Prof Oluibukun Gbenga Ajayi

Biography

Prof Oluibukun earned a Bachelor’s degree from the Federal University of Technology, Minna, Nigeria, with a First Class Honours and a Master’s degree from the University of Lagos, Nigeria, with Distinction, both in Surveying and Geoinformatics. He also holds a PhD in Surveying and Geoinformatics from the Federal University of Technology, Minna, Nigeria, where he worked as a lecturer for over 9 years before joining the Department of Land and Spatial Science in 2022 as a Senior Lecturer. He has won different research grants and has (co)authored over 50 scientific articles. He is the recipient of the prestigious Len Curtis Award 2018, which was jointly presented by Taylor and Francis Inc. and the Remote Sensing and Photogrammetry Society (RSPSoc), United Kingdom, for an outstanding technical paper published in the International Journal of Remote Sensing, which was adjudged the best scientific paper published in the open literature of remote sensing during the year 2017. In 2018, He was a visiting scholar to the Faculty of Environment and Technology, the University of the West of England, Bristol, United Kingdom. He has received numerous national and international awards, including the dual 2021 Federal University of Technology, Minna Vice Chancellor’s awards for invaluable and exceptional contributions to the development of the University. He also received the Professor Hilary Inyang National Young Scientist’s Prize in Geoenvironmental Sciences, 2022, presented by the National Young Academy of the Nigerian Academy of Science. He was also the Faculty (Faculty of Engineering and the Built Environment) and Institutional (NUST)’s Established Researcher of the year, 2024.

Professional Affiliation 

• International Federation of Surveyors (FIG)
• Registered Surveyor, Surveyors Council of Nigeria (2944)
• Corporate Member, Nigerian Institution of Surveyor (NIS/FM/2531)
• Individual Member, International Society for Photogrammetry and Remote Sensing

Research Focus Areas

• Digital Photogrammetry and Remote Sensing Applications
• Geospatial Modelling
• Application of Artificial Intelligence in Geoenvironmental Sciences

Teaching

Undergraduate

• GIS Programming (GIP710S)
• Programming for Geoinformatics (PGI520S)
• Remote Sensing 1 (RES511S)
• Remote sensing 2 (RES612S)

Postgraduate

• Environmental Remote Sensing (ERS810S)
• Research Methodology (GRM921S)
• Spatial Analytical Methods (SAM911S)

Community Development Activities

• Mapping of informal settlements in Okhandja
• Member, Network of Excellence on Land Governance in Africa (NELGA, Southern Africa)

Selected Publications

1. Ajayi, O G., Ibrahim, P. O., Adegboyega, S. O. (2024). Effect of Hyperparameter tuning on the   Performance of Yolov8 for Multi-Crop Classification on UAV images. Applied Sciences. 14(13):5708. https://doi.org/10.3390/app14135708 

2. Ajayi, O.G., Iwendi, E, Adetunji, O. O. (2024). Optimizing Crop Classification in Precision Agriculture using AlexNet and UAV Hyperspectral Imagery. Technology in Agronomy. 4: e011. https://doi.org/10.48130/tia-0024-0009 

3. Adesina, E. A., Ajayi, O G., Odumosu, J. O (2024).  Soil loss risk assessment using revised universal soil loss equation (RUSLE) and geographical information system (GIS) approach. Advanced GIS. 4 (2), 42-53

4. Adesina, E. A., Ajayi, O G., Odumosu, J. O., Kolade, T. (2024). Mapping Soil Erosion Susceptibility: A Comprehensive Multi-Criteria Analysis Using Remote Sensing and GIS. Environmental, Technology and Science Journal (ETSJ). 15(1), 35-45. https://dx.doi.org/10.4314/etsj.v15i1.4 

5. Ajayi, O. G., & Nwadialor, I. J. (2024). Accuracy assessment of the effect of different feature descriptors on the automatic co-registration of overlapping images. Geodesy and Cartography, 50(1), 8–19. https://doi.org/10.3846/gac.2024.18199 

6. Adesina, E., Ajayi, O., Odumosu, J., & Illah, A. (2024). Assessing the risk of soil loss using geographical information system (GIS) and the revised universal soil loss equation (RUSLE). Advanced GIS, 4(2), 42–53. Retrieved from https://publish.mersin.edu.tr/index.php/agis/article/view/1350 

7. Ajayi, O. G. and Daud, M. O. (2024). Assessment of Generative Adversarial Networks for Cloud Occlusion Removal in Remotely Sensed Images. Arabian Journal of Geosciences. 17, 141 https://doi.org/10.1007/s12517-024-11939-y

8. Vallejo-Orti, M., Anders, K., Ajayi, O., E., Bubenzer, O., and Höfle, B. (2024). Integrating and optimizing multi-user digitizing actions for mapping gully footprints using a combined Kalman filter and machine learning approach. ISPRS Open Journal of Photogrammetry and Remote Sensing, 12, 100059. https://doi.org/10.1016/j.ophoto.2024.100059

9. Ajayi, O. G and Olufade O. O. (2023). Drone-based crop type identification with convolutional neural networks: an evaluation of the performance of RESNET architectures. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1/W1-2023, 991–998, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-991-2023 

10. Ajayi, O. G., Ogundele, B. S. and Aleji, G. A. (2023). Performance evaluation of different selected UAV image processing software on building volume estimation. Advances in Geodesy and Geoinformation 72(1), https://doi.org/10.24425/agg.2023.144591. 

11. Ajayi, O. G., Ashi, J. and Guda, B (2023). Performance evaluation of YOLO v5 for automatic weed and crop type classification on drone acquired images. Smart Agricultural Technology, 5, 

12.  https://doi.org/10.1016/j.atech.2023.100231

13. Ajayi, O. G., and Ashi, J. (2023). Effect of varying training epochs of faster region-based convolutional neural network on the accuracy of an automatic weed classification scheme. Smart Agricultural Technology, 3. https://doi.org/10.1016/j.atech.2022.100128 

14. Ajayi, O. G., Nwadialor, I. J., Odumosu, J. O., Adetunji, O. O., and Abdulwasiu, I. O. (2022). Assessment and delineation of groundwater potential zones using integrated geospatial techniques and analytic hierarchy process. Applied Water Science, 12(276). https://doi.org/10.1007/s13201-022-01802-4.

15. Ajayi, O. G., Opaluwa, Y. D., Ashi, J. and Zikirullahi, W.M. (2022). Applicability of artificial neural network for automatic crop type classification on UAV-based images. Environmental Technology and Science Journal. 13(1), 57-72. https://doi.org/10.4314/etsj.v13i1.5

Full and updated list of publications can be found in the links below:

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