Please login first
Spatio-Temporal Land Cover Change Assessment of Multi-Forests in the High Forest Zone of Ghana
* 1 , 1 , 2 , 1
1  Department of Forest Resources Technology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
2  Department of Geomatic Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
Academic Editor: Fabio Tosti

Abstract:

Tropical forests are essential for maintaining carbon balances and preserving biodiversity, yet they continually experience human threats like illegal mining, agricultural expansion, and logging. This study explores the land use and land cover changes over two decades (2004–2024) in four forest reserves in Ghana: Atewa, Bosomtwe Range, Fure River, and Tano Suraw. Land covers (closed and open forests, water bodies, and bare land) and past changes were mapped using Landsat satellite imagery, Random Forest Classification, and Land Change modelling. CA Markov Chain modelling was adopted to predict the potential land cover of the forest reserves in 2034. The overall classification accuracies ranged between 91% and 97%. The Atewa forest had the most decline in closed-canopy forest (CCF) with 51.3 km² transitioning to open-canopy forest (OCF) between 2004 and 2024. Projections suggest further declines, with CCF expected to decline from 106.04 km² to 85.7 km² by 2034. Similarly, the Bosomtwe Range forest had bare land increasing steadily from 2.3 km² to 3.1 km² in 2034. The Fure River forest experienced severe degradation, losing 3.9 km² of CCF to bare land from 2015 to 2024, with bare land anticipated to expand from 7.79 km² to 14.4 km² by 2034. In the Tano Suraw forest, 3.9 km² of CCF transitioned to OCF, while bare land is projected to increase from 11.06 km² to 15.7 km² by 2034, reflecting intensifying deforestation. Overall, the emerging dominant land cover is OCF, signaling extensive habitat destruction. The forest degradation is largely driven by illegal mining and agricultural expansion, threatening biodiversity and ecosystem functionality. Predictions for 2034 indicate that, without intervention, these forests will continue to experience severe degradation, escalating carbon emissions, and biodiversity loss. Mapping the changes and future trends of the forests provides vital insights to inform policies to guide sustainable land management and conservation.

Keywords: Tropical forest; Random Forest; Mapping; Landsat; Land Cover Change; Degradation
Comments on this paper
Currently there are no comments available.



 
 
Top