Abstract

This study combined logistic regression, Markov chain and the Dyna-CLUE models to simulate land use patterns in the Bonsa catchment of Ghana, West Africa. Historical model validation produced Relative Operating Characteristics (ROC) statistics above 0.69; indicating a significant relationship between the driving factors and the land cover types, and overall accuracy of 71% as well as a Kappa statistic of 55%, indicating a moderate agreement between observed and simulated land uses. The statistics of the historical model were used to simulate three plausible future land use scenarios. The historical simulation revealed that increases in population density, proximity to roads and expansion of mines were the major drivers that significantly increased the probability of settlement expansion and deforestation. Simulations of future land use showed that settlement expansion and deforestation may increase by similar margins for all scenarios, but the increase in secondary forests may be higher for the economic growth and reforestation (EGR) scenario, compared to the economic growth (EG) and the business-as-usual (BAU) scenarios. The mining areas may double in the future for all the scenarios, but shrubs/farms may increase in the BAU scenario, but reduce marginally in the EG and the EGR scenarios. The results of this study can be used to support land use planning and evaluation of the impacts of different future development pathways.Keywords: Bonsa catchment, deforestation, driving factors, Dyna-CLUE, land use, logistic regression, West Africa

Highlights

  • Land cover/land use patterns over a period of time are determined by demographic, economic and environmental driving factors (Verburg et al, 1999; Castella et al, 2007) both at a national and global scale

  • This study aims to extend the knowledge on spatial patterns of land use changes in relation to their driving forces in West Africa, by conducting an empirical spatially distributed land use modelling, using the Bonsa catchment in southern Ghana as a study site and it builds on a previous land use change analysis study by Aduah et al (2015)

  • This study has demonstrated a moderately successful modelling of land cover/use changes for both historical and future scenarios, using a combination of logistic regression, Markov chain and the Dyna-CLUE models

Read more

Summary

Introduction

Land cover/land use patterns over a period of time are determined by demographic, economic and environmental driving factors (Verburg et al, 1999; Castella et al, 2007) both at a national and global scale. Several land use mapping (Braimoh and Vlek, 2004; Attua and Fisher, 2010; FAO, 2010; Laurin et al, 2013; Aduah et al, 2015) and a few land use modelling studies (Mertens and Lambin, 2000; Braimoh and Vlek, 2005; Houessou et al, 2013) have been conducted in West Africa; in Ghana there is still a considerable knowledge gap on land use change processes, patterns and their driving forces at the local scale. Studies in rainforest regions of Ghana have mainly quantified the land use changes (Attua and Fisher, 2010; Schueler et al, 2011; Aduah et al, 2015), none attempted to gain a quantitative and deeper understanding of the processes of changes in relation to their driving forces. Several case studies worldwide (Verburg and Veldkamp, 2004; Verburg and Overmars, 2009), show that there is a potential for a deeper understanding of the land use change processes in relation to their driving forces at the local scale, through spatially distributed land use modelling

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.