Xia Zhang | Remote Sensing | Women Researcher Award

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Prof. Xia Zhang | Remote Sensing | Women Researcher Award

Prof. Xia Zhang | Aerospace Information Research Institute Chinese Academy of Sciences | China

Prof. Xia Zhang is a distinguished Chinese scientist specializing in hyperspectral remote sensing, soil monitoring, and planetary science. She earned her Ph.D. in Cartography and GIS from the Chinese Academy of Sciences, following earlier degrees in Remote Sensing and GIS from Beijing Normal University and Agricultural Meteorology from Nanjing Institute of Meteorology. Currently a Professor at the Aerospace Information Research Institute, Chinese Academy of Sciences, she has devoted her career to advancing quantitative inversion algorithms for monitoring soil properties and developing mineral detection methods for celestial bodies. Her pioneering research has provided reliable systems for monitoring soil heavy metals, organic matter, and texture, as well as mapping lunar minerals and Martian water-bearing materials. Prof. Zhang has published numerous SCI papers, authored books, secured patents, and contributed to China’s major satellite and lunar exploration projects. Her work bridges earth sciences and space exploration, making significant contributions to both environmental sustainability and planetary understanding.

Publication Profile

Scopus

Education

Prof. Xia Zhang has pursued a strong academic journey in the field of geospatial sciences, remote sensing, and meteorology, which laid the foundation for her distinguished career in research and innovation. She earned her Ph.D. in Cartography and Geographic Information Systems from the Institute of Remote Sensing Applications at the Chinese Academy of Sciences, where she specialized in advanced applications of remote sensing and geographic technologies. Prior to her doctoral studies, she completed a Master’s degree in Remote Sensing and GIS from Beijing Normal University, gaining in-depth expertise in spatial data analysis and earth observation techniques. Her academic path began with a Bachelor’s degree in Agricultural Meteorology from the Nanjing Institute of Meteorology, where she developed a strong background in environmental monitoring, climate science, and agricultural systems. This comprehensive educational foundation enabled her to integrate meteorology, remote sensing, and geoinformatics, leading to her impactful contributions in soil monitoring, environmental sustainability, and planetary exploration.

Employment

Prof. Xia Zhang has built a distinguished professional career dedicated to hyperspectral remote sensing and earth observation research within the Chinese Academy of Sciences. She currently serves as a Professor at the Hyperspectral Remote Sensing Laboratory, Aerospace Information Research Institute, where she continues to advance scientific innovations in soil monitoring and planetary exploration. Previously, she held the position of Professor at the Institute of Remote Sensing and Digital Earth, where she contributed significantly to the development of quantitative inversion algorithms and environmental applications. Her academic journey includes long-term service at the Institute of Remote Sensing Applications, beginning as a Research Assistant at the Open Laboratory of Remote Sensing Science, later advancing to Assistant Professor and subsequently to Associate Professor, where she honed her expertise in satellite imaging and hyperspectral analysis. Through these progressive roles, Prof. Zhang has demonstrated remarkable leadership, consistent scientific contributions, and a strong commitment to advancing China’s capabilities in remote sensing technologies and global environmental studies.

Research Focus

Prof. Xia Zhang’s research primarily focuses on hyperspectral remote sensing, environmental monitoring, and precision soil assessment, placing her work at the intersection of geospatial sciences, agricultural sustainability, and planetary exploration. Her studies emphasize the development of advanced algorithms for soil property estimation, including soil organic matter, heavy metals, pH, moisture, and texture, using multi-source satellite and field spectroscopy data. By integrating hyperspectral and multispectral imagery from platforms such as GF-5, Zhuhai-1, Sentinel-2, and ZY1, she has contributed to innovative approaches for improving soil quality monitoring and land cover classification. Her expertise extends to addressing environmental complexities, mitigating data distortions, and applying machine learning and deep learning models for enhanced accuracy in spectral analysis. Beyond earth-focused applications, her research also explores mineral mapping on extraterrestrial surfaces, such as the Moon and Mars, deepening scientific understanding of planetary evolution. Overall, her contributions span soil science, environmental sustainability, and planetary remote sensing.

Publication Top Notes

Soil zinc content estimation using GF-5 hyperspectral image with mitigation of soil moisture influence
Year: 2025

Prediction and monitoring of soil pH using field reflectance spectroscopy and time-series Sentinel-2 remote sensing imagery
Year: 2025
Citations: 1

A mixed convolution and distance covariance matrix network for fine classification of corn straw cover types with fused hyperspectral and multispectral data
Year: 2024

Estimation of soil organic matter content by combining Zhuhai-1 hyperspectral and Sentinel-2A multispectral images
Year: 2024
Citations: 5

Evaluation of Soil As Concentration Estimation Method Based on Spectral Indices
Year: 2024
Citations: 3

Removal of environmental influences for estimating soil texture fractions based on ZY1 satellite hyperspectral images
Year: 2024
Citations: 9

Generating surface soil moisture at the 30 m resolution in grape-growing areas based on stacked ensemble learning
Year: 2024
Citations: 3

Conclusion

Prof. Xia Zhang stands out as an accomplished researcher whose innovations in hyperspectral remote sensing and planetary science strongly align with the goals of the Research for Women Researcher Award. With her solid track record in impactful publications, patents, and contributions to major scientific missions, she is highly suitable for this recognition, representing excellence, innovation, and leadership in women’s research.

 

Yujie Liu | Remote Sensing | Best Researcher Award

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Dr. Yujie Liu | Remote Sensing | Best Researcher Award

Dr. YujieLiu at Yinglin Branch Yunnan Institute of Forest Inventory and Planning, China

Liu Yujie, born in November 1992 in Wuxi, Jiangsu, is a dedicated researcher in forestry and entomology. A member of the Communist Party of China, he specializes in forestry quantitative remote sensing and pest control. With a strong academic background and extensive research experience, he has contributed significantly to understanding forest health and pest management. His work combines theoretical expertise with practical applications, aiding in environmental conservation efforts. He has served in both research and administrative roles, demonstrating a well-rounded career in forestry and agricultural policy. His contributions have been recognized in multiple scientific publications.

Publication Profile

Scopus

Academic Background

Liu Yujie pursued his undergraduate studies at Nanjing Forestry University (2011-2015), specializing in Forestry. He then continued his postgraduate education at Beijing Forestry University (2015-2022), where he enrolled in a combined Master’s and Doctoral program in Forest Protection under the guidance of Professor Luo Youqing. His academic journey focused on forestry quantitative remote sensing, entomology, and integrated pest control. His studies have provided him with in-depth knowledge of forest ecosystems, pest behavior, and advanced remote sensing techniques, equipping him to address critical challenges in forestry conservation and management.

Professional Background

Liu Yujie has gained extensive experience in both research and administrative roles. From October 2022 to January 2024, he worked at the Ningbo Haishu District Agriculture and Rural Bureau Office, focusing on agricultural comprehensive management and policy implementation. Following this, from January 2024 to July 2024, he served in the Ningbo Haishu District People’s Government Office, handling secretarial and governmental administrative duties. His experience bridges scientific research with practical policy applications, allowing him to contribute to forestry conservation, pest control strategies, and environmental sustainability. His career reflects a blend of academic excellence and hands-on governance experience.

Awards and Honors

Liu Yujie has received several accolades for his contributions to forestry research and pest control strategies. His studies on forest health assessment, remote sensing, and pest management have been published in high-impact journals such as the Chinese Journal of Applied Entomology and the Journal of Environmental Entomology. He has been recognized for his innovative approaches in pine wood nematode disease control, ash borer prevention, and volatile compound analysis in forestry. His work has earned him recognition in forestry research communities, establishing him as a promising researcher in forest protection and quantitative remote sensing applications.

Research Focus

Liu Yujie specializes in forestry quantitative remote sensing, pest management, and entomology. His research explores forest health monitoring using advanced remote sensing technologies and develops effective pest control strategies for protecting forest ecosystems. His studies on pine wood nematode disease, insect behavior, and chemical ecology contribute to sustainable forestry management. His work integrates data-driven approaches with field experiments, enhancing early detection and mitigation of forest pest outbreaks. By combining innovative technologies with traditional forestry principles, he aims to improve forest conservation efforts and address ecological challenges posed by invasive pests.

Publication Top Notes

📖 Acoustic detection of the wood borer, Semanotus bifasciatus, as an early monitoring technology

Year: 2022 📅 | Cited by: 5 🔍 | Journal: Pest Management Science

Conclusion

Liu Yujie is a highly qualified researcher specializing in forestry quantitative remote sensing, pest control, and entomology, with a Master’s and PhD from Beijing Forestry University. His strong academic background, impactful research publications (CSCD, CSSCI indexed), and practical experience in both scientific studies and governmental roles make him a well-rounded candidate for the Best Researcher Award. His work on forest health assessment, pest monitoring, and remote sensing applications has significant relevance to contemporary environmental challenges. While some administrative responsibilities may have momentarily shifted his research focus, his contributions to forestry science, innovative research, and policy applications solidify his strong candidacy for this prestigious award.

 

 

Getie Gebrie Eshetie | Geomatics Engineering | Best Researcher Award

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Mr. Getie Gebrie Eshetie | Geomatics Engineering | Best ResearGeomatics Engineeringcher Award

Woldia, Bahir Dar University, Ethiopia

Getie Gebrie Eshetie is a dedicated academic and researcher specializing in land administration and geodesy. Currently a lecturer at Woldia University in Ethiopia, he has significantly contributed to the field through his roles as the Head of the Department of Land Administration and Surveying, Dean of the School of Land Administration, and Legal Entity Appointed Representative for the Li4LaM project. As an active member of the East Africa Land Administration Network (EALAN), he is committed to advancing land management and governance in Ethiopia and beyond. 📚🌍

Profile

Google Scholar

Han Gao | Radar Remote Sensing | Best Researcher Award

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Dr. Han Gao | Radar Remote Sensing | Best Researcher Award

Dr. Han Gao, China University of Petroleum (East China),China

Dr. Han Gao is an accomplished researcher at the College of Oceanography and Space Informatics, China University of Petroleum (East China). Specializing in radar remote sensing and microwave vision theory, his expertise extends to time series PolSAR data processing and remote sensing monitoring of flood disasters. Proficient in MATLAB, Python, and C++, he has developed innovative methods in crop classification and flood disaster monitoring, with significant applications in various Chinese provinces. Dr. Gao’s work has been published in top-tier journals like IEEE TGRS and RSE, earning substantial citations and recognition. 📡💻🛰️

Publication Profile

Orcid

Google Scholar

Education

Dr. Han Gao pursued his academic journey at Central South University, where he obtained a Ph.D. in Photogrammetry and Remote Sensing from the College of Geosciences and Info-physics in June 2022. Prior to his doctorate, he completed a Master’s degree in Geomatics Engineering in June 2018, following his Bachelor’s degree in the same field in June 2015. His extensive education has laid a solid foundation for his research in remote sensing and geosciences. 📡💻🛰️

 

Research Focus 🌍🔬

Dr. Han Gao’s research primarily focuses on advanced remote sensing techniques, particularly in radar remote sensing and microwave vision theory. He has developed innovative methods for crop classification using time-series dual-polarization SAR datasets, integrating data from various sources like GF-3 PolSAR and Sentinel-2A. His work extends to flood disaster monitoring and the development of adaptive filters for PolSAR data. Dr. Gao’s research also includes forest height estimation and phase optimization for DS-InSAR. His significant contributions are published in high-impact journals, highlighting his expertise in agricultural and ecological remote sensing. 🌾📡🌳

 

Publication Top Notes

  1. A novel crop classification method based on ppfSVM classifier with time-series alignment kernel from dual-polarization SAR datasets – H Gao, C Wang, G Wang, H Fu, J Zhu – Remote Sensing of Environment 264, 112628 – 32 citations – 2021 📅📈
  2. A new crop classification method based on the time-varying feature curves of time series dual-polarization Sentinel-1 data sets – H Gao, C Wang, G Wang, Q Li, J Zhu – IEEE Geoscience and Remote Sensing Letters 17 (7), 1183-1187 – 30 citations – 2019 📅📈
  3. A crop classification method integrating GF-3 PolSAR and Sentinel-2A optical data in the Dongting Lake Basin – H Gao, C Wang, G Wang, J Zhu, Y Tang, P Shen, Z Zhu – Sensors 18 (9), 3139 – 28 citations – 2018 📅📈
  4. An adaptive nonlocal mean filter for PolSAR data with shape-adaptive patches matching – P Shen, C Wang, H Gao, J Zhu – Sensors 18 (7), 2215 – 21 citations – 2018 📅📈
  5. Forest height estimation using PolInSAR optimal normal matrix constraint and cross-iteration method – C Wu, C Wang, P Shen, J Zhu, H Fu, H Gao – IEEE Geoscience and Remote Sensing Letters 16 (8), 1245-1249 – 16 citations – 2019 📅📈
  6. TSPol-ASLIC: Adaptive superpixel generation with local iterative clustering for time-series quad-and dual-polarization SAR data – H Gao, C Wang, D Xiang, J Ye, G Wang – IEEE Transactions on Geoscience and Remote Sensing 60, 1-15 – 13 citations – 2021 📅📈
  7. A phase optimization method for DS-InSAR based on SKP decomposition from quad-polarized data – G Wang, B Xu, Z Li, H Fu, H Gao, J Wan, C Wang – IEEE Geoscience and Remote Sensing Letters 19, 1-5 – 13 citations – 2021 📅📈
  8. Fusion of spatially heterogeneous GNSS and InSAR deformation data using a multiresolution segmentation algorithm and its application in the inversion of slip distribution – H Yan, W Dai, H Liu, H Gao, WR Neely, W Xu – Remote Sensing 14 (14), 3293 – 5 citations – 2022 📅📈

Sajjad Hussain | Remote sensing Award | Best Researcher Award

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Mr. Sajjad Hussain | Remote sensing Award | Best Researcher Award

Mr. Sajjad Hussain, COMSATS University Islamabad, Pakistan

🌍 Mr. Sajjad Hussain is a PhD student in Environmental Sciences at COMSATS University Islamabad, Vehari Campus (2023-2026). With a strong academic foundation, he holds an MS in Environmental Science (CGPA 3.43/4), an MEd in Science Education, and an MSc in Mathematics (CGPA 3.53/4). His research focuses on land use and climate change in Southern Punjab. Proficient in GIS software and data analysis, he has published extensively in high-impact journals. His notable works include studies on land cover changes, groundwater quality, and urban growth predictions. 🌿📊

Publication Profile

Google Scholar

Academic Qualification

🌟 Mr. Sajjad Hussain is currently pursuing a PhD in Environmental Sciences (2023-2026) at COMSATS University Islamabad, Vehari Campus. He holds an MS in Environmental Science (CGPA 3.43/4) from the same institution (2017-2019) and an MEd in Science Education (65%) from Alama Iqbal Open University Islamabad (2019-2020). His academic journey also includes an MSc in Mathematics (CGPA 3.53/4) from Government College University Faisalabad (2014-2016), a BSc in Physics and Double Math (70.37%) from Government Postgraduate College Burewala (2012-2014), and an FSc in Pre-Engineering (64.45%) from the same college (2010-2012). He began his educational path with a Matriculation in Science (86.19%) from Government High School Machianwala District Vehari (2008-2010). 🎓📚✨

 

📚 Research Focus

Mr. Sajjad Hussain’s research primarily focuses on environmental sciences with a particular emphasis on land use and land cover (LULC) changes, climate change, and sustainable agriculture. His studies utilize Geographic Information Systems (GIS) and remote sensing techniques to analyze environmental transformations over time, especially in various regions of Pakistan. His notable works include assessing the impact of LULC on land surface temperature, monitoring vegetation cover dynamics, and evaluating water use efficiency in agriculture. Hussain’s interdisciplinary approach integrates environmental science, geospatial technology, and sustainable agricultural practices. 🌱🛰️📈

 

📚 Publications

  1. Using GIS tools to detect the land use/land cover changes during forty years in Lodhran District of Pakistan – Environmental Science and Pollution Research, 2020. Cited by: 233 🌍
  2. Fate of organic and inorganic pollutants in paddy soils – Environmental pollution of paddy soils, 2018. Cited by: 187 🌾
  3. Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan – Geology, Ecology, and Landscapes, 2023. Cited by: 94 🌡️
  4. Study of land cover/land use changes using RS and GIS: a case study of Multan district, Pakistan – Environmental monitoring and assessment, 2020. Cited by: 89 🛰️
  5. Improving water use efficiency in agronomic crop production – Agronomic Crops: Volume 2: Management Practices, 2019. Cited by: 88 💧
  6. Spatiotemporal variation in land use land cover in the response to local climate change using multispectral remote sensing data – Land, 2022. Cited by: 82 📅
  7. Land use and land cover (LULC) change analysis using TM, ETM+ and OLI Landsat images in district of Okara, Punjab, Pakistan – Physics and Chemistry of the Earth, 2022. Cited by: 75 🌎
  8. Monitoring of land use–land cover change and potential causal factors of climate change in Jhelum district, Punjab, Pakistan, through GIS and multi-temporal satellite data – Land, 2021. Cited by: 75 🔍
  9. Monitoring the dynamic changes in vegetation cover using spatio-temporal remote sensing data from 1984 to 2020 – Atmosphere, 2022. Cited by: 49 📈
  10. Effect of plant growth promoting bacteria and drought on spring maize (Zea mays L.) – Pak. J. Bot, 2021. Cited by: 46 🌽