Specific areas:
• Spatial Analytics
• Waste Resource Management
• Urban planning & development
• Coastal Management
25
Scopus Publications
778
Scholar Citations
7
Scholar h-index
6
Scholar i10-index
Scopus Publications
Fuzzy TOPSIS-based geospatial framework for delineating groundwater potential zones in the Pune metropolitan catchment, western India Deepa D. Naik, Navendu Chaudhary, Jyoti Jain Tholiya Ecological Engineering and Environmental Technology, 2026 Rapid urban expansion and increasing water demand place significant pressure on groundwater resources in metropolitan river basins.Although GIS-based multi-criteria decision-making (MCDM) approaches are widely used for groundwater potential mapping, their application in rapidly urbanizing basins requires improved handling of uncertainty and integration of hydro geological and anthropogenic factors.The objective of this study was to develop and apply a GIS-based Fuzzy-TOPSIS framework to identify and classify groundwater potential zones (GWPZ) in the Mula-Mutha catchment, western India, and to evaluate whether such an approach can provide spatially consistent prioritization for groundwater development in an urbanized basin.Six controlling factorsrunoff, soil, slope, land use/land cover, groundwater level, and lithology -were integrated into a fuzzy membership structure to address uncertainty in parameter standardization.The weighted criteria were then ranked using the TOPSIS method to generate a groundwater potential indicator and spatial classification map.The results delineated three groundwater potential categories: low (28%), moderate (41%), and high (31%).High-potential zones are primarily associated with permeable lithological formations, gentle slopes, and favourable soil conditions, whereas low-potential zones correspond to urbanized or steep areas with limited infiltration capacity.The study achieved its objective by producing a spatially differentiated and internally consistent groundwater potential map for the entire catchment.The Fuzzy-TOPSIS framework successfully integrated heterogeneous environmental variables and generated a reproducible decision-support tool suitable for groundwater resource planning in urbanized basins.
Predicting Mangrove Degradation Under Anthropogenic and Climatic Stressors: A Google Earth Engine - Based Case Study from Pichavaram , Navendu A. Chaudhary, T. P. Singh ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences, 2025 Mangrove forests are vital ecosystems that protect coastlines, support biodiversity, and capture carbon, yet they are increasingly threatened by human activities and climate change. This study presents a data driven approach to assess and predict mangrove degradation in the Pichavaram region of Tamil Nadu, India, using Google Earth Engine (GEE) and Random Forest classification. By combining satellite imagery from Landsat and Sentinel-2 with vegetation indices (NDVI and NBR), elevation, slope, salinity, tidal dynamics, and distances to roads, rivers, and settlements, developed a model to classify mangrove areas into stable, degraded, and regenerating zones. The classification model was associated with a very high accuracy (98.14%), strong agreement (Kappa = 0.972), and AUC scores above 0.96 for every class. According to the results, degraded zones were usually close to settlements, roads, and aquaculture, whereas regenerating patches lied close to rivers. A custom Climatic Stress Index integrating vegetation trends, salinity, and tidal variability provided added insight into environmental pressures.This research shows a transferable, cloud-based methodology for real-time mangrove monitoring, which thereby can provide useful tools for conservation planning, restoration prioritisation, and climate adaptation exercises in accordance with the Sustainable Development Goals (SDG 13 and 15). It shows how remote sensing and machine learning can be used to direct ecosystem management in areas where there is a lack of.
OPPORTUNITIES AND CHALLENGES IN HERITAGE CONSERVATION: HERITAGE WALKS, HERITAGE DRIVES, AND ON-SITE TALKS IN PUNE, INDIA , Yogesh PISOLKAR, Navendu CHAUDHARY, , Ananya SHARMA, , Alisha TASKAR, and International Journal of Conservation Science, 2025 Historic sites in countries like India are often neglected due to lack of awareness. They are often present in the middle of a busy city and blend in with ordinary modern structures. It is the author's effort to understand the opportunities present in creating understanding of the level of awareness and challenges faced in the conservation of such hidden gems. With their experiences as regular participants in various heritage walks & heritage talks in Pune city and a sample survey conducted, authors aim to suggest a marketing strategy for sustained activities highlighting various options for onsite talks, heritage walks, and/or heritage drives. Authors would also like to bring forward major challenges to the sustainability of these activities, mainly if it is ‘the paid activity. However, authors will also suggest how relevant stakeholders can be integrated for the successful implementation of these heritage-related activities. Most importantly, this inquiry will put forward opportunities for local people to make successful marketing and improve their avenues.
A Scoping Review of GIS Mapping of Type 1 Diabetes in Children: Identifying Current Gaps and Future Research Directions Using PRISMA-ScR Demi Miriam, Navendu Chaudhary, Sushil Yewale, Anuradha Khadilkar Current Diabetes Reviews, 2025 Background: Type 1 Diabetes poses a significant public health threat, especially in low-and-middle countries, where resources are limited. The use of geographical information systems in diabetes research has shown the potential to reveal several epidemiological risk factors. Aims: This scoping review aimed to identify the scope and extent of the current literature and explore its limitations on the geographical mapping of children with type 1 diabetes. Methods: A scoping review was conducted using five electronic databases and included studies published between the years 2000 and 2023. The search terms included: "Type 1 Diabetes Mellitus", "GIS mapping", "Juvenile Onset Diabetes Mellitus", "Spatial Epidemiology", "Spatial Clustering", "Spatial analysis", and "Geographic information system". Relevant full-text articles that met the inclusion criteria were selected for review. Results: The search identified 17 studies that met the criteria for inclusion in the review. More than half the studies were conducted before 2015 (n=11; 61%). All studies were conducted in High-Income Countries. More than 10 articles studied environmental factors, 3 of them focused on the environment, 6 of them included sociodemographic factors, and 1 study incorporated nutrition (as a variable) in environmental factors. 2 studies focused on the accessibility of health services by pediatric patients. Conclusion: Studies on type 1 diabetes highlight the complex relationship between incidence and risk, suggesting comprehensive prevention and treatment. Geographical mapping has potential in low- and middle-income nations, but further research is needed to develop innovative strategies. The importance of geomappping in understanding the risk factors for Type 1 Diabetes is highlighted in this scoping review, which also suggests a possible direction for focused interventions, particularly in settings with low resources.
Geographic information system mapping and predictors of glycemic control in children and youth with type 1 diabetes: A study from Western India Sushil Yewale, Navendu Chaudhary, Demi Miriam, Shital Bhor, Nimisha Dange, Nikhil Shah, Vaman Khadilkar, Anuradha Khadilkar Journal of Pediatric Endocrinology and Metabolism, 2025 Objectives Geographic Information System (GIS) mapping, is a novel way to provide insights into spatial distribution of type 1 diabetes (T1D) and associations between T1D outcomes and potential predictors. We aimed to explore GIS in children with T1D, and identify predictors of poor glycemic control. Methods Design: Cross-sectional; Participants: 402 children and youth (187 boys) with T1D. Place of residence (coordinates) of participants were geocoded in GIS. They were divided into two groups living in urban or peri-urban areas using ArcGIS Pro. The characteristics of urban/peri-urban living were linked to sociodemographic and biochemical data and spatial autocorrelation analysis was performed. Association between glycemic control and distance to our unit was studied. Results Mean age was 13.2 ± 4.7 years; 196 children were living in urban areas, 206 in peri-urban areas. There was significant difference in HbA1c between groups (Urban 9.9 (9.7, 10.2) %, Peri-urban 10.5 (10.1, 10.8) %) (p=0.004); mean difference 0.5 (0.1, 1.0) with poorer glycemic control and higher prevalence of vitamin D sufficiency in peri-urban and higher prevalence of hypothyroidism in urban areas. There was significant correlation between glycemic control (HbA1c) and distance to our unit r=0.108 (0.023, 0.218) (p=0.031). Individuals with an HbA1c ≥9.5 were residing farther away (58.9 (49.4, 68.5) km) as compared to those with HbA1c <9.5 (44.5 (35.1, 53.9) km) (p<0.05). Conclusions Children with T1D when grouped using GIS had differences in glycemic control and comorbidities; peri-urban participants and those residing further away from our unit had poorer glycemic control. Future efforts may be aimed at identifying centers and channelizing resources towards children showing poor glycemic control, thus optimizing disease management.
Neoteric machine learning approaches to diagnose the state of carotid artery Hariharan Anantharaman, Navendu Chaudhary, Vimal Raj International Journal of Medical Engineering and Informatics, 2024 This paper aims to develop machine learning models based on the information, data elements, and images captured on a carotid ultrasound, initiated with the capture, collation, and compilation of comprehensive carotid ultrasound reports of patients. Next is the analysis, extraction, cleaning, and compilation of data for the development of the models. In this neoteric approach, a set of supervised algorithms and image-deep learning algorithms are implemented, and different models are built and tested. The performance of all the models is par excellence, with the majority delivering accuracy over 75%. All the models, based on the varied machine learning algorithms, delivered acceptable and consistent accuracy - few models have even surpassed and delivered superior accuracy.
Water security: a Geospatial Framework for urban water resilience Jyoti Jain Tholiya, Navendu Chaudhary Water Supply, 2023 Urban water issues impacting sustainable development can be analyzed, modeled, and mapped through cutting-edge geospatial technologies; however, the water sector in developing countries suffers various spatial data-related problems such as limited coverage, unreliable data, limited coordination, and sharing. Available spatial data are limited to the aggregate level (i.e., national, state, and district levels) and lack details to make informed policy decisions and allocations. Despite significant advancements in geospatial technologies, their application and integration at the policy and decision-making level are rare. The current research provides a broad GIS-centric framework for actionable science, which focuses on real context and facilitates geospatial maps and theoretical and practical knowledge to address various water issues. The study demonstrates the application of the proposed Geospatial Framework from technical and institutional perspectives in water-stressed zones in Pune city, showing where and how to solve problems and where proposed actions can most impact creating a sustainable water-secured future. The framework makes it possible for everyone to explore datasets that can provide a baseline for research, and analysis, contribute to the process, propose, and act on solutions, and take the benefits of the outcomes and policy recommendations.
Determinants of geographical inequalities in domestic water supply across city of Pune, India Jyoti Jain Tholiya, Navendu Chaudhary, Bhuiyan Monwar Alam Water Supply, 2022 The water supply system in the city of Pune is affected due to the fast and chaotic development in and around the city. The quantity of per capita water supply and hours of supply per day varies substantially across the city. Some central parts of the city benefit from a large availability of water as compared to peripheral areas. This research employed Ordinary Least Squares (OLS) Regression, Geographically Weighted Regression (GWR), and the new version of GWR termed Multi-scale Geographically Weighted Regression (MGWR) models to better understand the factors behind observed spatial patterns of water supply distribution and to predict water supply in newly merged and proposed villages in the Pune city's periphery. Results showed statistical significance of slope; distance from service reservoirs; and water supply hour. MGWR and GWR models improved our results (adjusted R2: 0.916 and 0.710 respectively) significantly over those of the OLS model (adjusted R2: 0.252) and proved how local conditions influence variables. The maps of GWR display how a particular variable is highly important in some areas but less important in other parts of the city. The results from the current study can help decision-makers to make appropriate decisions for future planning to achieve Sustainable Development Goal number 6 (SDG #6), which focuses on achieving universal and equitable access to safe and affordable drinking water for all.
Urban Water Security: Geospatial Assessment For Water Supply Services In Pune, India Jyoti Jain Tholiya, Navendu Chaudhary Urban Water Journal, 2022 Despite significant advances in geospatial technologies, planners, policy, and decision-makers seldom integrate modern geospatial technologies to serve citizens with adequate water supply services. Several researchers have evaluated water supply services’ performance at the national, state, regional and city level; however, challenges remain to solve inequitable distribution of water supply services at the intra-city level. The current research evaluated water supply services’ performance through geospatial techniques in 141 water supply zones in Pune city. We computed performance indicators and water indexes for each water supply zone, analyzed spatially, and compared each zone based on the performance for water supply services. The results found that 50% of the city’s total water supply zones are high-performing, 26% medium-performing, and 24% low-performing zones for their water supply services. The study provides greater efficiencies in problem-solving, identifies areas of improvement, and enables decision-makers to allocate resources to achieve equitable water supply services to their citizens.
Eroding Ecosystem Services And Functions And Proposed Business Strategies: Problems And Prospects In And Around Village Devbag, Southern Coastal Maharashtra, India Indian Journal of Environmental Protection, 2021
Projecting changes in coastal morphology by satisfying prerequisite conditions of SLAMM software in context of sundarban 1 1 1* 1 2 International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences ISPRS Archives, 2018
Monitoring selected iceberg calving events in eastern antarctica using optical remote sensing 38th Asian Conference on Remote Sensing Space Applications Touching Human Lives Acrs 2017, 2017
Fuzzy TOPSIS-based geospatial framework for delineating groundwater potential zones in the Pune metropolitan catchment, western India DD Naik, N Chaudhary, JJ Tholiya Ecological Engineering & Environmental Technology 27 (4), 200-219 , 2026 2026
Predicting Mangrove Degradation Under Anthropogenic and Climatic Stressors: A Google Earth Engine-Based Case Study from Pichavaram R Adrina Niceline, NA Chaudhary, TP Singh ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information … , 2025 2025
A Scoping Review of GIS Mapping of Type 1 Diabetes in Children: Identifying Current Gaps and Future Research Directions Using PRISMA-ScR D Miriam, N Chaudhary, S Yewale, A Khadilkar Current Diabetes Reviews 21 (8), e260424229413 , 2025 2025
Geographic information system mapping and predictors of glycemic control in children and youth with type 1 diabetes: a study from Western India S Yewale, N Chaudhary, D Miriam, S Bhor, N Dange, N Shah, V Khadilkar, ... Journal of Pediatric Endocrinology and Metabolism 38 (1), 29-36 , 2025 2025
OPPORTUNITIES AND CHALLENGES IN HERITAGE CONSERVATION: HERITAGE WALKS, HERITAGE DRIVES, AND ON-SITE TALKS IN PUNE, INDIA Y Pisolkar, N Chaudhary, A Sharma, A Taskar International Journal of Conservation Science 16 (1), 165-174 , 2025 2025 Citations: 1
Geographic information system mapping and relationship with glycemic control in type 1 diabetes in western India S Yewale, N Chaudhary, D Miriam, S Bhor, N Dange, N Shah, V Khadilkar, ... HORMONE RESEARCH IN PAEDIATRICS 97, 91-91 , 2024 2024
Neoteric machine learning approaches to diagnose the state of carotid artery H Anantharaman, N Chaudhary, V Raj International Journal of Medical Engineering and Informatics 16 (3), 274-286 , 2024 2024 Citations: 1
Water security: a Geospatial Framework for urban water resilience J Jain Tholiya, N Chaudhary Water Supply 23 (8), 3013-3029 , 2023 2023 Citations: 7
Semantic segmentation of 3D LiDAR data using deep learning: a review of projection-based methods: Semantic segmentation of 3D LiDAR data using deep learning: A review of … A Jhaldiyal, N Chaudhary Applied Intelligence 53 (6), 6844-6855 , 2023 2023 Citations: 86
Urban water security: geospatial assessment for water supply services in Pune, India J Jain Tholiya, N Chaudhary Urban Water Journal 19 (6), 616-628 , 2022 2022 Citations: 9
Determinants of geographical inequalities in domestic water supply across city of Pune, India JJ Tholiya, N Chaudhary, BM Alam Water Supply 22 (2), 2148-2169 , 2022 2022 Citations: 13
Water security: A geospatial approach for water management in Pune City JJ Tholiya, N Chaudhary NDCWWC Journal 11 (1), 3-10 , 2022 2022
Identification of inorganic chemical formulas based on support vector machine and SURF key point descriptor S Mapari, N Chaudhary International Journal of Computing and Digital System , 2021 2021 Citations: 2
Water Security: A Geospatial Aproach for Water Management in Pune City JJ Tholiya, N Chaudhary Water and Energy International 64 (8), 75-75 , 2021 2021
Relationship between rice residue burning and increasing air pollution in North-west India S Bhadauriya, N Chaudhary, S Mamatha, SS Ray The International Archives of the Photogrammetry, Remote Sensing and Spatial … , 2020 2020 Citations: 7
Water security: A ge ospatial app roach for water management in Pune city JJ Tholiya, N Chaudhary NDCWWC Journal 9 (1), 12-19 , 2020 2020
Projecting Changes in Coastal Morphology by Satisfying Prerequisite Conditions of Slamm Software in Context of Sundarban A Chakraborty, A Basu, N Mukherjee, N Chaudhary, K Chakraborty The International Archives of the Photogrammetry, Remote Sensing and Spatial … , 2018 2018
ASSESSMENT OF FOREST FRAGMENTATION IN UTTARAKHAND, INDIA USING REMOTE SENSING AND GIS TECHNOLOGY A Dabas, G Areendran, K Raj, N Chaudhary, S Das Practical Geography and XXI Century Challenges, 674-674 , 2018 2018
Challenges for Wellness Tourism Development along Malvan Coast, Sindhudurg District, Maharashtra (India) Y Pisolkar, N Chaudhary Annual Research Journal of SCMS, Pune 6 , 2018 2018 Citations: 2
Study of Potential Risk of Dengue Outbreak Using Spatial Modeling Based on Socioeconomic Parameters. S Chopda, S Das, N Chaudhary, TP Singh Indian Journal of Public Health Research & Development 8 (4) , 2017 2017
MOST CITED SCHOLAR PUBLICATIONS
Inhibition of sulfate‐reducing bacteria by metal sulfide formation in bioremediation of acid mine drainage VP Utgikar, SM Harmon, N Chaudhary, HH Tabak, R Govind, JR Haines Environmental Toxicology: An International Journal 17 (1), 40-48 , 2002 2002 Citations: 338
Toxicity of metals and metal mixtures: analysis of concentration and time dependence for zinc and copper VP Utgikar, N Chaudhary, A Koeniger, HH Tabak, JR Haines, R Govind Water Research 38 (17), 3651-3658 , 2004 2004 Citations: 166
Acute toxicity of heavy metals to acetate‐utilizing mixed cultures of sulfate‐reducing bacteria: EC100 and EC50 VP Utgikar, BY Chen, N Chaudhary, HH Tabak, JR Haines, R Govind Environmental Toxicology and Chemistry 20 (12), 2662-2669 , 2001 2001 Citations: 101
Semantic segmentation of 3D LiDAR data using deep learning: a review of projection-based methods: Semantic segmentation of 3D LiDAR data using deep learning: A review of … A Jhaldiyal, N Chaudhary Applied Intelligence 53 (6), 6844-6855 , 2023 2023 Citations: 86
Multi-scale image segmentation and object-oriented processing for land cover classification RC Frohn, N Chaudhary GIScience & Remote Sensing 45 (4), 377-391 , 2008 2008 Citations: 29
Determinants of geographical inequalities in domestic water supply across city of Pune, India JJ Tholiya, N Chaudhary, BM Alam Water Supply 22 (2), 2148-2169 , 2022 2022 Citations: 13
Urban water security: geospatial assessment for water supply services in Pune, India J Jain Tholiya, N Chaudhary Urban Water Journal 19 (6), 616-628 , 2022 2022 Citations: 9
Water security: a Geospatial Framework for urban water resilience J Jain Tholiya, N Chaudhary Water Supply 23 (8), 3013-3029 , 2023 2023 Citations: 7
Relationship between rice residue burning and increasing air pollution in North-west India S Bhadauriya, N Chaudhary, S Mamatha, SS Ray The International Archives of the Photogrammetry, Remote Sensing and Spatial … , 2020 2020 Citations: 7
The problems of coastal tourism, environment and local sustainable development along Sindhudurg District, Coastal Maharashtra India Y Pisolkar, N Chaudhary Annual Research Journal of SCMS, Pune 4 , 2016 2016 Citations: 6
Usage of fuzzy rule and SOM based model to identify a handwritten chemical symbol or structures S Mapari, N Chaudhary, S Naik, P Metkewar 2017 Second International Conference on Electrical, Computer and … , 2017 2017 Citations: 4
Issues, Concerns, and Local Stakes: Future of Water Resources in Coastal Villages of Devbag and Tarkarli, Coastal Maharashtra, India NCY Pisolkar Reconsidering the Impact of Climate Change on Global Water Supply, Use, and … , 2016 2016 Citations: 3
Identification of inorganic chemical formulas based on support vector machine and SURF key point descriptor S Mapari, N Chaudhary International Journal of Computing and Digital System , 2021 2021 Citations: 2
Challenges for Wellness Tourism Development along Malvan Coast, Sindhudurg District, Maharashtra (India) Y Pisolkar, N Chaudhary Annual Research Journal of SCMS, Pune 6 , 2018 2018 Citations: 2
OPPORTUNITIES AND CHALLENGES IN HERITAGE CONSERVATION: HERITAGE WALKS, HERITAGE DRIVES, AND ON-SITE TALKS IN PUNE, INDIA Y Pisolkar, N Chaudhary, A Sharma, A Taskar International Journal of Conservation Science 16 (1), 165-174 , 2025 2025 Citations: 1
Neoteric machine learning approaches to diagnose the state of carotid artery H Anantharaman, N Chaudhary, V Raj International Journal of Medical Engineering and Informatics 16 (3), 274-286 , 2024 2024 Citations: 1
Strategies to Integrate Communities and Geo Spatial Technologies for Sustainable Development along Tarkarli-Devbag Coast, Maharashtra (India) Y Pisolkar, N Chaudhary Annual Research Journal of SCMS, Pune Volume 5, March 2017, 136 , 2016 2016 Citations: 1
Geospatial Technology: Opportunity in Fostering Social Enterpreneureship N Chaudhary Annual Research Journal of Symbiosis Centre for Management Studies, Pune 2 … , 2014 2014 Citations: 1
An object oriented approach to land cover classification for state of Ohio N Chaudhary University of Cincinnati , 2007 2007 Citations: 1
Fuzzy TOPSIS-based geospatial framework for delineating groundwater potential zones in the Pune metropolitan catchment, western India DD Naik, N Chaudhary, JJ Tholiya Ecological Engineering & Environmental Technology 27 (4), 200-219 , 2026 2026
