Browsing by Author "Umesh, P."

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AN ECONOMICAL APPROACH TOWARDS BATHYMETRIC MAPPING OF SHALLOW WATER BASINS USING UNMANNED SURFACE VESSEL
(American Society of Mechanical Engineers (ASME), 2022) Shetty, D.; Kotian, R.; Sequeira, S.L.; Pavithra, N.R.; Umesh, P.; Gangadharan, K.V.
In recent years, the use of unmanned vehicles has advanced because of a growing number of civil applications such as firefighting or non-military security work, such as surveillance of pipelines etc. The application of these technologies with decreased cost and size has received attention in both civil and military applications. Recent advances in sensors, modeling and simulation and availability of open-source software and hardware for data integration has created an environment of remotely monitoring that was not possible a few years ago. This paper examines a niche cost-effective, portable Unmanned Surface Vessel that has been designed to capture the bathymetric profile of shallow water basins using single beam echosounder. Bathymetry is the measurement of the depth of water in oceans, rivers, or lakes. Bathymetric maps look a lot like topographic maps, which use lines to show the shape and elevation of land features. Today, echo sounders are used to make bathymetric measurements. Global shallow water bathymetry maps offer critical information to inform activities such as scientific research, environment protection, and marine transportation. Accurate mapping of shallow bathymetry is critical for understanding and characterizing coastal environments providing a foundation for measuring underwater light density, mapping and monitoring and planning marine operations and transportation. Methods for estimating shallow water bathymetry have suffered from a variety of trade-offs and limitations. Conventional methods such as shipborne sounding or airborne LiDAR have limited spatial coverage. The unit described in this paper has been designed and has been trained to acquire data in a predefined set path, minimizing the human intervention and the associated errors. A successful trial run was done for mapping the bed profile of the river basin in India. The vessel has been upskilled for capturing sonar data sets, with water quality parameters and soil samples using an automated auger. The vessel functions using the combined various open-source software and hardware tools for data assimilation, while the captured data sets are real- time transferred using IOT to Ground Controlled Station. The tropical river basin chosen is a part of Netravati River located in Dakshina Kannada District, Karnataka, India. This area is a part of the monsoon belt, and the Netravati riverbed is subjected to heavy sand deposition during a part of the year. The data on the excessive sand deposition is of immense value to the district and state administration. This study has been carried out at a frequency of 30 days and is provided as an input during non- monsoon period for district administration for outlining removal of excessive sand deposition monitoring of water quality in the estuarine ecosystem. The work done is a one-of-a-kind pilot study developed in-house using the recent advances seen in the world of open-source platforms. This paper demonstrates a unique application that is of value to the state administration in decision making and in addition contributes to environmental monitoring of the riverbed. Â© Â© 2022 by ASME.
An exploratory analysis of rainfall: A case study on western ghats of India
(IEOM Society ieom-society@iieom.org, 2018) Rao, P.S.B.; Shetty, S.; Umesh, P.; Shetty, A.
In this study high resolution 0.250 Ã—0.250 (approximately 25KmÃ—25Km) gridded daily rainfall data is used to analyze the effect of changing climate on distribution of rainfall in different topographical zones of Western Ghats (WG) of India over the period 1901-2013. The non parametric two tailed Mann- Kendall with Hamed and Rao's method of autocorrelation and Sen's slope estimator for obtaining magnitude of change over time period is used. The rainfall trend in annual, monsoon and post-monsoon is increasing in state of Goa and Coastal region of Karnataka state and significantly decreasing in some part of Kerala and Maharashtra state. Winter season rainfall has seen a declined trend in southern part of the study area and in high elevated region of Kerala state. Even the mean rainfall over the study area is declining from 1951-1960 with disturbance in alternate sequence of flood and drought year from period 1990. The frequency of heavy rainfall events (65mm-124.4mm) are increasing in recent decades with 40-50% contribution from 2000-2013 in regions of Maharashtra state. The trend of heavy rainfall events are increasing in West Coast of India at 5% significance level with no trend in very heavy to extreme rainfall events (>124.5mm). Â© IEOM Society International.
An exploratory analysis of urbanization effects on climatic variables: a study using Google Earth Engine
(Springer Science and Business Media Deutschland GmbH, 2022) Shetty, A.; Umesh, P.; Shetty, A.
Rapid global economic expansion has resulted in a drastic increase of urbanization while impacting the Earth’s entire ecology. This study evaluates the impact of historical land-use/land-cover (LU/LC) change signatures on seasonal variation of climatic variables using a cloud platform-Google Earth Engine. Due to rapid urbanization and the noticeable spatio-temporal difference in the climate, administrative units of Dakshina Kannada district are taken for demonstration. The LU/LC of the district extracted from high-resolution images of Landsat using random forest classification, land surface temperature (LST) extracted from the thermal band of Landsat images using the mono window algorithm, evapotranspiration (ET) data extracted from MOD16A2.006 and precipitation data from CHIPRS was used. The data was extracted for the pre-monsoon and post-monsoon period 2001–2019. The district has seen a 13.67% reduction in the forest area with 18.81% increase in the built-up areas. The LST and ET has seen a progressive drift in the past two decades, with an increase of 4.07 °C in median temperature in forest areas and a decline of 2.19 mm in median ET value, which necessitates monitoring forest encroachment. The higher variation in maximum LST in built-up land (0.36∘C/year/sq.km) (near the industrial area) indicates that LU/LC change signature is the predominant driving factor and is associated with the physical characteristics of the built-up area. The ET exhibited a decreasing rate of 0.62 mm/year/sq.km of the built-up land. This study highlights the power of Google Earth Engine and free availability of satellite data in environmental protection, land-use management and sustainable development in the region. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Assessing the Impacts of Vented Dam Land Submergence and Storage Capacity for Water Resources Management
(Springer Science and Business Media Deutschland GmbH, 2024) Mahima, N.; Pai, A.; Umesh, P.
Water plays an important role in sustaining life on earth hence it is necessary to store water and increase the ground water table. Due to the increase in population, the demand for water has also risen over a period of time. The area with sufficient rainfall is also facing scarcity of water due to improper water storage management. In order to overcome the scarcity of water, vented dams are constructed to harvest the water. The present study is attempted for two vented dams that are at Nethravathi River and Papanashini River. In order to increase the storage of water in the reservoir the height of the dam gate is increased by 2Â m on the existing height. Due to which there is submergence of land and there is increase in area of storage. Bathymetry survey is carried out to determine the depth of water stored and volume is estimated. The water stored can be used for irrigation, surrounding agricultural purposes. Â© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Assessment of spatial variation of soil moisture during maize growth cycle using SAR observations
(2019) Gururaj, P.; Umesh, P.; Shetty, A.
Spatial Information about Soil moisture over agricultural crops are required for efficient irrigation which in turn helps in saving water and increases crop yield. Soil moisture also useful in prediction of flooded and drought regions. However field measurement of soil moisture is not a practical approach. The main objective of the study is to track soil moisture variation all along the maize growth period in a Semi-Arid region. There are only few studies carried out on soil moisture variation considering whole maize growing period. During the crop growing period soil moisture field investigation are conducted in synchronization with Satellite pass. Sentinel-1a Synthetic Aperture RADAR (SAR) satellite, Interferometric wide swath dual polarized data with 5.405 GHz frequency and central incidence angle of 23�?� with repeat period of 12 days was used in this study. All in all during growth period 6 satellite pass scenes are acquired and processed by standard procedure using Sentinel Application Platform (SNAP) software. An attempt was made to redeem surface soil moisture for the whole maize growing crop cycle using water cloud model. The whole period of maize crop was divided into 3 parts like seedling, growing and harvesting period and soil moisture is retrieved for each period. The estimated soil moisture was validated with 30 field measured soil moisture samplings. The correlation coefficient of retrieved and actual soil moisture of seedling, growing and harvesting periods are 0.77, 0.72 and 0.6 respectively. The output of this study will be helpful in formulating strategies for irrigation water management. � 2019 SPIE.
Assessment of surface soil moisture from ALOS PALSAR-2 in small-scale maize fields using polarimetric decomposition technique
(Springer Science and Business Media Deutschland GmbH, 2021) Gururaj, P.; Umesh, P.; Shetty, A.
Surface soil moisture knowledge is important, especially in agriculture and irrigation management. Properties of microwave remote sensing like penetration power and longer wavelength facilitate retrieval of surface soil moisture. ALOS PALSAR-2, quad polarized data are used to retrieve surface soil moisture using polarization decomposition techniques in a marginal farmer small-scale maize field. The focus of the study is to explore the utility of ALOS PALSAR-2 in retrieving surface soil moisture using the polarization decomposition technique. The demonstration of the study is carried out in Malavalli village, southern India, an agricultural predominant area. The study involves field soil moisture sampling in synchronous with satellite pass, measuring soil properties, preprocessing of SAR data, polarization decomposition, proportional analysis, regression analysis, model calibration and validation. Van Zyl decomposition gave the highest surface scattering component (43%) and reduced volumetric scattering component compared to Yamaguchi and Freeman–Durden decomposition. Surface scattering component of Yamaguchi decomposition gave a good coefficient of determination (R2 = 0.8029) with field-measured surface soil moisture. The semi-empirical model (SEM) was developed using surface scattering component and depolarization ratio with adjusted R2 = 0.75 at 95% confidence interval. On its comparison with existing soil moisture models, it is observed that the developed model is performing well with RMSE and AEmax of 1.81 and 2.88, respectively. Implying the applicability of ALOS PALSAR-2 in soil moisture retrieval in marginal farmer small-scale maize fields gave satisfactory results of accuracy. © 2021, Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences.
Automated rice mapping using multitemporal Sentinel-1 SAR imagery using dynamic threshold and slope-based index methods
(Elsevier B.V., 2025) Aishwarya Hegde, A.H.; Umesh, P.; Tahiliani, M.P.
Rice cultivation plays a crucial role in food security and economic development, particularly in regions like India, due to its vast population and position as the top rice producer globally. This work introduces a novel framework, the Rice Mapping Method (RMM), which leverages Multitemporal Sentinel-1 Synthetic Aperture Radar (SAR) imagery for automated rice mapping. Contrary to the traditional approaches, RMM combines the Dynamic Threshold Method (DTM) for robust rice field identification and a slope-based index for classifying single and double cropping practices. By analyzing VH backscatter patterns and employing specific thresholds, DTM separates rice pixels from the other background pixels. The DTM, which relies on VH backscatter values during the growing season, has been tested across various rice cultivation landscapes, demonstrating high accuracy up to 0.95. DTM is also tested on different rice-growing areas such as the hilly Kodagu district, with an F1 Score of 0.96, and in the flooded delta region of Kuttanad, achieving an F1 Score of 0.93. The Slope-based Index I(r,c) is introduced to differentiate the single and double cropping pixels by calculating the index for the second season of cropping and gives F1 Score of 0.81. The DTM's effectiveness in rice field identification is evaluated by comparing it to the classification of the Bi-directional Gated Recurrent Unit (Bi-GRU) network. Similarly, the Slope-based Index is compared with other established automated rice mapping methods to assess its accuracy in distinguishing cropping patterns. RMM was successfully applied in mapping rice-growing areas in the Udupi district for 2021, estimating Kharif and Rabi season areas, the estimated rice area is compared to official statistics by the Directorate of Economics and Statistics, Karnataka State. The proposed RMM approach offers a robust solution for mapping rice fields, particularly in regions with complex cropping landscapes, and enhances agricultural monitoring and decision-making processes contributing to sustainable rice production and food security initiatives. © 2024 Elsevier B.V.
Automatizing the Khasra Maps Generation Process Using Open Source Software: QGIS and Python Coding Language
(Springer Science and Business Media Deutschland GmbH, 2022) Sharma, R.; Beg, M.K.; Bhojaraja, B.E.; Umesh, P.
Humans are trying to acquire a piece of land from the time they have come into existence. In modern era, the management of land and its ownership is taken up by the Land and Revenue Department of the State. In order to do that, they need maps with specific objectives, so that even a laymen can understand and use it. The process explained in this paper automate the process of map making after getting the digitized shapefile of the khasra (property identification number), as a single village is divided into numerous grids and it is a tedious work and can have lots of errors while doing it manually. So in order to do the process in swift manner and without having any errors, the process was developed using the Quantum Geographic Information System (QGIS) and Python. The proposed method involves making the use of models built in QGIS along with the Python console. It helps to run the whole process on its own with taking the required input parameters and storing the outputs in a specific folder designed for them. The requirement of the project was to do the same operations on a village file and to get the final khasra map from the village polygon file. Depending upon the village area and its dimensions, the numbers of grids for a particular village is decided and the same GIS tools need to be run on each grid files which make this process a tedious work and more prone to errors. By making use of the method suggested in the paper, all the work can be done error proof with the use of Python. The use of Python code helps to do work in just couple of seconds which would have taken days to complete. Â© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Climate indices and drought characteristics in the river catchments of Western Ghats of India
(Springer Science and Business Media Deutschland GmbH, 2024) Shetty, S.; Umesh, P.; Shetty, A.
The study addresses the long-term trend in rainfall, minimum and maximum temperature, and the climate indices for the river catchments located in the diverse climate of the Western Ghats of India. The dry sub-humid Chaliyar catchment and humid Kajvi catchment have shown a dramatic change in the decadal rainfall, with the decade 1950–1960 being the point of change. The monsoon rainfall has decreased in the Chaliyar and Netravati catchments and increased insignificantly in the Kajvi catchment. With the increase in mean temperature, the number of rainy days is decreasing, and intense rainfall is increasing in the pre-monsoon. The increase in minimum temperature is more severe in all three catchments, irrespective of the region’s climate. The decline in rainy days is more figurative in the humid and per-humid catchments and has seen a 16–20% decrease in R×1 day, R×3 day, and R×5 day in the past six decades with an insignificant increase in the dry sub-humid catchment. The frightful increase in warm days/nights with a decrease in cool days/nights has been alarming for the extremity of temperature in future years. The significant changes in the forest area in Chaliyar and Kajvi catchment and the increase in a built-up area in Netravati may have a decisive role in the nonseasonal variability in rainfall and temperature along with increasing greenhouse gases. In the case of meteorological drought studied using the Standardized Precipitation Index (SPI), moderate droughts have occurred over the Chaliyar and Kajvi, and extreme droughts over the Netravati catchments with no reduction in the frequency or severity of short-duration extreme rainfall events. The geographical location of the catchment has a greater impact on the characteristics of the rainfall and meteorological drought, and these changes in the hydrological regimes of the catchment have a significant bearing on the water availability in the catchments in the future years. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2023.
Comparison of Neural Networks for Binary Spatial Classification of Rice Field by Studying Temporal Pattern using Dual Polarimetric SAR Measurements
(Springer, 2024) Aishwarya Hegde, A.; Umesh, P.; Tahiliani, M.P.
Timely and precise information on rice cultivation plays a pivotal role in reshaping the global food and agricultural system. Synthetic aperture radar, with its capability to observe around the clock and in all weather conditions, is an invaluable tool for monitoring rice distribution. Such comprehensive cropland data at vast spatial scales not only enhances crop management but also provides critical support to governmental decision-making processes. The paper focuses on Binary classification by learning the temporal pattern of the Rice pixel. Time series curves of VV, VH, VV+VH, and VV/VH polarization and major rice varieties, MO4 and Kaje Jaya, cultivated in the area are analyzed to study the similarity of the curves the similarities in the curves, which could influence the temporal pattern recognition capacity of deep learning models. The study underscores the superior performance of RNN models, particularly BiLSTM and the proposed Dual Branch BiLSTM, over their CNN counterparts, such as 3DCNN and 3DUNET, especially for the VH and VV+VH polarizations. Specifically, the Dual Branch BiLSTM emerged as a standout, exhibiting an accuracy rate of 99.92% for combination of VH and VV+VH polarization. This model adeptly combined features from both VH and VV+VH polarizations, ensuring robust rice field mapping. Our results present a promising avenue for enhanced rice mapping, especially in tropical or subtropical zones, through the nuanced application of deep learning models. © Indian Society of Remote Sensing 2024.
Conceptualization and Design ofÂ Remotely-Accessible Hardware Interface (RAHI) Laboratory
(Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2021) Potdar, S.M.; Gupta, V.; Umesh, P.; Gangadharan, K.V.
With the rising popularity of e-learning through means like Massive Open Online Courses (MOOCs), remote-triggered and virtual laboratories, new and innovative technologies for enhancing the learning experience are in demand. E-learning resources for electronics hardware are generally simulation-based, as getting access to high-end hardware is difficult for students due to cost and availability. In this paper, a novel method to create a remotely-accessible, low-cost, modular, and scalable hardware learning platform is proposed and demonstrated through a prototype. Users can interact with the system through a web interface anytime-anywhere and verify results on actual hardware through real-time visual and textual feedback and learn at their pace. The prototype demonstrates a web application hosted on a Linux-PC server interacting with a Raspberry Pi. Student activities are logged in a database for future reference and correction by instructors. The software stack used for the system is free and open-source. The prototype system was launched on a pilot run, gaining positive feedback from students and teachers. Hence, such a system can undergo comprehensive implementation in educational institutions and for the delivery of MOOCs with minimal investment for both laboratory setups and learners. Â© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Dependability of rainfall to topography and micro-climate: an observation using geographically weighted regression
(Springer, 2022) Shetty, S.; Umesh, P.; Shetty, A.
The dependability of rainfall to topography and micro-climate of the region in an eco-sensitive Western Ghats of India is evaluated using the geographically weighted regression method. The correlation between rainfall and topographical features, namely, elevation, slope, Terrain Ruggedness Index, topography, and distance from the coast/ridge, varies seasonally with consistent variation across the years. The Normalized Differential Vegetation Index and rainfall have an inverse relationship due to the adverse effect of high spell rainfall on vegetation growth in the monsoon season. The rainfall negatively correlates with maximum land surface temperature and conversely with a minimum land surface temperature in the windward side of the Ghats other than monsoon season. The connection between rainfall and other variables differs significantly throughout space, with vast differences on the mountain’s windward and leeward sides, as well as in the Ghats’ southern and northern regions. The effect of the terrain is amplified in the broad, gradually sloping intermediate rough mountain that is close to the coast. The maximum rainfall depends on the mountain’s steepness on the windward side; at isolated mountains, maximum rainfall occurs at an elevation range of 500–800 m and in cascaded mountain ranges at 800–1200 m along with the influence of other driving factors. Also, the control exerted by the ridge of the mountain on the rain-bearing wind is prominent until 120 km from the mountain ridge. These results are useful in understanding the reliance of rainfall on topographic and micro-climatic parameters and can be used in hydro-geological applications. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
Design and Development of a BCI Framework to Control a UTM Using EEG Headset
(Springer Science and Business Media Deutschland GmbH, 2024) Manish, E.S.; Pratheesh; Umesh, P.; Gangadharan, K.V.
We live in a period where machines have become a fundamental piece of our day-to-day existence. These machines that surround us largely depend on human assistance. To operate them, a human would nearly have to be functional. We only lose the capacity to engage with machines when these capabilities are hindered, possibly by a bodily condition or injury. This study picks the Universal Testing Machine as the machine to be operated to help physically challenged people run machinery. Additionally, it uses an Internet of Things architecture to monitor specific brain activities in the personâ€™s brain, while controlling the machine. Â© 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Development of a LoRaWAN-Enabled Unmanned Aerial System for Autonomous Real-Time Surveillance and Monitoring
(American Society of Mechanical Engineers (ASME), 2023) Manish, E.S.; Umesh, P.; Gangadharan, K.V.; Shetty, D.
This research paper proposes a LoRaWAN-enabled Unmanned Aerial System (UAS) for autonomous real-time surveillance and monitoring for agriculture fields. Traditional security measures in agriculture face challenges due to their high costs and labor-intensive nature, especially on large farms. The paper outlines the development of the complete system, explaining each block that forms its components. Additionally, it presents an experiment where a UAS successfully flew to a specific location triggered by motion sensors connected to LoRa nodes as part of surveillance and monitoring of an area. The results demonstrate the system's effectiveness in real-time monitoring and autonomous operation. By leveraging LoRaWAN technology, this system offers a promising solution to enhance agricultural security and efficiency. The integration of technologies showcased in this research contributes to the field of precision agriculture. Â© Â© 2023 by ASME.
DEVELOPMENT OF PORTABLE GROUND CONTROL STATION FOR REAL-TIME DATA MONITORING OF AN UNMANNED SURFACE VESSEL
(American Society of Mechanical Engineers (ASME), 2023) Kotian, R.; Umesh, P.; Gangadharan, K.V.; Shetty, D.
This paper presents a portable ground control station for unmanned surface vessels (USVs) that can operate autonomously or remotely without crew onboard. USVs equipped with various sensors, propulsion systems, and communication equipment perform a wide range of tasks, including scientific research, environmental monitoring, and maritime security. The Ground Control Station (GCS) is essential to the operation of a USV, enabling remote control and monitoring of the vehicle, allowing it to operate autonomously or semi-autonomously. A portable GCS allows the operator to bring the system to remote or difficult-to-access locations, enabling the USV to operate in a wider range of environments and conditions. The paper describes the hardware architecture of the system, with an emphasis on navigational sensors for guidance and control. The hardware components include controllers, communication equipment, and sensors such as GPS, and sonar. These sensors provide the USV with real-time information about its position, velocity, and environment, enabling informed navigation and control decisions. The software includes control algorithms, user interfaces, and data processing tools that allow the operator to control and monitor the USV's operations. The user-friendly software interfaces and clear feedback make it easy for the operator to manage the USV's movements and data collection. Overall, the paper provides insights into the design and implementation of a system for controlling USVs, focusing on hardware, User interface and, and Mission planning. Â© Â© 2023 by ASME.
Development of Portable Tethered Vertical Profiler for Underwater Monitoring
(Institute of Electrical and Electronics Engineers Inc., 2023) Sequeira, S.L.; Manish, E.S.; Rakshith; Umesh, P.; Gangadharan, K.V.
Human activities and industrial waste flow to water bodies will contaminate the coastal areas, leading to changes in the underwater ecosystem and affecting aquatic habitats. Understanding these ecosystems requires quick data collection, systematic process monitoring, and coastal resource preservation through proper decision-making. We can understand the variation of water properties with depth by deploying sensors from the surface, one of the most popular methods of gathering ocean data. However, high-resolution oceanographic data collection and long-term human observations are risky and expensive. Although some autonomous profiling systems address these issues, there is still scope for developing practical, affordable, and accurate data-providing systems. This paper discusses an open-source, economical, easily portable, propeller-driven underwater Vertical Profiler controlled by a joystick located in Ground Control System (GCS) using a Neutrally buoyant tether cable. Data from sensors, like temperature, pressure, and depth, are collected. The paper also discusses functionality and sensor tests conducted on the developed vehicle at a controlled environment/test site. The developed Profiler can perform basic manoeuvres and collect water quality data upstream of vented dams and rivers in and around the Dakshina Kannada district of Karnataka, India. Â© 2023 IEEE.
Enhancing soil organic carbon estimation accuracy: Integrating spatial vegetation dynamics and temporal analysis with Sentinel 2 imagery
(Elsevier B.V., 2024) Mruthyunjaya, P.; Shetty, A.; Umesh, P.
This article introduces an improved method for estimating Soil Organic Carbon (SOC) using Sentinel 2 images, with a specific emphasis on the Dakshina Kannada area in India. By examining 364 soil samples, SOC estimation models were constructed using Random forests (RF) and Partial Least Squares Regression (PLSR), focusing on the impact of nearby vegetation pixels. The approach consisted of classifying soil samples by the presence of plant pixels at distances of 0, 10, and 20 m, and evaluating the influence of dry vegetation by the use of the Normalised Burn Ratio 2 (NBR2). The findings demonstrated a significant improvement in the precision of the model (by up to 20 %) when vegetation pixels within a 20-meter radius of the sample locations were omitted. The research also included a temporal analysis utilizing Sentinel-2 images from April 2017 to May 2023. This analysis showed strong relationships between the amount of exposed soil and the accuracy of predicting soil organic carbon (SOC) levels. These results emphasize the need to take into account both the spatial dynamics of vegetation and the temporal variations in bare soil covering to get an accurate estimate of soil organic carbon (SOC). This study improves the accuracy and dependability of SOC evaluations by including geographical and temporal aspects, providing useful insights for agricultural and ecological applications. © 2024 The Author(s)
Evaluation of surface soil moisture models over heterogeneous agricultural plots using L-band SAR observations
(Taylor and Francis Ltd., 2022) Gururaj, P.; Umesh, P.; Shetty, A.
The goal of this study is to evaluate the efficiency of surface soil moisture models based on L-band SAR data at two different crop stages in typical Indian agricultural plots. Agricultural fields examined include paddy, tomato, sugarcane, at two distinct crop stages, and a reference fallow field. Among the evaluated models, X-Bragg model underestimates soil moisture in all agricultural fields, whereas the Oh 2004 model fits into three agricultural plots for two crop stages without any necessity of auxiliary field information. All models underperformed in the case of sugarcane at the grand growth stage. Although WCM gave best result, it came at the cost of field data utilized to calibrate model parameters. Overall, the Oh 2004 model outperforms other models across crop types and growth stages. To the best of our knowledge, this is the only study that deals with soil moisture estimations at the plot scale across different crops. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
Examining the effects of vented dams on land use and land cover in the Shambhavi Catchment: a multitemporal sentinel imagery analysis
(Elsevier Ltd, 2024) Chandana, S.; Aishwarya Hegde, A.; Umesh, P.; Chandan, M.C.
The rapid expansion of the global economy has given rise to concerning ecological consequences, notably a dramatic increase in land cover change (LCC). This section presents how to use the Google Earth Engine (GEE) cloud platform to explore the administrative divisions of the Southern Indian Dakshina Kannada (DK) district, which were chosen for their LCC susceptibility. Leveraging GEE, we generated a time series dataset tracking LCC over a 4-year period (2019–22). Our findings demonstrate an impressive overall accuracy (OA) of 96.30% for 2019 and 95.47% for 2022. A significant revelation in our study is the 13.64% reduction in forested areas, accompanied by a 0.68% increase in urban development within the district. This research attempt offers vital insights into the impact of dam construction on LCC, aiding informed decisions on water resource management. This research promotes a sustainable and ecologically conscious approach to holistic development in the study region and beyond. © 2024 Elsevier B.V.
Experiential Learning of Physio-Chemical and Bacteriological Properties of Water using Virtual Labs
(Institute of Electrical and Electronics Engineers Inc., 2020) Shetty, S.; Shetty, A.; Aishwarya Hegde, A.; Salian, A.B.; Akshaya; Umesh, P.; Gangadharan, K.V.
Virtual Labs, an initiative by the Government of India under the National Mission on Education through Information and Communication Technology (NMEICT), has revolutionized the teaching and learning process for laboratory courses in the science and engineering disciplines. The web-based laboratories provided by the Virtual Labs project enable personalized learning while being cost effective and highly scalable. This approach helps to quickly learn the fundamental concepts of science and engineering through virtual experimentation, fosters curiosity and innovation among students, and prevents laboratory hazards. In this paper, we describe the design and development of two web-based virtual laboratories that simulate the fundamental concepts of Civil Engineering and Environmental Engineering. The proposed virtual labs provide a detailed explanation of the experiments in the respective engineering domains, and reagents and apparatuses involved while performing the experiments. The outcomes of this work are evaluated by analyzing the feedback collected from the users of these virtual labs, which reveals that the labs are an useful means to provide easy, cost effective and scalable solutions for online experiential learning. Â© 2020 IEEE.