Underlying causes and drivers of land use/cover changes in benin: How can remote sensing and geographical information system help?

This study aims at improving the understanding of the processes of land use/cover change in a Central Region of Benin Republic. In this vein, an integrated approach that links satellite observations of land cover change at fine and temporal resolution to socio-economic analysis of land use change and to growing stock estimation was used. This approach was based on a multi scale methodology using Multispectral (XS) Spot and Landsat Thematic Mapper (TM) for the multi-scale study of land use/cover change. A forest survey was carried out to estimate the plant diversity and the growing stock. To provide reliable information on the plant communities indices such as specific richness, Shannon index, Pielou equitability index and coefficient of variation were determined. Using a four stage sampling procedure, a total of 202 respondents were selected and interviewed. To predict land use change the Markov model approach was used. In all, a statistical model was developed for forest transition probabilities. In summary, this study has highlighted how a combination of GIS techniques and socio economic data in addition to growing stock volume data can be integrated together to document causes and processes of land use/cover change and to improve the understanding of the social consequences and social dynamics related to these land use/cover changes.