Vishal Sharma | Climate and Remote Sensing | Best Researcher Award

Assist Prof Dr. Vishal Sharma | Climate and Remote Sensing | Best Researcher Award

Indian Institute of Technology | India

๐Ÿ‘จโ€๐ŸŽ“ Profile

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๐Ÿ“ Summary

Dr. Vishal Sharma is a passionate researcher and educator in the field of Geomatics Engineering. Currently pursuing his Ph.D. at the Indian Institute of Technology (IIT) Roorkee, his research focuses on geospatial data science, remote sensing, and the application of machine learning for crop yield prediction and satellite image processing. He has extensive experience working with remote sensing data, GIS tools, and image analysis, contributing significantly to the development of innovative solutions for agricultural monitoring and environmental applications.

๐ŸŽ“ Education

Dr. Sharma’s academic journey has been marked by excellence in education. He is currently pursuing his Ph.D. at IIT Roorkee, where he holds a CGPA of 9.5. He completed his M.Tech. in 2013 from IIT Roorkee with a CGPA of 8.2, and earned his B.Tech. in 2010 from Hindustan College of Science and Technology. His foundational education in the sciences and engineering laid the groundwork for his research in geospatial technologies.

๐Ÿ’ผ Professional Experience

Dr. Sharma has accumulated diverse teaching and research experience, serving as an Assistant Professor-II at DIT University in Dehradun for over five years, as well as holding roles at IIMT in Meerut. His early career also included technical support work at RT Outsourcing. His academic roles have involved teaching, administrative duties, research mentoring, and curriculum development, which have honed his leadership and communication skills.

๐Ÿ“š Academic Contributions & Publications

Dr. Sharmaโ€™s research includes developing novel methodologies for crop yield prediction by integrating machine learning with satellite image analysis. His work on the Automatic Spectro-Temporal Feature Selection (ASTFS) method for optimal feature selection and the improvement of flood mapping models have been highly regarded in the academic community. His work is currently under review for publication in “Computers and Electronics in Agriculture.”

๐Ÿ–ฅ๏ธ Technical Skills

Dr. Sharma is proficient in advanced geospatial and image analysis tools such as Google Earth Engine (GEE), ERDAS Imagine, ArcGIS, and QGIS. His skills extend to programming with Python and RStudio for spatial data processing and machine learning applications. He is also experienced in using GIS software for natural resource mapping and image enhancement techniques.

๐Ÿ‘จโ€๐Ÿซ Teaching Experience

With over 7.5 years of teaching experience, Dr. Sharma has worked with undergraduate and postgraduate students across a variety of subjects, including Digital Image Processing, Geographic Information Systems (GIS), and Data Structures. He has supervised multiple M.Tech. students on research projects and guided them in developing practical applications of geospatial technologies. His approach to teaching combines theoretical knowledge with hands-on experience in GIS and image processing.

๐ŸŒ Research Interests

Dr. Sharmaโ€™s primary research interests lie in the fields of geospatial data science, remote sensing, and the application of machine learning in crop yield prediction. His work focuses on improving crop monitoring systems and optimizing satellite image analysis techniques. He is particularly interested in using machine learning algorithms to enhance the accuracy of environmental monitoring and mapping systems.

๐Ÿ“–ย  Top Noted Publications

Evaluating the Potential of 8 Band PlanetScope Dataset for Crop Classification Using Random Forest and Gradient Tree Boosting by Google Earth Engine ๐ŸŒพ๐Ÿ“Š
    • Authors: V Sharma, SK Ghosh
    • Citation: The International Archives of the Photogrammetry, Remote Sensing and Spatial โ€ฆ
    • Year: 2023
An Analysis of Multi-Source Temperature Datasets using Statistical Techniques ๐ŸŒก๏ธ๐Ÿ“Š
    • Authors: V Sharma, SK Ghosh
    • Citation: MAPAN, 1-15
    • Year: 2024
Temporal Trend Analysis of Climate Data by using Innovative Polygon Trend Analysis method for Hardwar, India ๐ŸŒ๐Ÿ“ˆ
    • Authors: V Sharma, SK Ghosh
    • Citation: 1
    • Year: 2022
Impact of Climate On Vegetation Indices Over Rainfed Districts of Uttarakhand, India ๐ŸŒฑโ˜”
    • Authors: V Sharma, SK Ghosh
    • Citation: The International Archives of the Photogrammetry, Remote Sensing and Spatial โ€ฆ
    • Year: 2022
Impact of Climate Parameters on Vegetation Using Different Indices in Hardiwar District, India ๐ŸŒž๐ŸŒพ
    • Authors: V Sharma, SK Ghosh
    • Citation: Proceedings of the 21st International Multidisciplinary Scientific โ€ฆ
    • Year: 2021
Generating Mustard Crop Maps Using PlanetScope High Resolution Dataset by Applying Machine Learning Algorithms ๐ŸŒพ๐Ÿค–
    • Authors: V Sharma, SK Ghosh
    • Citation: Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV 12727, 14-22
    • Year: 2023

Changjiang Liu | Remote sensing | Best Researcher Award

Dr. Changjiang Liu | Remote sensing | Best Researcher Award

Xinjiang Normal University, China

Author Profiles ๐Ÿ“š

Scopus

Orcid

Early Academic Pursuits ๐ŸŽ“

Dr. Changjiang Liu’s academic journey centers on the field of cartography and geographic information systems (GIS). His early pursuits focused on understanding the intricacies of remote sensing and its applications to environmental monitoring. This foundation laid the groundwork for his subsequent research on water environment extraction in arid regions, specifically lakes and reservoirs, using advanced remote sensing techniques. His work over the past five years has contributed significantly to the understanding of water dynamics in such challenging environments.

Professional Endeavors ๐Ÿ’ผ

Dr. Liu’s professional career has been marked by continuous engagement with cutting-edge research in remote sensing applications, particularly in the context of arid areas. He has secured various research grants, including the Open Project of Xinjiang Laboratory of Lake Environment and Resources in Arid Zone, and the Xinjiang Uygur Autonomous Region Natural Science Foundation. These projects have allowed him to explore the relationship between water quality, quantity, and environmental changes, contributing to the advancement of remote sensing technologies in resource management.

Contributions and Research Focus ๐Ÿ”ฌ

Dr. Liu’s primary research focuses on the remote sensing of water environments, especially in arid regions. His studies examine the spatiotemporal variations in water quality and quantity in lakes and reservoirs, emphasizing the role of shallow water bottom reflection and its impact on remote sensing data. By developing radiative transfer simulations, he has made significant strides in enhancing the accuracy of water monitoring. Additionally, his work on quantifying the radiation transmission mechanism in shallow water environments has improved the understanding of water behavior in arid areas.

Impact and Influence ๐ŸŒ

Dr. Liuโ€™s research has had a profound impact on the scientific community, with 10 SCI papers as the first author and numerous collaborations with international researchers. His work has been widely cited (913 times), reflecting its importance and influence in the fields of remote sensing and environmental science. His papers in prestigious journals like Journal of Cleaner Production and Science of the Total Environment have contributed to advancing knowledge on water quality monitoring, environmental protection, and sustainable resource management in arid regions.

Academic Cites ๐Ÿ“š

Dr. Liu has an H-Index of 16, which reflects the citation impact of his published work. With a total of 29 papers, his research is well-regarded in the field of environmental sciences, particularly in remote sensing. His influential articles continue to shape the discourse on water quality monitoring, environmental management, and the utilization of GIS and remote sensing technologies to assess and manage natural resources.

Technical Skills ๐Ÿ› ๏ธ

With a strong background in remote sensing and GIS, Dr. Liu possesses advanced technical skills in radiative transfer simulation, spatial data analysis, and environmental monitoring using remote sensing technologies. His expertise extends to the application of these techniques for analyzing water quality, quantity, and the environmental impacts of shallow water reservoirs and lakes. Dr. Liuโ€™s contributions to technical advancements in these areas have enhanced the accuracy of environmental assessments in arid regions.

Teaching Experience ๐ŸŽ

As a lecturer at Xinjiang Normal University, Dr. Liu imparts his knowledge and expertise to students, fostering a new generation of researchers and professionals in the fields of cartography, remote sensing, and GIS. His teaching experience includes guiding students through complex topics such as environmental monitoring, remote sensing analysis, and geographic information system applications, emphasizing both theoretical and practical aspects.

Legacy and Future Contributions ๐Ÿ”ฎ

Dr. Liu’s legacy lies in his pioneering work in the application of remote sensing for environmental monitoring in arid regions. His research has contributed to the development of more accurate techniques for assessing water quality and quantity in challenging environments. Moving forward, Dr. Liu is poised to make continued contributions to the field, with ongoing research projects that aim to refine remote sensing methodologies and improve sustainable water management practices. His future work will undoubtedly further the understanding of arid region water systems, with broad applications for resource management and environmental protection.

Top Noted Publications ๐Ÿ“–

An Advanced Spatiotemporal Fusion Model for Suspended Particulate Matter Monitoring in an Intermontane Lake
    • Authors: Zhang, F.; Duan, P.; Jim, C.Y.; Johnson, V.C.; Liu, C.; Chan, N.W.; Tan, M.L.; Kung, H.-T.; Shi, J.; Wang, W.
    • Journal: Remote Sensing
    • Year: 2023
Determining the main contributing factors to nutrient concentration in rivers in arid northwest China using partial least squares structural equation modeling
    • Authors: Wang, W.; Zhang, F.; Zhao, Q.; Liu, C.; Jim, C.Y.; Johnson, V.C.; Tan, M.L.
    • Journal: Journal of Environmental Management
    • Year: 2023
High-Resolution Planetscope Imagery and Machine Learning for Estimating Suspended Particulate Matter in the Ebinur Lake, Xinjiang, China
    • Authors: Pan Duan; Fei Zhang; Changjiang Liu; Mou Leong Tan; Jingchao Shi; Weiwei Wang; Yunfei Cai; Hsiang-Te Kung; Shengtian Yang
    • Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    • Year: 2023
Reconstruction of Sentinel Images for Suspended Particulate Matter Monitoring in Arid Regions
    • Authors: Duan, P.; Zhang, F.; Jim, C.-Y.; Tan, M.L.; Cai, Y.; Shi, J.; Liu, C.; Wang, W.; Wang, Z.
    • Journal: Remote Sensing
    • Year: 2023
Remote sensing for chromophoric dissolved organic matter (CDOM) monitoring research 2003โ€“2022: A bibliometric analysis based on the web of science core database
    • Authors: Li, Z.; Zhang, F.; Shi, J.; Chan, N.W.; Tan, M.L.; Kung, H.-T.; Liu, C.; Cheng, C.; Cai, Y.; Wang, W. et al.
    • Journal: Marine Pollution Bulletin
    • Year: 2023

Mohamed Zakzouk -Oil Spill Detectionย – Best Researcher Awardย 

Mr Mohamed Zakzouk -Oil Spill Detectionย - Best Researcher Awardย 

National Authority for Remote Sensing and Space Sciences - Egypt

Author Profile

Early Academic Pursuits

Mohamed Ramadan Abdallah Zakzouk began his academic journey in 2014, earning a Bachelor's degree in Petroleum Engineering from Suez University with honors and an impressive grade of 83.12%. He continued his pursuit of knowledge by obtaining a Master's degree in Petroleum Engineering from Cairo University in 2021, achieving a commendable GPA of 3.7.

Professional Endeavors

Zakzouk has accumulated a total of 7 years of experience, currently holding the position of Assistant Researcher at the National Authority for Remote Sensing and Space Sciences (NARSS) since 2021. Prior to this role, he served as a Research Assistant at NARSS from 2017 to 2020, focusing on environmental studies.

Contributions and Research Focus

His primary area of specialization is remote sensing, with a sub-division in oil spill detection. His notable contribution includes a master's thesis titled "Monitoring Oil Spills along the Egyptian Coasts Using Optical and Synthetic Aperture Radar Remote Sensing." He actively contributes to cutting-edge research projects, particularly in the mapping of oil spills along Egypt's coasts.

Accolades and Recognition

Zakzouk has received recognition for his dedication to research and development. He was a distinguished participant in the OceanChallenge4Africa Hackathon in 2022, ranking among the top 14 participants. Additionally, he secured the third place in the regional "UG-GMES IoT Innovation Challenge 2021" in Ghana, showcasing his expertise in utilizing artificial intelligence for oil spill detection.

Impact and Influence

His commitment is further demonstrated by the completion of seven research projects, a citation index of 40 in Scopus/Web of Science, and two consultancy and industry-sponsored projects. Zakzouk has also published four peer-reviewed articles and one conference paper, highlighting his impact on environmental monitoring.

Legacy and Future Contributions

With a diverse skill set, including expertise in satellite SAR image processing, spectral image processing, and proficiency in GIS software and Python programming, Zakzouk is poised to make significant future contributions to the field of environmental studies. As a Ph.D. student, he continues his academic pursuits, ensuring a lasting legacy in the realm of remote sensing and oil spill detection.

In conclusion, Mohamed Ramadan Abdallah Zakzouk's journey is marked by academic excellence, impactful research, and a commitment to advancing knowledge in environmental monitoring, positioning him as a promising and accomplished researcher in the field.

Notable Publication