Contribution of Remote Sensing and GIS for Sustainable Forest Management in Côte d’Ivoire; Case of the classified Forest of TENE in the department of OUME (Côte d’Ivoire).

Abstract:

The classified forest of TENE located in the department of OUME has a role of timber production characterized by a high logging. This operation requires a measure of preservation of sensitive sites to exploitation in order to maintain ecological functions, ecosystem and biodiversity living there. The parameters such as streams, slopes, wetlands and rivers are indicators of the existence of sensitive sites to preserve. However, no knowledge of the location, boundaries and the surface of these natural habitats makes its protection difficult. Thus, knowledge of the natural and conceptual environment at the forest of TENE is necessary for the preservation of the ecosystem and biodiversity, prerequisite for its sustainability. Furthermore, Remote Sensing and GIS are less expensive techniques for synthetic and fast analysis of these parameters at different scales as well as spatially and temporally. It should be noted that this study is focused on wetlands mapping in the forest of TENE for a sustainable management. The satellite image of December 2014 from Landsat 8 carried on the Operational Land Imager (OLI) sensor was used for analysis. The methodological approach is based primarily on prior knowledge of the spectral signatures of different elements on the image in different wavelengths. Then the thematic layers extraction of hydromorphic soil without and with vegetation are made by thresholding associated luminance values. The combination of the obtained layers allowed to map all wetlands in the forest of TENE. Finally, the superimposition of this layer with the water system was used to assess the conformity of the result with the reality on the ground. The result showed that the wetlands subject of sensitive sites are mainly found in the western part of the forest of TENE. They are also encountered along the rivers. These wetlands extend over a total area of 12,915 ha against 16,898.22 ha for the non wetlands with a coverage rate of 43.32 %. These areas should be protected against logging in order to do not disturb them because they are refuge environments for fauna as well as flora conservation. This study will enable the manager of the classified forest of TENE to target those sites considered sensitive to preserve for a sustainable management. Keywords: Spectral signature, Forest, Wetland, Remote Sensing, GIS, Côte d’Ivoire.