TY - JOUR
T1 - Analysing patterns of forest cover change and related land uses in the Tano-Offin forest reserve in Ghana
T2 - Implications for forest policy and land management
AU - Oduro Appiah, Joseph
AU - Agyemang-Duah, Williams
AU - Sobeng, Augustus Kweku
AU - Kpienbaareh, Daniel
N1 - Funding Information:
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors wish to declare that they have no conflict of interest. This study did not involve any human subjects.
Publisher Copyright:
© 2021 The Authors
PY - 2021/9/1
Y1 - 2021/9/1
N2 - Forest cover change is a major contributing factor to global environmental change. Whereas several studies have focused on the general land use and land cover dynamics, we focus on analysing forest cover change patterns in a protected landscape taking into consideration how other land categories are increasing at the expense of the forest. In this study, we analyse forest cover change patterns and associated proximate land use factors between 1987 and 2017 using Landsat images from the Tano-Offin Forest Reserve (TOFR) in Ghana. Using the Random Forest machine learning algorithm, we classified the images into forest, developed land, and agricultural land. The study finds that forest cover losses are 1.9 and 1.4 times the amount of forest cover gains in 1987–2002 and 2002–2017, respectively. We find that even though the forest cover is more likely to recover from the agricultural land, land developers mostly targeted the agricultural land. The focus of Ghana's Forest and Wildlife Policy and the underlying process of forest cover change in the TOFR suggest that a country's forest policy should focus on a combination of diverse and spatially explicit proximate factors that are likely to threaten the integrity of forests.
AB - Forest cover change is a major contributing factor to global environmental change. Whereas several studies have focused on the general land use and land cover dynamics, we focus on analysing forest cover change patterns in a protected landscape taking into consideration how other land categories are increasing at the expense of the forest. In this study, we analyse forest cover change patterns and associated proximate land use factors between 1987 and 2017 using Landsat images from the Tano-Offin Forest Reserve (TOFR) in Ghana. Using the Random Forest machine learning algorithm, we classified the images into forest, developed land, and agricultural land. The study finds that forest cover losses are 1.9 and 1.4 times the amount of forest cover gains in 1987–2002 and 2002–2017, respectively. We find that even though the forest cover is more likely to recover from the agricultural land, land developers mostly targeted the agricultural land. The focus of Ghana's Forest and Wildlife Policy and the underlying process of forest cover change in the TOFR suggest that a country's forest policy should focus on a combination of diverse and spatially explicit proximate factors that are likely to threaten the integrity of forests.
KW - Forest cover losses
KW - Globally significant biodiversity area
KW - Intensity analysis
KW - Land transitions
KW - Remote sensing
KW - Rural livelihood
UR - http://www.scopus.com/inward/record.url?scp=85108276251&partnerID=8YFLogxK
U2 - 10.1016/j.tfp.2021.100105
DO - 10.1016/j.tfp.2021.100105
M3 - Article
SN - 2666-7193
VL - 5
JO - Trees, Forests and People
JF - Trees, Forests and People
M1 - 100105
ER -