The main objective of research was to use 3S technology coupled to traditional method of vegetation sampling to assess the vegetation dynamic in Northern Togo. The remote sensed data of three different years (1987, 2000 and 2007) were used to evaluate the land use change by employing the normalized difference vegetation index (NDVI) algorithm, Iso-Data unsupervised classification and change detection method set by Winne. The vegetation sampling followed the Braun-Blanquet concept and was carried in riparian forest. The analysis and interpretation of the map of land cover change dynamic show that the rate of forest harvest is higher than it regrowth. The vegetation which has not been subjected to physical structure modification is localized along the river and is displayed in white color on the map, but around this type of vegetation, it is evolved in the regrowth stage displayed in cyan. From the 62 forest samples, 61 plants species were listed. A large number of these species belong to Combretaceae, Rubiaceae, Mimosaceae and Caesalpiniaceae families. The cluster analysis of the samples allows the identification three riparian forest grouping. Their distributions follow a latitudinal position; the grouping of Pterocarpus santaloïdes and Cola laurifolia (Rp1) is found in low latitude while P.santaloïdes and Eugenia kerstingii (Rp2) is presented in high latitude. The third group is mainly constituted of adjacent dry forest species which grow in flooded plain around the rivers and streams. These basic information in spite of their insufficiency, could be useful management purposes of land resources.
Key words: Land use change, land resources, Riparian forest, normalized difference vegetation index (NDVI), biodiversity.
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