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Mr. Asheesh Sharma
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Academic Career Length
18Years (2009-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications12 February 2015 in Journal of Environmental Health Science and Engineering
Journal Article
RVRitesh Vijay
Ritesh VijayASAsheesh Sharma
Asheesh SharmaTCTapan Chakrabarti
Tapan ChakrabartiRGRajesh Gupta
Rajesh GuptaIn context of increasing traffic noise in urban India, the objective of the research study is to assess noise due to heterogeneous traffic conditions and the impact of honking on it. Traffic volume, noise levels, honking, road geometry and vehicular speed were measured on national highway, major and minor roads in Nagpur, India. Initial study showed lack of correlation between traffic volume and equivalent noise due to some factors, later identified as honking, road geometry and vehicular speed. Further, frequency analysis of traffic noise showed that honking contributed an additional 2 to 5 dB (A) noise, which is quite significant. Vehicular speed was also found to increase traffic noise. Statistical method of analysis of variance (ANOVA) confirms that frequent honking (p < 0.01) and vehicular speed (p < 0.05) have substantial impact on traffic noise apart from traffic volume and type of road. The study suggests that honking must also be a component in traffic noise assessment and to identify and monitor “No Honking” zones in urban agglomerations.
21 November 2016 in Soft Computing
Journal Article
Journal Article
ASAsheesh Sharma
Asheesh SharmaMPMandeep Poonia
Mandeep PooniaARAnkush Rai
Ankush RaiRBRajesh B. Biniwale
Rajesh B. BiniwaleFTFranziska Tügel
Franziska Tügel
Reinhard Hinkelmann +1
Flooding poses a significant threat as a prevalent natural disaster. To mitigate its impact, identifying flood-prone areas through susceptibility mapping is essential for effective flood risk management. This study conducted flood susceptibility mapping (FSM) in Chandrapur district, Maharashtra, India, using geographic information system (GIS)-based frequency ratio (FR) and Shannon’s entropy index (SEI) models. Seven flood-contributing factors were considered, and historical flood data were utilized for model training and testing. Model performance was evaluated using the area under the curve (AUC) metric. The AUC values of 0.982 for the SEI model and 0.966 for the FR model in the test dataset underscore the robust performance of both models. The results revealed that 5.4% and 8.1% (FR model) and 3.8% and 7.6% (SEI model) of the study area face very high and high risks of flooding, respectively. Comparative analysis indicated the superiority of the SEI model. The key limitations of the models are discussed. This study attempted to simplify the process for the easy and straightforward implementation of FR and SEI statistical flood susceptibility models along with key insights into the flood vulnerability of the study region.
1 January 2014 in Noise and Health
Journal Article
The objective of this study is to develop a traffic noise model under diverse traffic conditions in metropolitan cities. The model has been developed to calculate equivalent traffic noise based on four input variables i.e. equivalent traffic flow (Q e ), equivalent vehicle speed (S e ) and distance (d) and honking (h). The traffic data is collected and statistically analyzed in three different cases for 15-min during morning and evening rush hours. Case I represents congested traffic where equivalent vehicle speed is 30 km/h and case III represents calm traffic where no honking is recorded. The noise model showed better results than earlier developed noise model for Indian traffic conditions. A comparative assessment between present and earlier developed noise model has also been presented in the study. The model is validated with measured noise levels and the correlation coefficients between measured and predicted noise levels were found to be 0.75, 0.83 and 0.86 for case I, II and III respectively. The noise model performs reasonably well under different traffic conditions and could be implemented for traffic noise prediction at other region as well.
4 November 2023 in Earth Science Informatics
Journal Article
ADAsha Dhole
Asha Dhole
RKRakesh Kadaverugu
Rakesh KadaveruguSTSagar Tomar
Sagar Tomar
RBRajesh Biniwale
Rajesh BiniwaleASAsheesh Sharma
Asheesh Sharma1 February 2013 in Computers & Geosciences
Journal Article
About Me
Asheesh Sharma is a Principal Scientist at the CSIR-National Environmental Engineering Research Institute (CSIR-NEERI) with over 15 years of experience in Computer Science and Engineering. He has made significant contributions to national projects, notably the National Jal Jeevan Project, where he introduced IoT-based solutions for real-time water quality and quantity monitoring across 108 villages in India. He also developed software to detect leaks and contamination in drinking water supply lines, adopted by several Municipal Corporations, including Nagpur. Asheesh is an expert in GIS and remote sensing, applying these techniques to water resource projects. His mobile application 'Jalabhilekh' was used by the Puducherry Government to identify and revitalize over 300 water bodies, earning recognition from prominent officials. He serves on the Board of Studies at Nagpur University and has authored over 12 international journal papers, holds copyrights for 7 software programs, and contributed to 2 book chapters. His work includes more than 20 consultancy projects focusing on GIS and remote sensing applications, and 10 R&D projects addressing water distribution system challenges. Currently, Asheesh is involved in water resource management, specializing in hydrological modeling, land use impact assessment of basin responses, and urban flood modeling.