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Drivers of afforestation in Northern Vietnam: Assessing local variations using geographically weighted regression

Drivers of afforestation in Northern Vietnam: Assessing local variations using geographically weighted regression

Clement, Floriane, Orange, Didier, Williams, Meredith, Mulley, Corinne and Epprecht, Michael (2009) Drivers of afforestation in Northern Vietnam: Assessing local variations using geographically weighted regression. Applied Geography, 29 (4). pp. 561-576. ISSN 0143-6228 (doi:10.1016/j.apgeog.2009.01.003)

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Abstract

This article identifies drivers of forest transition in a province of Northern Vietnam between 1993 and 2000 by applying geographically weighted regression (GWR) analysis to remotely sensed and statistical data. The regression model highlighted the spatial variation of the relationship between the percentage of land afforested and its proximate causes. Factors identified as having a major impact on afforestation are: the presence or proximity of a wood-processing industry, the distance to highways, and land allocation to households. Whereas the two former variables are in most areas of the province positively correlated with afforestation, an unexpected negative correlation was observed for the latter. The analysis of these results, supported by an in-depth knowledge of the area and of the political context, leads to the conclusion that, during the time period considered, afforestation was largely driven by state organisations on protected state-owned land, and forestry was not a significant component of household economic activities.

Item Type: Article
Uncontrolled Keywords: afforestation, forest-cover change, geographically weighted regression, GWR, forest policy, land allocation, Vietnam
Subjects: G Geography. Anthropology. Recreation > G Geography (General)
G Geography. Anthropology. Recreation > GE Environmental Sciences
Faculty / Department / Research Group: Faculty of Engineering & Science > Department of Pharmaceutical, Chemical & Environmental Sciences
Related URLs:
Last Modified: 08 Dec 2016 14:58
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/4402

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