Yousif Mousa | Remote Sensing | Best Researcher Award

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Dr. Yousif Mousa | Remote Sensing | Best Researcher Award

Adjunct Research Fellow, Curtin University and Al-Muthanna University Iraq

Dr. Yousif A. Mousa, a prominent academic in Surveying Engineering, specializes in Photogrammetry and Remote Sensing. He holds a Ph.D. from Curtin University and has a rich academic history, with research contributions focusing on satellite and UAV image processing. With extensive experience in academia, Dr. Mousa has taught at institutions such as Al-Muthanna University and Curtin University. His scientific activities, particularly in the areas of mapping, GIS, and urban planning, have led him to review for international journals and publish influential papers on building detection and DTM extraction.

Profile

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🎓 Education

Dr. Mousa completed his Ph.D. in Surveying Engineering, specializing in Photogrammetry and Remote Sensing, from Curtin University (2020). He also holds a Master’s degree in Surveying Engineering from Baghdad University (2010) and a Bachelor’s degree from the same institution (2007). His academic journey has been marked by strong analytical and technical foundations in geospatial sciences, laying the groundwork for his contributions in spatial analysis and remote sensing.

💼 Experience 

Dr. Mousa has been a Lecturer at Al-Muthanna University since 2010, teaching subjects related to surveying and photogrammetry. He has also served as a casual academic at Curtin University (2016-2020), tutoring in Photogrammetry, Applied Cartography, and Advanced Photogrammetry. Additionally, he worked as an Adjunct Research Fellow at Curtin University (2020-2024). His academic contributions extend to urban planning and GIS work for Muthanna Governorate and research on Sawa Lake’s water level decline for environmental protection.

🏆 Awards and Honors 

Dr. Mousa’s career has been distinguished by numerous accolades, including recognition for his groundbreaking research in remote sensing. His work has been published in leading journals like the Canadian Journal of Remote Sensing and Remote Sensing of Environment. His commitment to research excellence is reflected in his role as a reviewer for top journals in his field. His ongoing contributions have made a significant impact in the realms of photogrammetry, remote sensing, and GIS.

🔬 Research Focus

Dr. Mousa’s research focuses on remote sensing, photogrammetry, and GIS applications, particularly in building detection, DTM extraction, and environmental monitoring using UAV and satellite data. He has pioneered new approaches to spatial analysis, particularly in urban mapping and environmental monitoring, such as investigating Sawa Lake’s physical parameters and drought impacts. His ongoing work involves developing efficient algorithms for processing spatial data, advancing technologies for mapping and urban planning.

Conclusion 

Dr. Yousif A. Mousa is undoubtedly a leading figure in the field of Surveying Engineering, with particular strengths in Photogrammetry and Remote Sensing. His solid academic foundation, combined with significant contributions to environmental and geospatial research, make him a strong candidate for the Best Researcher Award. While there are opportunities to broaden his interdisciplinary collaborations and practical applications, his work has already proven to be valuable, impactful, and cutting-edge in the realm of remote sensing and geospatial technologies. His continued contributions promise to further the advancement of these fields and tackle pressing environmental issues.

Publication

  1. Title: Comparison Study of Three Building Regularization Algorithms
    Authors: Bulatov, D., Mousa, Y.A., Helmholz, P.
    Conference: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
    Year: 2024
    Volume: 10(4), pp. 59–66
    Citations: 0

 

  1. Title: Building Detection and Outlining in Multi-Modal Remote Sensor Data: A Stratified Approach
    Authors: Böge, M., Mousa, Y.A., Bulatov, D., Qiu, K.
    Journal: Canadian Journal of Remote Sensing
    Year: 2024
    Volume: 50(1), 2430490
    Citations: 0

 

  1. Title: Spatio-Temporal Analysis of Sawa Lake’s Physical Parameters between (1985–2020) and Drought Investigations Using Landsat Imageries
    Authors: Mousa, Y.A., Hasan, A.F., Helmholz, P.
    Journal: Remote Sensing
    Year: 2022
    Volume: 14(8), 1831
    Citations: 4

 

  1. Title: DTM Extraction and Building Detection in DSMs Having Large Holes
    Authors: Mousa, Y.A., Bulatov, D., Abed, F.M., Helmholz, P.
    Conference: Proceedings of SPIE – The International Society for Optical Engineering
    Year: 2021
    Volume: 11864, 118640H
    Citations: 3

 

  1. Title: Geo-locating Historical Survey Data and Images – A Case Study for the Canning River, Perth, Western Australia
    Authors: Helmholz, P., Mousa, Y., Snow, T., Tonkin, J., Lamont, W.
    Conference: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives
    Year: 2020
    Volume: 43(B4), pp. 575–582
    Citations: 1

 

  1. Title: Building Detection and Regularisation Using DSM and Imagery Information
    Authors: Mousa, Y.A., Helmholz, P., Belton, D., Bulatov, D.
    Journal: Photogrammetric Record
    Year: 2019
    Volume: 34(165), pp. 85–107
    Citations: 28

 

  1. Title: New DTM Extraction Approach from Airborne Images Derived DSM
    Authors: Mousa, Y.A.-K., Helmholz, P., Belton, D.
    Conference: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives
    Year: 2017
    Volume: 42(1W1), pp. 75–82
    Citations: 23

Michael | Geological Remote Sensing | Best Researcher Award

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Mr. Michael | Geological Remote Sensing | Best Researcher Award

University of Electronic Science and Technology of China,  China

Michael Appiah-Twum, a geoscientist, combines Artificial Intelligence and Machine Learning with advanced remote sensing to revolutionize natural resources and environmental management. He specializes in geospatial data analysis for geological surveys, mineral exploration, petroleum exploration, and environmental monitoring. With a solid foundation in geology, geophysics, and geochemistry, Michael integrates cutting-edge AI technologies for sustainable development. Currently pursuing a Ph.D. in Information and Communication Engineering at the University of Electronic Science and Technology of China, he excels in developing innovative AI-driven solutions for geological interpretation and resource management.

Profile

Orcid

Scholar

🎓 Education

Ph.D. in Information and Communication Engineering: University of Electronic Science and Technology of China (2020-Present); GPA: 3.52/4.0. Thesis: Deep Learning-based Multisource Geological Interpretation. M.Sc. in Information and Communication Engineering: University of Electronic Science and Technology of China (2020); GPA: 3.51/4.0. Thesis: Remote Sensing and Geological Survey of Gold Deposits. B.Sc. in Earth Science: University for Development Studies, Ghana (2014). Thesis: Atlas of Laterite and Exploration Implications.

🧑‍🏫 Experience

Researcher: Yangtze Delta Region Institute, UESTC (2022–Present) – Conducting AI/ML research for geological data analysis and mineral exploration. Course Instructor: UESTC (2023) – Designed curricula and taught Remote Sensing in Resources and Environment. Teaching Assistant: UESTC (2022–2023) – Conducted tutorials, guided projects, and mentored students in Remote Sensing. VIP Member: UESTC Green Club (2018–2020) – Advocated sustainable agriculture and environmental awareness. Electoral Official: Electoral Commission of Ghana (2015) – Managed polling operations during elections.

🏆 Awards and Honors

Top Ranked Ph.D. Student: University of Electronic Science and Technology of China (2020-Present). Graduate Student Member: IEEE Geoscience and Remote Sensing Society. Top Ranked M.Sc. Student: UESTC, Chengdu (2020). Research Excellence: Developed advanced geological interpretation models using AI/ML. Leadership Recognition: UESTC Green Club VIP for promoting sustainability and environmental stewardship.

🔬 Research Focus

Geological Surveys: Using remote sensing for mineral and petroleum exploration. AI/ML Applications: Implementing deep learning for geological and environmental data interpretation. Geospatial Analysis: Advanced modeling for resource exploration and sustainable development. Hydrology and Regolith: Focused on soil mechanics and hydrogeology for environmental management. Remote Sensing Integration: Leveraging UAVs and satellite imagery for accurate geoscientific data visualization.

Conclusion 

Michael Appiah-Twum is undoubtedly a strong contender for the Best Researcher Award, given his exceptional research in remote sensing, AI/ML applications, and resource management. His technical proficiency, leadership in academic settings, and dedication to sustainability make him a highly deserving candidate. With minor improvements in interdisciplinary collaboration and global outreach, his impact on the geoscience field could expand even further, contributing to more innovative and sustainable solutions in the industry.

📚Publications 

  1. Spatial distribution and trace element geochemistry of laterites in Kunche area: Implication for gold exploration targets in NW, Ghana
    Authors: E.D. Sunkari, M. Appiah-Twum, A. Lermi
    Journal: Journal of African Earth Sciences, 158, 103519 (2019)
    Citations: 34

 

  1. Data Centric Blockchain-Based Evaluation Approach to Analyze E-Commerce Reviews Using Machine and Deep Learning Techniques
    Authors: E.M. Acheampong, S. Zhou, Y. Liao, P. Atandoh, D. Addo, E. Antwi-Boasiako, et al.
    Conference: 2023 20th International Computer Conference on Wavelet Active Media
    Citations: 1

 

  1. Enhanced Word Embedding with CNN Using Word Order Information for Sentiment Analysis
    Authors: P. Atandoh, Z. Fengli, P.A. Hakeem, E.M. Acheampong, D. Addo, et al.
    Conference: 2023 20th International Computer Conference on Wavelet Active Media
    Citations: 1

 

  1. Assessing Landsat-9 in Identifying Lithology Using a Hybrid Metric-Learning and SVM Method Against Baseline Algorithms: A Case Study of the West African Craton
    Authors: M. Appiah-Twum, H. Jia, W. Xu
    Conference: IGARSS 2023 – IEEE International Geoscience and Remote Sensing Symposium
    Citations: 1

 

  1. Using Laterite Geochemistry for Exploration of Orogenic Gold Deposits in the Wa-Lawra Belt, NW Ghana: Kunche in Perspective
    Authors: E.D. Sunkari, M. Appiah-Twum, A. Lermi
    Journal: Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 7(3), 1137 (2018)
    Citations: 1

 

  1. DenseViT: A Hybrid CNN-Vision Transformer Model for an Improved Multisensor Lithological Classification
    Authors: M. Appiah-Twum, W. Xu, E.M. Acheampong
    Conference: IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium (2024)

 

  1. An Attention-Based LSTM Lithological Classification Using Multisensor Datasets
    Authors: M. Appiah-Twum, W. Xu
    Conference: IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium (2024)

 

  1. Lithological Classification Using Densely Connected Convolution Network on Landsat-9 and Aster Datasets in a Semi-Arid Environment
    Authors: M. Appiah-Twum, X. Wenbo, C.B. Mawuli, P. Atandoh
    Conference: 2023 20th International Computer Conference on Wavelet Active Media (2023