Dr. Manohar Yadav
Assistant Professor
GIS Cell
Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India-211004
E-mail: ssmyadav[at]mnnit[dot]ac[dot]in
Telephone: +91-532-227-1344(O) +91-9559753727(M)
Teaching
- Current Courses:
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- Undergraduate (UG) courses:
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- GI17503: Introduction to Remote Sensing
- GI18502: Fundamentals of LiDAR Technology
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- Postgraduate (PG) courses:
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- GI21301: Principles of Remote Sensing
- GI21201: Geoinformatics Lab I
- GI22303: LiDAR Technology
- GI22201: Geoinformatics Lab II
- GI17503: Introduction to Remote Sensing
- GI18502: Fundamentals of LiDAR Technology
- Past Courses:
- CE-365: Precision Remote Sensing
- GI2201: Satellite Image Processing
- GI2217: Geoinformatics for Transportation
- GI2114: Disaster and Hazard Mitigation, Assessment and Management
Education
- Undergraduate:
- B.Tech. in Electronics and Communication Engineering [1st Division] Uttar Pradesh Technical University (UPTU), Lucknow, India.
- Postgraduate:
- M.Tech. in Specialization - Geoinformatics [8.69/10], Indian Institute of Technology (IIT) Kanpur, India [Thesis Title: Laser scanner integration with INS-GPS for Mobile Mapping] Supervisor: Prof. Bharat Lohani, IIT Kanpur. [Recognition: Thesis work was published in SCIE-indexed international Journal and received best paper publication award of a year].
- Doctoral:
- PhD (awarded) [9.5/10] Thesis Title: Roadway Features Inventorization Using Mobile Terrestrial Laser Scanning) [One of the thesis Supervisors from IIT Kanpur]
Areas of Research
- High resolution remote sensing (Airborne, UAV-based, mobile and ground-based LiDAR) data generation, and processing for scientific and industrial applications in various sectors, such as urban planning, smart city mission, forestry, transportation (Roads and Rails), archaeology, agriculture, autonomous vehicles, topographic mapping, building construction, renewable energy and many more.
- Multi-sensor integration and data fusion
- Objects detection and classification using LiDAR point cloud and image data: Rule-based, Machine learning and Deep learning methods
- GIScience and Renewable Energy
- GIScience and Precision Agriculture
Research ID's
- Researcher ID:-(Web of Science): Z-3741-2019
- Scopus Scholar ID:-55966231500
- ORCID ID:-0000-0003-0239-1183
- Vidawan ID:-104653
- Google Scholar ID:-jatcpJwAAAAJ