Mr. Zhenjiang Liu | Geodetic Analysis Awards | Best Researcher Award

Mr. Zhenjiang Liu | Geodetic Analysis Awards | Best Researcher Awardย 

Mr. Zhenjiang Liu, Chang’an University, China

Zhenjiang Liu is a dedicated Ph.D. candidate at Changโ€™an University, specializing in InSAR observation and earthquake cycle modeling. With a robust academic background, he earned his Bachelor’s degree in Surveying and Mapping Engineering from the Institute of Disaster Prevention, achieving an impressive GPA of 4.2/5.0. He continued his studies at Changโ€™an University, obtaining a Masterโ€™s degree in Geodesy and Survey Engineering with a GPA of 3.6/5.0. Currently, as a Ph.D. candidate, Liu maintains a GPA of 3.9/5.0 while actively engaging in groundbreaking research. His work focuses on the co-seismic mechanisms and stress evolution of significant earthquakes, demonstrated through his contributions to various high-impact publications in esteemed journals. Liu’s research includes emergency analyses of major earthquake events such as the Menyuan, Luding, and Taitung earthquakes, as well as the Turkey and Herat earthquake sequences. He has also participated in field investigations, demonstrating his commitment to advancing knowledge in geodesy and seismic studies.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Based on the provided information, Zhenjiang Liu emerges as a highly suitable candidate for the Best Researcher Award. His academic journey, extensive research contributions, and innovative methodologies in InSAR (Interferometric Synthetic Aperture Radar) observations and earthquake cycle modeling demonstrate a profound commitment to advancing the field of geodesy and disaster prevention.

๐Ÿ“š Education Background:

  • Ph.D. Candidate (GPA 3.9/5.0) – Changโ€™an University, Geodesy and Survey Engineering (2022-Present)
  • Masterโ€™s Degree (GPA 3.6/5.0) – Changโ€™an University, Geodesy and Survey Engineering (September 2020 – June 2022)
  • Bachelorโ€™s Degree (GPA 4.2/5.0) – Institute of Disaster Prevention, Surveying and Mapping Engineering (September 2016 – June 2020)

๐Ÿ” Research Interests:

Zhenjiang Liu specializes in InSAR observation and earthquake cycle modeling. His research focuses on the mechanisms of seismic events, employing advanced radar interferometry techniques to analyze and monitor earthquake activities.

๐ŸŒ Research Engagement:

Zhenjiang has actively participated in emergency research on significant earthquakes, including:

  • Menyuan Earthquake (2022)
  • Luding Earthquake (2022)
  • Taitung Earthquake Sequence (2022)
  • Turkey Earthquake Sequence (2023)
  • Herat Earthquake Sequence (2023)
  • Jishishan Earthquake (2023)
  • Wushi Earthquake (2024)
  • Hualien Earthquake (2024)

๐Ÿ”ฌ Field Investigations:

He has also taken part in field scientific investigations related to the Menyuan and Luding earthquakes, contributing valuable data to his research.

๐ŸŒŸ Contribution to Science:

Zhenjiang Liu’s work has significantly advanced the understanding of seismic activities and hazard assessments, making vital contributions to the field of geodesy and remote sensing.

Publicationย Top Notes

A New Method for the Identification of Earthquake-Damaged Buildings Using Sentinel-1 Multitemporal Coherence Optimized by Homogeneous SAR Pixels and Histogram Matching

Characterizing the evolution of the Daguangbao landslide nearly 15ย years after the 2008 Wenchuan earthquake by InSAR observations

Mapping Surface Deformation in Rwanda and Neighboring Areas Using SBAS-InSAR

Automatic detection of active geohazards with millimeter-to-meter-scale deformation and quantitative analysis of factors influencing spatial distribution: A case study in the Hexi corridor, China

Stress Triggering and Future Seismic Hazards Implied by Four Large Earthquakes in the Pamir from 2015 to 2023 Revealed by Sentinel-1 Radar Interferometry

Reduction of Atmospheric Effects on InSAR Observations Through Incorporation of GACOS and PCA Into Small Baseline Subset InSAR

Coโ€ and Postโ€Seismic Mechanisms of the 2020 Mw 6.3 Yutian Earthquake and Local Stress Evolution

Yongquan Wang | Remote Sensing | Best Researcher Award

Dr.Yongquan Wang | Remote Sensing | Best Researcher Award

PhD atย  shenzhen university, China

Yongquan Wang is a dedicated researcher specializing in ocean color and radiative transfer. With a robust academic background, he holds an M.S. and Ph.D. in Urban Informatics from Shenzhen University and a B.S. in Geodesy and Geomatics from Anhui Agriculture University. Recognized as an Outstanding Graduate Student of Guangdong Province, Yongquan’s research focuses on innovative techniques for environmental monitoring, particularly in retrieving oceanic particulate organic nitrogen (PON) concentrations. His work integrates advanced imaging technologies and data processing skills, reflecting a commitment to addressing pressing ecological challenges.

Profile:

Scopus Profile

Strengths for the Award:

Yongquan Wang has demonstrated exceptional research capabilities in the fields of ocean color and radiative transfer. His focus on retrieving oceanic particulate organic nitrogen (PON) concentrations from image data shows innovative thinking and application of advanced techniques. His research work is well-supported by a solid academic background, achieving high GPAs and recognition as an Outstanding Graduate Student of Guangdong Province. The breadth of his publications in reputable journals like IEEE Transactions and Remote Sensing further establishes his expertise. Additionally, his contributions to novel methods using aerial imaging and UAV technology in environmental monitoring underscore his ability to address real-world challenges effectively.

Areas for Improvement:

While Yongquan has made significant strides in his research, he could enhance his impact by diversifying his research collaborations, particularly with interdisciplinary teams that include ecologists and data scientists. Engaging more with broader environmental policy discussions could also strengthen the societal relevance of his work. Additionally, expanding his outreach to communicate research findings to non-specialist audiences may increase public engagement and understanding of his work.

Education:

Yongquan Wang completed his M.S. and Ph.D. at the School of Architecture and Urban Planning, Shenzhen University, where he achieved a GPA of 86.7/100. Prior to this, he earned a B.S. in Geodesy and Geomatics from Anhui Agriculture University, graduating with a GPA of 88.8/100. His educational journey has been marked by academic excellence, including multiple scholarships for outstanding performance. This strong foundation has equipped him with the knowledge and skills to engage in impactful research in ocean color remote sensing and related fields.

Experience:

Yongquan Wang has amassed significant research experience since September 2018, focusing on the retrieval of oceanic particulate organic nitrogen (PON) concentrations from image data. He has explored the development of retrieval models for global ocean monitoring and atmospheric corrections under weak light conditions. Additionally, he has engaged in innovative projects using tethered UAVs for emergency surveying and mapping, demonstrating versatility in applying technology to real-world problems. His work reflects a commitment to advancing remote sensing methodologies for environmental applications.

Research Focus:

Yongquanโ€™s research centers on ocean color and radiative transfer, particularly the retrieval of oceanic particulate organic nitrogen (PON) concentrations. He investigates bio-optical proxies for PON retrieval and develops models to analyze monthly variations in global ocean PON levels. His work also addresses atmospheric correction techniques in optically complex waters, enhancing the accuracy of remote sensing data. By leveraging advanced imaging technologies and data processing skills, Yongquan aims to contribute valuable insights into oceanic health and environmental sustainability.

Publications Top Notes:

  1. Towards Applicable Retrieval Models of Oceanic Particulate Organic Nitrogen Concentrations for Multiple Ocean Color Satellite Missions ๐Ÿ“„
  2. Ocean Colour Atmospheric Correction for Optically Complex Waters under High Solar Zenith Angles: Facilitating Frequent Diurnal Monitoring and Management ๐ŸŒŠ
  3. Remote Sensing Video Production and Traffic Information Extraction Based on Urban Skyline ๐Ÿšฆ
  4. Spatiotemporal Dynamics and Geo-environmental Factors Influencing Mangrove Gross Primary Productivity during 2000โ€“2020 in Gaoqiao Mangrove Reserve, China ๐ŸŒณ
  5. Estimating Particulate Organic Nitrogen Concentrations in the Surface Ocean from Ocean Color Remote Sensing Data ๐Ÿ”
  6. Satellite Retrieval of Oceanic Particulate Organic Nitrogen Concentration ๐ŸŒ
  7. A Glimpse of Ocean Color Remote Sensing From Moon-Based Earth Observations ๐ŸŒ™
  8. Framework to Create Cloud-Free Remote Sensing Data Using Passenger Aircraft as the Platform โœˆ๏ธ
  9. Dynamic Earth Observation Based on an Urban Skyline: A New Remote Sensing Approach for Urban Emergency Response ๐Ÿ™๏ธ
  10. Volunteered Remote Sensing Data Generation with Air Passengers as Sensors ๐Ÿš

Conclusion:

Yongquan Wang is a strong candidate for the Research for Best Researcher Award, with notable achievements and contributions in oceanographic research. His innovative approaches and demonstrated academic excellence position him well for recognition. Continued efforts to broaden his collaboration network and enhance public engagement will further solidify his status as a leading researcher in his field.