Factors associated with deforestation probability in Central Vietnam: a case study in Nam Dong and A Luoi districts
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February 22, 2023
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info:eu-repo/semantics/altIdentifier/doi/10.1080/13416979.2023.2182259
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Disforestation Depletion of forests Conversion, Forest Forest conversion Forest depletion Forest-land conversionCite this document
Canh Tran Quoc et al., « Factors associated with deforestation probability in Central Vietnam: a case study in Nam Dong and A Luoi districts », Serveur académique Lausannois, ID : 10.1080/13416979.2023.2182259
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Abstract
Vietnam is undergoing a forest transition stage with an overall increase in forest cover since the 1990s; however, deforestation and forest degradation of natural forests still occur in several areas, especially in the Central region of the country. In order to better manage and protect natural forests, predicting deforestation probability and understanding its associated factors are necessary. In the present study, we focused on the two mountainous districts (Nam Dong and A Luoi) in Central Vietnam as a case study. We used Landsat satellite images for identifying changes of natural forests over the period of 1989–2020. The logistic regression model showed a good performance in prediction of deforestation (testing AUC = 0.874) in the study area. Our data showed that deforestation probability of natural forests in the study area in the period of 1989–2020 could be influenced by 11 socio-economic and topographical factors. In particular, forest areas with low elevation, gentle slopes, nearby rivers and residential areas have a high deforestation probability. Production forest, forest areas not included in payment for environmental service (PFES) schemes, forest with no ownership and forest areas managed by private owners may also have a high deforestation probability. The total area of very high level of deforestation probability in A Luoi (8,988 ha) and Nam Dong (5,304 ha) districts occupied about 11.4% of natural forests in the study area. Our study suggests that protection activities should be focused on high deforestation probability-prone forest areas.
