Land Use/Land Cover Dynamics and Future Changes Using a CA-Markov Model in the Mount Nlonako Forest and Peripheries (Littoral, Cameroon)  

作　　者：Franck Mathaus Douandji Douandji Borel Yanick Kamga Louis Njie Ndumbe Armand Delanot Tanougong Nkondjoua Michael Lyonga Ngoh Victor François Nguetsop Franck Mathaus Douandji Douandji;Borel Yanick Kamga;Louis Njie Ndumbe;Armand Delanot Tanougong Nkondjoua;Michael Lyonga Ngoh;Victor François Nguetsop(Department of Plant Biology, University of Dschang, Dschang, Cameroon;Department of Forestry and Wildlife, Faculty of Agriculture and Veterinary Medicine, University of Buea, Buea, Cameroon;FOKABS Cameroon, City of Seven Hills, Tsinga, Yaounde, Cameroon;Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, USA)

机构地区：[1]Department of Plant Biology, University of Dschang, Dschang, Cameroon [2]Department of Forestry and Wildlife, Faculty of Agriculture and Veterinary Medicine, University of Buea, Buea, Cameroon [3]FOKABS Cameroon, City of Seven Hills, Tsinga, Yaounde, Cameroon [4]Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, USA

出　　处：《Journal of Geoscience and Environment Protection》2025年第2期230-260,共31页地球科学和环境保护期刊(英文)

摘　　要：Forests are facing several challenges related to forest deforestation mostly due to the actions of man. The study used a CA-Markov model to examine land use/land cover dynamics from 1986 to 2022, as well as estimate future changes from 2022 to 2052 in the Mount Nlonako forest and peripheries. Three types of Landsat images (Landsat 4 - 5 Thematic Mapper (TM) images of 1986 and 2004, and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI-TIRS) image of 2022) were used for diachronic analysis. The results revealed six major land use/land cover classes namely: Dense forest, Clear forest, Farmland, Savannah, Built-up Area and Bare floor. Accuracy rates for land use/land cover classification ranged from 89.85% to 93.11%. The prediction model was accepted with an overall satisfaction rate of 84.08%. The Dense Forest class has been steadily decreasing from 138320.94 ha (75.42%) in 1986 to 84161.34 ha (45.89%) in 2022, corresponding to a total loss of 54159.6 ha (29.53%) over the 36-year period and is projected to reach 39028.34 ha (21.28%) in 2052 corresponding to a future loss of 45133 ha (24.61%) over a period of 30 years. Anthropogenic factors (mainly agriculture and industrial logging) and natural factors (excess rainfall) were responsible for the degradation of the area. Regardless of the limitations of the CA-Markov model due to the non integration of socio-economic factors, this study is a crucial alert to decison and policy makers to undergo protection procedures for this area to be protected, thereby involving the local communities in the management and restoration of the area through participatory management.Forests are facing several challenges related to forest deforestation mostly due to the actions of man. The study used a CA-Markov model to examine land use/land cover dynamics from 1986 to 2022, as well as estimate future changes from 2022 to 2052 in the Mount Nlonako forest and peripheries. Three types of Landsat images (Landsat 4 - 5 Thematic Mapper (TM) images of 1986 and 2004, and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI-TIRS) image of 2022) were used for diachronic analysis. The results revealed six major land use/land cover classes namely: Dense forest, Clear forest, Farmland, Savannah, Built-up Area and Bare floor. Accuracy rates for land use/land cover classification ranged from 89.85% to 93.11%. The prediction model was accepted with an overall satisfaction rate of 84.08%. The Dense Forest class has been steadily decreasing from 138320.94 ha (75.42%) in 1986 to 84161.34 ha (45.89%) in 2022, corresponding to a total loss of 54159.6 ha (29.53%) over the 36-year period and is projected to reach 39028.34 ha (21.28%) in 2052 corresponding to a future loss of 45133 ha (24.61%) over a period of 30 years. Anthropogenic factors (mainly agriculture and industrial logging) and natural factors (excess rainfall) were responsible for the degradation of the area. Regardless of the limitations of the CA-Markov model due to the non integration of socio-economic factors, this study is a crucial alert to decison and policy makers to undergo protection procedures for this area to be protected, thereby involving the local communities in the management and restoration of the area through participatory management.

关 键 词：Mount Nlonako Forest Spatio-Temporal Change Future Changes CA-Markov Model Degradation Deforestation 

分 类 号：S71[农业科学—林学]