Implications of some major human-induced activities on forest cover using extended change matrix quantity and intensity analysis based on historical Landsat data from the Kloto District, Togo

Abstract

This study analyses forest reference level in terms of loss, gain and transitions among forest, cocoa agroforestry, cassava, maize, settlement and others in the Kloto district (Togo) for REDD+ and sustainable forest and agriculture. The pixel-based classification was adopted and combined with the extended change matrix quantity and intensity analysis using 32-year (1985–2017) Landsat data and land use information from land owners and farmers. Results indicate an active forest loss (19.5%) with dormant gain (0.8%). Forest is involved in most transitions as the most targeted category with the largest transition being a forest to cocoa agroforestry while the avoiding transition was from forest, cocoa agroforestry, maize, cassava and settlement to unclassified classes (e.g. road, water body) and vice versa. Other targeting categories were from forest to settlement, cassava and maize Thus, both cash and food crops are major contributors of forest loss. The study concludes that cropland land degradation is the main reason that explains the significant conversion of forest lands to stable agricultural lands. Therefore, review of the existing cropping and farming systems by promoting agroecology systems (e.g. agroforestry, rotational cropping, mixing cropping with pulses) to sustain and restore soil degradation while mitigating climate change, forest degradation and provide food security for the rural communities is recommended. Economic measures such as: trade-off compensations for agroecology practices and afforestation and reforestation through farmer’s association initiatives could be encouraged to limit forest extensions.