales. Overall, the results indicate that the riparian scale is more predictive than the watershed and reach scales. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Item Integration of multi-layer perceptron neural network and cellular Automata-Markov chain approach for the prediction of land use land cover in land change modeler(Elsevier B.V., 2025) Choudhary, P.; Devatha, C.P.; Azhoni, A.Land use and land cover (LULC) significantly influence the hydrological cycle and various earth processes. Understanding these dynamics is essential for effectively managing environmental issues within river basins. The study focuses on a highly dynamic and flood-prone sub-basin of the Upper Krishna River, where major urban settlements and intensive agricultural activities are concentrated along the riverbanks. The uniqueness of this research comes from the selection of this hydrologically sensitive landscape, shaped by both natural processes and anthropogenic pressures, which presents a critical case for land use and land cover modeling. Utilizing high-resolution satellite data (10 m), combined with the advanced Multi-Layer Perceptron Neural Networks (MLPNN) and Cellular Automata-Markov Chain (CA-Markov) modeling techniques within TerrSet's Land Change Modeler (LCM), which is not only capable of generating spatial transitions and dynamic maps but also identifies the key contributors in gain and loss of various land use classes. We projected LULC scenarios for the mid-century (2049) and end-century (2099) using data from 2015 to 2020. Our model was validated against the actual LULC map from 2024 and showed a strong correlation (Kappa = 0.85). The results indicate significant urban growth along the riverbank and predict an increase in built-up area from 6.53 % in 2024 to 9.59 % in 2049 and further to 15 % by 2099 of the total geographical area. We observed consistent declines in forest cover, cropland, and barren land. These findings are valuable for future hydrological studies and provide important insights for policymakers to support sustainable urban planning and flood risk management. © 2025