Earth and Planetary Sciences, Nature and Landscape Conservation, Earth-Surface Processes
28
Scopus Publications
293
Scholar Citations
7
Scholar h-index
7
Scholar i10-index
Scopus Publications
Prediction of groundwater quality assessment by integrating boosted learning with DE optimizer Sonalika Subudhi, Alok Kumar Pati, Sephali Bose, Subhasmita Sahoo, Avipsa Pattanaik, Biswa Mohan Acharya, Rakesh Ranjan Thakur Scientific Reports, 2026 Groundwater is eventually undermined by human activities, such as rapid industrialization, urbanization, over-extraction, and contamination from agricultural and urban sources. Among the different contaminants, the presence of minerals such as calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), fluoride (F), and chloride (Cl) proves to have serious health risks when present in excess concentrations. This study addresses this gap by developing a predictive machine learning model to evaluate the groundwater quality index (GWQI) and to identify the critical contaminants affecting water safety. A total of 1989 groundwater samples were collected from Jajpur district, where the Sukinda Valley is located, and analyzed for multiple physicochemical parameters, as this region is known for extensive chromite mining activities and has been identified as one of the most critically polluted areas in India, posing significant groundwater contamination risks. This study introduces the novel hybrid machine learning model, LCBoost fusion, which distinguishes this work from previous studies by combining the strengths of CatBoost and LightGBM to enhance predictive accuracy. It has been achieved with the help of a hybrid machine learning model i.e. LCBoost fusion. The model outperforms individual models (CatBoost and LightGBM), by achieving low RMSE (0.6826), MSE (0.5100), MAE (0.3148) and a high [Formula: see text] score of 0.9810. Feature importance analysis highlights potassium (K), fluoride (F) and total hardness (TH) as the most influential indicators of groundwater contamination. This research successfully demonstrates the application of machine learning in assessing groundwater quality risks in Odisha, with practical implications for real-time groundwater monitoring and risk mitigation. LCBoost Fusion model offers a reliable and efficient approach for real-time groundwater monitoring and risk mitigation. These findings will help environmental organizations and policy makers to map out targeted places for sustainable groundwater management.
A deep learning-geospatial analytics fusion framework for predicting land use land cover dynamics in eastern region of India Debabrata Nandi, Rakesh Ranjan Thakur, Dillip Kumar Bera, Alok Kumar Pati, Priyanka Mishra, Fahad Alshehri, Mohamed Zhran Results in Engineering, 2026 Globally, rapid urbanisation and unregulated urban expansion have driven widespread Land Use and Land Cover (LULC) changes, resulting in deforestation, loss of vegetation, and depletion of water bodies. In India, cities and peri-urban areas are experiencing similar transformations, making it essential to monitor and manage urban growth effectively. This study aims to analyse LULC changes in Berhampore, West Bengal, from 2001 to 2023, identify key drivers of urban expansion, and predict future land use for 2033 using remote sensing, GIS-based spatial analysis, and Deep learning techniques (ANN and CA models). The results show a sharp increase in built-up areas from 20.39 sq. km (2001) to 43.85 sq. km (2023), leading to significant reductions in vegetation (-52.13 sq. km) and water bodies (-1.74 sq. km). Forecast for 2033 shows continued urban development where agricultural territories represent sixty-two percent of the land while forests face a fifty percent reduction thus boosting risks of biodiversity depletion along with enhanced flood potential. This research proves that land sustainability policies and green infrastructure planning combined with strategic urban strategies must urgently develop to balance development with environmental endurance. This research shows that ANN and CA operate as predictive methods to enhance LULC accuracy by helping administrators execute measurement policies. This study incorporates deep learning architecture parts that integrate CNNs and LSTMs to establish advanced LULC modelling frameworks which excel at spatial-temporal pattern detection. Future research on urban growth prediction will benefit from the proposed structures built to improve predictive models by integrating hierarchical features based on long-term dependency according to academic publications.
Resilient Traditions and Changing Spaces: Vernacular Architecture and Livelihood Shifts in Assam’s Handloom and Handicraft Settlements Anashuiya Bhattacharya, Priyanka Mishra, Damodar Jena, Rakesh Ranjan Thakur, Vishwanath Neelannavar, Bandana Nayak Indian Journal of Information Sources and Services, 2025 The handloom and bell-metal craft sectors are integral to Assam’s socio-economic fabric, reflecting its rich cultural heritage and economic identity, particularly in the traditional settlements of Sualkuchi and Sarthebari. However, these communities are undergoing a rapid transformation due to the growing influence of modernization, changing lifestyles, and shifting socio-economic conditions. This paper examines the transformations in vernacular architecture and its intrinsic connection to local artisanal livelihoods. Using a mixed-method approach comprising field surveys, interviews, focus group discussions, and spatial mapping, the research documents the production techniques, settlement patterns, and built forms in these craft-based communities. The study examines the transition from traditional Assam-type dwellings to reinforced concrete (RCC) structures, investigating how these changes impact spatial functionality, sustainability, and cultural continuity. Findings suggest that while contemporary materials improve structural durability, they often compromise climatic responsiveness and disrupt the historic integration of living and working spaces. This disruption threatens the long-standing artisanal traditions that are deeply tied to the built environment. The paper highlights the urgent need for sustainable, culturally rooted design strategies and recommends hybrid construction approaches, community participation in planning, and integration of traditional knowledge into rural development frameworks. These interventions are critical for reconciling heritage preservation with the demands of modern living in Assam’s artisanal settlements.
Machine Learning-Enhanced Monitoring and Assessment of Urban Drinking Water Quality in North Bhubaneswar, Odisha, India Kshyana Prava Samal, Rakesh Ranjan Thakur, Alok Kumar Panda, Debabrata Nandi, Alok Kumar Pati, Kumarjeeb Pegu, Bojan Đurin Limnological Review, 2025 Access to clean drinking water is crucial for any region’s social and economic growth. However, rapid urbanization and industrialization have significantly deteriorated water quality, posing severe pollution threats from domestic, agricultural, and industrial sources. This study presents an innovative framework for assessing water quality in North Bhubaneswar, integrating the Water Quality Index (WQI) with statistical analysis, geospatial technologies, and machine learning models. The WQI, calculated using the Weighted Arithmetic Index method, provides a single composite value representing overall water quality based on several key physicochemical parameters. To evaluate potable water quality across 21 wards in the northern zone, several key parameters were monitored, including pH, electrical conductivity (EC), dissolved oxygen (DO), hardness, chloride, total dissolved solids (TDSs), and biochemical oxygen demand (BOD). The Weighted Arithmetic WQI method was employed to determine overall water quality, which ranged from excellent to good. Furthermore, Principal Component Analysis (PCA) revealed a strong positive correlation (r > 0.6) between pH, conductivity, hardness, and alkalinity. To enhance the accuracy and reliability of water quality assessment, multiple machine learning models Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Naïve Bayes (NB) were applied to classify water quality based on these parameters. Among them, the Decision Tree (DT) and Random Forest (RF) models demonstrated the highest precision (91.8% and 92.7%, respectively) and overall accuracy (91.7%), making them the most effective in predicting water quality and integrating WQI, machine learning, and statistics to analyze water quality. The study emphasizes the importance of continuous water quality monitoring and offers data-driven recommendations to ensure sustainable access to clean drinking water in North Bhubaneswar.
Monitoring changes in vegetation cover of Bhitarkanika marine National Park region, Odisha, India using vegetation indices of multidate satellite data Indian Journal of Geo Marine Sciences, 2019
An Integrated Geospatial Assessment of Multi-hazard Vulnerability and Groundwater Potential for Advancing Sustainable Water Security in Northern Odisha, India D Nandi, JK Tripathy, D Behera, AM Saqr, R Beuria, RR Thakur Water Conservation Science and Engineering 11 (2), 52 , 2026 2026
Integrated water quality assessment of the Drenica River using macroinvertebrates and Promethee decision method PBFSHÇRKSRESDNBĐBDVHFFURELFLRRTDNRBO Fetoshi1 Biologia 81 (146), 1-25 , 2026 2026
Leveraging AI for sustainable water quality management in lakes: bibliometric insights and critical review AM Saqr, MG Snousy, JO Alao, RR Thakur, D Nandi, A Alitane, M Ouarani, ... Recent Advances in Water Science, 115-141 , 2026 2026 Citations: 1
Assessment of Groundwater Quality in Some Regions of Kosovo Based on Physico-Chemical and Microbiological Parameters F Zogaj, T Blazhevska, F Sallaku, RR Thakur, H Çadraku, U Rathnayake, ... Limnological review 26 (2), 16 , 2026 2026
Vulnerability Research: Global Trends, Emerging Techniques, Sustainability Implications, and Future Directions AM Saqr, RR Pant, A Alitane, RR Thakur, JO Alao, PK Chaurasia A Global Perspective on Contaminants in Groundwater: Assessment and … , 2026 2026
Two Decades of Groundwater Vulnerability Research: Global Trends, Emerging Techniques, Sustainability Implications, and Future Directions AM Saqr, RR Pant, A Alitane, RR Thakur, JO Alao, PK Chaurasia, M Nasr A Global Perspective on Contaminants in Groundwater: Assessment and … , 2026 2026
Advancing watershed science: A comprehensive review of morphometry, land use change, vulnerability, and resilience frameworks D Nandi, JK Tripathy, D Behera, R Beuria, RR Thakur Physics and Chemistry of the Earth, Parts A/B/C 144, 104412 , 2026 2026
Enhancing hand-pump tubewells' functionality by appraising the suitability of site selection: an MCDM approach to achieve SDG 6 S Halder, S Banerjee, Z Mukhtar, J Saha, G Bhandari, D Ray, A Alam, ... Journal of Water and Climate Change 17 (2), 245-281 , 2026 2026
AI-powered delay risk prediction in construction projects: leveraging machine learning, deep learning and hybrid models P Sahu, DK Bera, PK Parhi, M Kandpal, RR Thakur International Journal of Construction Management, 1-22 , 2026 2026
A Deep Learning-Geospatial Analytics Fusion Framework for Predicting Land Use Land Cover Dynamics in Eastern Region of India MZ Debabrata Nandi , Rakesh Ranjan Thakur , Dillip Kumar Bera , Alok Kumar ... Results in Engineering , 2026 2026 Citations: 1
Prediction of groundwater quality assessment by integrating boosted learning with DE optimizer BMARRT Sonalika Subudhi1, Alok Kumar Pati1, Sephali Bose1, Subhasmita ... Scientific Reports 16 (618) , 2026 2026
Resilient Traditions and Changing Spaces: Vernacular Architecture and Livelihood Shifts in Assam’s Handloom and Handicraft Settlements A Bhattacharya, P Mishra, D Jena, RR Thakur, V Neelannavar, B Nayak Indian Journal of Information Sources and Services 15 (4), 96-107 , 2025 2025
Resilient Traditions and Changing Spaces: Vernacular Architecture and Livelihood Shifts in Assam’s Handloom and Handicraft Settlements VNBN Anashuiya Bhattacharya , Priyanka Mishra, Damodar Jena, Rakesh Ranjan ... Indian Journal of Information Sources and Services 15 (4), 96-107 , 2025 2025
Machine Learning-Enhanced Monitoring and Assessment of Urban Drinking Water Quality in North Bhubaneswar, Odisha, India * Kshyana Prava Samal 1, Rakesh Ranjan Thakur 2, Alok Kumar Panda 3 ... limnological review 25 (44), 25 , 2025 2025 Citations: 2
Integrated Water Quality Assessment of the Drenica River Using Macroinvertebrates and PROMETHEE Decision Method P Bytyçi, F Sallaku, H Çadraku, R Koto, S Rizani, E Skura, D Nuha, ... 2025
Socio-economic Inequities and Anemia in Pregnancy in Gajapati District of Odisha: An Empirical Inquest M Pattanaik, D Jena, P Mishra, A Mishra, B Nayak, RR Thakur Indian Journal of Information Sources and Services 15 (3), 239-247 , 2025 2025
Socio-economic Inequities and Anemia in Pregnancy in Gajapati District of Odisha: An Empirical Inquest BNRRT Madhuswapna Pattanaik1 , Damodar Jena2* , Priyanka Mishra3*, Abha Mishra4 Indian Journal of Information Sources and Services 15 (3), 239-247 , 2025 2025
Machine learning-based LULC change detection and environmental implications in Bankura, West Bengal, India DKBRB Debabrata Nandi, Rakesh Ranjan Thakur, Bojan Ðurin3, Mayank Pandey ... AIMS Environmental Science 12 (5), 835–855 , 2025 2025 Citations: 1
Heatwave-induced thermoregulatory stress in Odisha's coastal and north-eastern districts: Examining the April 2024 event using advanced statistical and geospatial techniques R Beuria, D Sahu, SC Sahu, D Nandi, S Behera, KL Mohanta, RR Thakur Dynamics of Atmospheres and Oceans 111, 101577 , 2025 2025 Citations: 3
Integrated Evaluation of Soil Pollution and Plant Bioaccumulation Using Multimetric Indices: A Case Study from the Rehova Copper Mine, Albania A Dollani, E Skura, F Sallaku, E Shkurta, E Lika, P Bytyçix, S Shallari, ... International journal of design & nature and ecodynamics 20 (8), 1729-1744 , 2025 2025 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Advances in nanoparticles and nanocomposites for water and wastewater treatment: a review J Tripathy, A Mishra, M Pandey, RR Thakur, S Chand, PR Rout, ... Water 16 (11), 1481 , 2024 2024 Citations: 151
A novel approach for ex situ water quality monitoring using the Google Earth engine and spectral indices in Chilika Lake, Odisha, India S Das, D Nandi, RR Thakur, DK Bera, D Behera, B Đurin, V Cetl ISPRS International Journal of Geo-Information 13 (11), 381 , 2024 2024 Citations: 25
Irrigation water quality prognostication: An innovative ensemble architecture leveraging deep learning and machine learning for enhanced SAR and ESP estimation in the east … AK Pati, AR Tripathy, D Nandi, RR Thakur, M Pandey Journal of Environmental Chemical Engineering 13 (3), 116433 , 2025 2025 Citations: 15
Hydrogeochemical and geospatial insights into groundwater contamination: fluoride and nitrate risks in western Odisha, India S Barad, RR Thakur, D Nandi, DK Bera, PC Sahu, P Mishra, KP Samal, ... Water 17 (10), 1514 , 2025 2025 Citations: 15
Peri-urban floodscapes: Identifying and analyzing flood risk areas in North Bhubaneswar in Eastern India P Mishra, D Jena, RR Thakur, S Chand, B Javed, AK Shukla Water 16 (21), 3019 , 2024 2024 Citations: 15
Geospatial monitoring of environmental sustainability: A remote sensing-based approach for assessing mining-induced impacts in Eastern India M Pandey, RR Thakur, D Nandi, DK Bera, R Beuria, M Kumari, M Zhran Results in Engineering 26, 104692 , 2025 2025 Citations: 12
Monitoring Changes in Vegetation Cover of Bhitarkanika Marine National Park Region, Odisha, India Using Vegetation Indices of Multidate Satellite Data S Thakur, R.R., Kumar, P & Palria Indian Journal of Geo-marine Sciences 48 (12), 1916-1924 , 2019 2019 Citations: 12
Prediction of groundwater quality assessment by integrating boosted learning with DE optimizer BMARRT Sonalika Subudhi, Alok Kumar Pati, Sephali Bose, Subhasmita Sahoo ... Scientific Reports, 58 , 2025 2025 Citations: 6
Urban Expansion and Land Use Transformations in Midnapore City (2003–2024): Implications for Sustainable Development * Rakesh Ranjan Thakur 1, Debabrata Nandi 2,*, Anoop Kumar Shukla 3 ... Earth 6 (50), 20 , 2025 2025 Citations: 6
Fluoride risk prognostication: A pioneering ensemble machine learning approach for groundwater contamination prediction in parts of the east coast of India AK Pati, AR Tripathy, D Nandi, RR Thakur, B Ðurin, D Dogančić, ... Water 17 (6), 909 , 2025 2025 Citations: 5
Exploring seasonal changes in coastal water quality: Multivariate analysis in Odisha and West Bengal coast of India PR Dixit, MS Akhtar, RR Thakur, P Chattopadhyay, B Kar, DK Bera, ... Water 16 (20), 2961 , 2024 2024 Citations: 5
Integrating nature-based solutions in the urbanization process by urban agriculture: a case of Bhubaneswar city, India S Panda, C Parida, A Azharunnisa, RR Thakur Discover Sustainability 5 (1), 286 , 2024 2024 Citations: 5
Predicting Potential Habitats and the Conservation of the Tasar Silkworm ( Antheraea mylitta ) in the Similipal Biosphere Reserve, Odisha, India RR Thakur, D Nandi, DK Bera, S Singh, R Beuria, P Mishra, FFB Hasher, ... Sustainability 17 (13), 5824 , 2025 2025 Citations: 4
Land-surface temperature dynamics in the fringes of north Bhubaneswar, India: an empirical analysis P Mishra, D Jena, NC Giri, RR Thakur, DN Dash Current Science 129 (2), 139-145 , 2024 2024 Citations: 4
Heatwave-induced thermoregulatory stress in Odisha's coastal and north-eastern districts: Examining the April 2024 event using advanced statistical and geospatial techniques R Beuria, D Sahu, SC Sahu, D Nandi, S Behera, KL Mohanta, RR Thakur Dynamics of Atmospheres and Oceans 111, 101577 , 2025 2025 Citations: 3
Space based information support for decentralised planning (SIS-DP)-A case study in balangir district, odisha, india P Kumar, SK Dash, RR Thakur, S Jonna, S Tripathi The International Archives of the Photogrammetry, Remote Sensing and Spatial … , 2014 2014 Citations: 3
Machine Learning-Enhanced Monitoring and Assessment of Urban Drinking Water Quality in North Bhubaneswar, Odisha, India * Kshyana Prava Samal 1, Rakesh Ranjan Thakur 2, Alok Kumar Panda 3 ... limnological review 25 (44), 25 , 2025 2025 Citations: 2
Leveraging AI for sustainable water quality management in lakes: bibliometric insights and critical review AM Saqr, MG Snousy, JO Alao, RR Thakur, D Nandi, A Alitane, M Ouarani, ... Recent Advances in Water Science, 115-141 , 2026 2026 Citations: 1
A Deep Learning-Geospatial Analytics Fusion Framework for Predicting Land Use Land Cover Dynamics in Eastern Region of India MZ Debabrata Nandi , Rakesh Ranjan Thakur , Dillip Kumar Bera , Alok Kumar ... Results in Engineering , 2026 2026 Citations: 1
Machine learning-based LULC change detection and environmental implications in Bankura, West Bengal, India DKBRB Debabrata Nandi, Rakesh Ranjan Thakur, Bojan Ðurin3, Mayank Pandey ... AIMS Environmental Science 12 (5), 835–855 , 2025 2025 Citations: 1
