Forest cover change in Onigambari reserve, Ibadan, Nigeria: Application of vegetation index and Markov chain techniques
Khadijat Oyebisi Alabi, Tobore Anthony, O.A. Ganiyu, Senjobi Bolarinwa
Abstract
Forest cover change (FCC) varies globally and is thus considered as one of the drivers of climate change. The present study identified the pattern of the FCC for the years 2010 and 2020 using vegetation index and Markov chain techniques. The Markov chain (MC) was utilized to predict the forest cover map for the year 2030. The vegetation index of Landsat 7 Enhanced thematic mapper plus (ETM+) and Landsat 8 Operational land images (OLI) were employed to assess the forest cover loss for the years 2010 and 2020. The validation result shows that the accuracy of the predicted forest cover map is more than 75 percent (%). The prediction result shows that if the current human activities continue such as deforestation, the forest cover will continue to be endangered and thus leading to a decrease in dense forest, plantation, and sparse vegetation by 20.9%, 16.1%, and 20% respectively. Hence, there is an urgent need to integrate bottom-up and participatory approaches between agriculture activities and forestry for socioeconomic development. This study will ensure sustainable forest management by assisting society, government and stakeholders.