EpulePengLepageEtAl2011
Référence
Epule, T.E., Peng, C., Lepage, L., Chen, Z. (2011) Forest Loss Triggers in Cameroon: A Quantitative Assessment Using Multiple Linear Regression Approach. Journal of Geography and Geology, 3(1):30-41.
Résumé
The triggers of forest area loss in Cameroon have not been properly understood. The measures used to curb forest area loss have been simplistic, generalized with no clear cut knowledge of the specific role of different potential factors. This study aims at investigating the hypothesis that population growth is the main cause of loss in forest area. This study will be able to identify what factors are of more significance in the causal equation. The open R programming software has been used to produce multiple linear regression models. The correlation between the dependent variable and the independent variables was established by a correlation matrix and the strength of the models tested by power analysis. The results supports the hypothesis that population growth is the most dominant cause of deforestation in Cameroon while arable production and permanent crop land and arable production per capita index are second and third respectively.
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@ARTICLE { EpulePengLepageEtAl2011,
AUTHOR = { Epule, T.E. and Peng, C. and Lepage, L. and Chen, Z. },
TITLE = { Forest Loss Triggers in Cameroon: A Quantitative Assessment Using Multiple Linear Regression Approach },
JOURNAL = { Journal of Geography and Geology },
YEAR = { 2011 },
VOLUME = { 3 },
PAGES = { 30-41 },
NUMBER = { 1 },
ABSTRACT = { The triggers of forest area loss in Cameroon have not been properly understood. The measures used to curb forest area loss have been simplistic, generalized with no clear cut knowledge of the specific role of different potential factors. This study aims at investigating the hypothesis that population growth is the main cause of loss in forest area. This study will be able to identify what factors are of more significance in the causal equation. The open R programming software has been used to produce multiple linear regression models. The correlation between the dependent variable and the independent variables was established by a correlation matrix and the strength of the models tested by power analysis. The results supports the hypothesis that population growth is the most dominant cause of deforestation in Cameroon while arable production and permanent crop land and arable production per capita index are second and third respectively. },
OWNER = { amriv2 },
TIMESTAMP = { 2012.08.02 },
}
