Use of logistic regression and GIS techniques in the analysis of forest cover dynamics in Mabote and Funhalouro, Inhambane, southern Mozambique - Macandza, Manuel Madeira (Sociedade & Natureza, 2022)
This article seeks to use logistic regression and GIS techniques as a way to understand the influence of forest policy on the dynamics of forest cover in the study area. For this, we chose the following variables: Dynamics of forest cover as the dependent variable; precipitation, temperature, simple license, forest concession, volume of charcoal exploited, agricultural areas, villages, and population dynamics as independent variables. From the correlation, the variables that showed significance in the model are simple license, temperature, and volume of charcoal exploited. But the logistic regression model showed that the simple license and temperature variants are significantliy important for the model. This does not rule out the existence of other variables that may explain the phenomenon. Thus, the constructed logistic regression model points out that the simple license predictor is statistically more significant in explaining the variation in forest cover compared with temperature. Simple licensing is one of the modalities that forestry policy in Mozambique has adopted for forest licensing. And many of the operators prefer this type of forest license. Temperature inversely influences the dynamics of forest cover, causing water stress in plants. While the variable volume of coal explored, its influence is significantly smaller.