Evaluation of forest degradation in Ago Owu Forest Reserve, Osun State, Nigeria: remote sensing and GIS approach
DOI: https://doi.org/10.3846/gac.2026.22764Abstract
Deforestation and forest degradation threaten biodiversity, climate regulation, and local livelihoods, particularly in tropical regions like Nigeria. This study evaluates the extent of deforestation and forest degradation in the Ago Owu Forest Reserve, Osun State, Nigeria, over 40 years (1984–2024) using remote sensing and Geographic Information System (GIS) techniques. This study aims to evaluate the trends of deforestation in Ago Owu Forest Reserve to mitigate the adverse effects of deforestation, to analyze Landsat satellite imagery from the years 1984, 2004, and 2024, using Land Use and Land Cover (LULC) classification and Normalized Difference Vegetation Index (NDVI). The results reveal a dramatic decline in forest cover, from 81.92% in 1984 to 11.26% in 2024. Simultaneously, built-up areas expanded from a negligible 0.056% in 1984 to 37.18% in 2024, highlighting significant human encroachment and urbanization into the forest reserve. The NDVI analysis reveals the degeneration of the forest NDVI from 0.7 to 0.2, indicating a reduction in forest density due to deforestation, urbanization, and logging activities. The findings provide critical insights into the need for effective and efficient deforestation policies to balance ecological preservation.
Keywords:
deforestation, forest degradation, NDVI, LULC, vegetation, urbanizationHow to Cite
Share
License
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Aderele, M. O., Bola, T. S., & Oke, D. O. (2020). Land use/land cover changes of Ago-Owu Forest Reserve, Osun State, Nigeria using remote sensing techniques. Open Journal of Forestry, 10(4), 401–411. https://doi.org/10.4236/ojf.2020.104025
Asifat, J. T., & Orimoogunje, O. O. I. (2020). Forest cover change and species distribution in Ago-Owu Forest Reserve, Osun State, South-Western, Nigeria. Tropical Plant Research, 7(2), 357–365. https://doi.org/10.22271/tpr.2020.v7.i2.041
Eneji, C. V. O., Ogundu, C. N., & Ojelade, I. A. (2019). Indigenous cultural practices and natural resources conservation in Owerri, Imo State, Nigeria. Advances in Social Sciences Research Journal, 6(9), 382–392. https://doi.org/10.14738/assrj.68.6381
Enuoh, O. O., & Ogogo, A. U. (2018). Assessing tropical deforestation and biodiversity loss in the Cross-River Rainforest of Nigeria. Open Journal of Forestry, 8(3), Article 86263. https://doi.org/10.4236/ojf.2018.83025
Fabiyi, O. (2011). Change ACTORS’ analysis and vegetation loss from remote sensing data in parts of the Niger Delta region. Journal of Ecology and the Natural Environment 3(12), 381–391.
Falana, A. R., Ademigbuji, A. T., Odeyale, O. C., Ibode, T. R., Ojo-Fakuade, F. F., Bamigboye, T. O., & Aigbokhan, O. J. (2022). Assessment of agroforestry practices in Ago-Owu Forest Reserve, Ayedaade local government area, Osun State, South-Western Nigeria. Journal of Applied Sciences and Environmental Management, 26(10), 1621–1627. https://doi.org/10.4314/jasem.v26i10.1
Gashaw, T., Bantider, A., & Mahari, A. (2014). Evaluations of land use/land cover changes and land degradation in Dera District, Ethiopia: GIS and remote sensing-based analysis. International Journal of Scientific Research in Environmental Sciences, 2(6), 199–208.
Goetz, S. J., Hansen, M., Houghton, R. A., Walker, W., Laporte, N., & Busch, J. (2015). Measurement and monitoring needs, capabilities and potential for addressing reduced emissions from deforestation and forest degradation under REDD+. Environmental Research Letters, 10, Article 123001. https://doi.org/10.1088/1748-9326/10/12/123001
Grecchi, R. C., Beuchle, R., Shimabukuro, Y. E., Aragão, L. E., Arai, E., Simonetti, D., & Achard, F. (2017). An integrated remote sensing and GIS approach for monitoring areas affected by selective logging: A case study in Northern Mato Grosso, Brazilian Amazon. International Journal of Applied Earth Observation and Geoinformation, 61, 70–80. https://doi.org/10.1016/j.jag.2017.05.001
Mensah, F., Adanu, S. K., & Adanu, D. K. (2015). Remote sensing and GIS based assessment of land degradation and implications for Ghana’s ecological zones. Environmental Practice, 17(1), 3–15. https://doi.org/10.1017/S1466046614000465
Miettinen, J., Stibig, H.-J., & Achard, F. (2014). Remote sensing of forest degradation in Southeast Asia – aiming for a regional view through 5–30 m satellite data. Global Ecology and Conservation, 2, 24–36. https://doi.org/10.1016/j.gecco.2014.07.007
Qamer, F. M., Shehzad, K., Abbas, S., Murthy, M. S. R., Xi, C., Gilani, H., & Bajracharya, B. (2016). Mapping deforestation and forest degradation patterns in Western Himalaya, Pakistan. Remote Sensing, 8(5), Article 385. https://doi.org/10.3390/rs8050385
Reddy, C. S., Manaswini, G., Satish, K. V., Singh, S., Jha, C. S., & Dadhwal, V. K. (2016a). Conservation priorities of forest ecosystems: Evaluation of deforestation and degradation hotspots using geospatial techniques. Ecological Engineering, 91, 333–342. https://doi.org/10.1016/j.ecoleng.2016.03.007
Reddy, C. S., Satish, K. V., Pasha, S. V., Jha, C. S., & Dadhwal, V. K. (2016b). Assessment and monitoring of deforestation and land-use changes (1976–2014) In Andaman and Nicobar Islands, India using remote sensing and GIS. Current Science, 111(9), 1492–1499. https://doi.org/10.18520/cs/v111/i9/1492-1499
Shimabukuro, Y. E., Arai, E., Duarte, V., Jorge, A., Santos, E. G. D., Gasparini, K. A. C., & Dutra, A. C. (2019). Monitoring deforestation and forest degradation using multi-temporal fraction images derived from Landsat sensor data in the Brazilian Amazon. International Journal of Remote Sensing, 40(14), 5475–5496. https://doi.org/10.1080/01431161.2019.1579943
View article in other formats
Published
Issue
Section
Copyright
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
License

This work is licensed under a Creative Commons Attribution 4.0 International License.