Ayomide Olubaju | Remote sensing | Best Researcher Award

Published on by Plant Scientist

Mr. Ayomide Olubaju | Remote sensing | Best Researcher Award

Abiola Ajimobi Technical University | Nigeria

Olubaju Ayomide Emmanuel is a dedicated and innovative researcher specializing in Geographic Information Systems (GIS) and Remote Sensing, with growing recognition for his contributions to geospatial science. He holds an M.Tech. in Surveying and Geoinformatics (Remote Sensing) and a B.Tech. in the same discipline from the Federal University of Technology, Akure, Nigeria. Currently serving as an Assistant Lecturer at Abiola Ajimobi Technical University, Ibadan, he combines teaching and research to advance environmental monitoring and sustainable urban planning. His research interests encompass environmental degradation, climate change impact assessment, urban informatics, multi-sensor remote sensing, forest species monitoring, and machine learning applications in geospatial analysis. Olubaju has authored and co-authored several peer-reviewed publications focusing on urbanization, forest ecology, and mining-induced land degradation, accumulating 3 documents, 4 citations, and an h-index of 2. He has participated in national and international conferences, workshops, and collaborative projects addressing climate resilience and spatial data science. A member of professional societies including ISPRS, IAENG, and the Nigeria Institution of Surveyors, Olubaju’s academic and professional journey reflects a commitment to interdisciplinary research and data-driven solutions for sustainable environmental management. His goal is to pursue a Ph.D. to deepen his expertise and contribute to innovative geospatial applications in global environmental research.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Akinbiola, S., Akinsola, J. E. T., Ajagbe, S. A., Salami, A., Olubaju, A., Awotoye, O., & Awoleye, O. M. (2025). Artificial intelligence technique for prediction of carbon stocks and uncertainty estimates in tropical forests. SN Computer Science.

Akinbiola, S., Salami, A. T., Olubaju, A. E., & Awotoye, O. O. (2025). Assessing the impact of environmental variables on the distribution of keystone tree species in Omo-Shasha-Oluwa forest complex using MaxEnt modelling techniques. SSRN Electronic Journal.

Ibukun, J. A., Olubaju, A. E., Thomas, S. F., Sodipo, E. O., Akinbiola, S. A., Oyetunji, S. O., Shitu, K., Kucher, D. E., & Tariq, A. (2025). Modeling mining-induced land degradation in Itagunmodi: A multi-temporal machine learning approach with random forest and gradient boosting. Trees, Forests and People, 21, 100926.

Ibukun, J. A., Olubaju, A. E., Thomas, S. F., Sodipo, E. O., Akinbiola, S. A., Rebouh, N. Y., Said, Y., & Tariq, A. (2025). Assessing vegetation degradation and thermal effects of artisanal small-scale mining using remote sensing time series data. Land Degradation & Development.

Akinbiola, S., Salami, A. T., Olubaju, A. E., & Awotoye, O. O. (2024). Assessing the impact of environmental variables on the distribution of keystone tree species in Omo-Shasha-Oluwa forest complex using MaxEnt modelling techniques. SSRN Electronic Journal.

Karim Solaimani | Remote Sensing | Best Researcher Award

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Prof. Karim Solaimani | Remote Sensing | Best Researcher Award

Sari Agricultural Sciences and Natural Resources, Iran

Professor Karim Solaimani is a distinguished Iranian environmental scientist and hydrologist affiliated with the Sari Agricultural Sciences and Natural Resources University (SANRU) under the Ministry of Science, Research and Technology of Iran. He earned his Ph.D. in Environmental Remote Sensing and Hydrology from the University of Glasgow, UK, and has since established himself as an eminent scholar in the fields of remote sensing, GIS applications, hydrology, watershed management, and land use planning. His extensive academic contributions include over 85 peer-reviewed journal articles, widely cited in international scientific databases, reflecting significant impact and global recognition. Professor Solaimani’s research integrates geospatial technologies for environmental modeling, sediment yield assessment, and natural hazard mapping, focusing particularly on Iran’s complex hydrological systems. He has received the Excellent National Teaching and Research Professor Award, acknowledging his outstanding contributions to education and research. Over his career, he has collaborated with multidisciplinary teams, supervised numerous postgraduate students, and contributed to the advancement of environmental science through innovation, mentorship, and applied research. His enduring commitment to sustainable land and water resource management continues to influence both academic and practical environmental policy developments in Iran and beyond.

Profile: Orcid

Featured Publications

Solaimani, K., Darvishi, S., & Shokrian, F. (2024). Assessment of machine learning algorithms and new hybrid multi-criteria analysis for flood hazard and mapping. Environmental Science and Pollution Research.

Solaimani, K. (2023). A new approach to landslide assessment using Depth-Number fractal model. ECOPERSIA.

Solaimani, K. (2023). Evaluation of effective criteria on flood risk based on network analysis process and GIS in Vazroud basin of Mazandaran province. Ecohydrology.

Solaimani, K. (2023). Investigating alterations in the underground water level of Ravansar-Sanjabi Plain under CIMP5 climate scenarios. Desert Ecosystem Engineering.

Solaimani, K. (2023). Monitoring and forecasting of spatiotemporal changes in land use and the growth of Kermanshah Township using remote sensing and the CA-Markov model. Urban Structure and Function Studies.