**6. Conclusions**

The LULC changes that are attributable to anthropogenic disturbance are leading to reductions in forest cover, contributing significantly to global carbon emissions. In this study, we employed the median satellite image composition method with historical Landsat sensor data in the GEE to quantify changes across the nation of Togo between 1985 and 2020 using the Random Forest algorithm. Our results indicate that all land-cover classes identified from the 1985 composite image were affected to varying degrees by these land-cover changes. Furthermore, forests lost about 52.28% of their original area from 1985 to 2020 through the expansion of crop and fallow lands, savannah, and urbanization. Ecological zones I, III, and V cover more than two-thirds of the total area of the country and contain less than half of the forest cover. The changes are mainly reflected by a strong increase in agricultural activity, deforestation through timber exploitation, and the urban expansion of a burgeoning human population. Easier accessibility of the areas and a greater human presence favor all of these activities. In contrast, ecological zones II and IV, which cover less than one-third of the total area of the country, contain more than 55% of the national forest cover in 2020. These are very mountainous areas, the steep slopes of which limit the adverse effects of human activities and, consequently, their effects on natural resources.

The methods that were applied in this study and the results that were obtained could help forestry and territorial administrators to better understand the factors that are involved in land-cover change and forest area reduction. They could also help the national coordination of REDD+ in Togo to better operate or to boost the measurement, reporting, and verification system, as part of the nation's forest monitoring system. For similar future

studies in Togo, more reliable satellite data (Landsat 8 and 9) with lower cloud cover or higher spatial resolution (Sentinel 2 and greater) could be used when sufficient time-series images become available on the GEE platform over the study area, as well as other countries in Sub-Saharan Africa.

**Author Contributions:** Conceptualization: A.K. and K.G.; Methodology: A.K., K.G. and F.F.; Data collection: A.K., F.F., W.A., M.D. and K.W.; Data analysis: A.K. and K.G., Preparation of the manuscript draft: A.K.; Supervision: K.G.; Writing and editing: all authors. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research has been funded by the *Programme Canadien de bourses de la Francophonie* (Government of Canada, Department of Foreign Affairs, Trade and Development, Canadian Partnership Branch), as well as the *Natural Sciences and Engineering Research Council of Canada* (NSERC Discovery gran<sup>t</sup> RGPIN-2018-06101 and NSERC CREATE Grant 543360-2020).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Data are available upon request and can be obtained by contacting the lead author.

**Acknowledgments:** We thank all of the reviewers for their guidance and contributions to writing and commenting on this manuscript. W.F.J. Parsons translated the French text.

**Conflicts of Interest:** The authors declare no conflict of interest. The organization providing the funding has played no role in the design of the study, collection, analysis, interpretation of the data, writing of the manuscript, or in the decision to publish the results.
