Impact of the Accuracy of Land Cover Data Sets on the Accuracy of Land Cover Change Scenarios in the Mono River Basin, Togo, West Africa

Abstract

Knowledge about land use and land cover (LULC) dynamics is of high importance for a 15 number of environmental studies including the development of water resources, land degradation and 16 food security. Often, available global or regional data sets are used for impact studies, although they 17 have not been validated for the area of interest. Validation is especially required if data are used to 18 set up a land change model predicting future changes for management purposes. 19 Therefore, three different LULC maps of the Mono River Basin in Togo were evaluated in this study. 20 The analyzed maps were obtained from three sources: CILSS (2 km resolution), ESA (300 m), and 21 Globeland (30m) datasets. Validation was performed using 1,000 reference points in the watershed 22 derived from satellite images. 23 The results reveal CILSS as the most accurate data set with a Kappa coefficient of 68% and an 24 overall accuracy of 83%. CILSS data shows a decrease of savanna and forest whereas an increase 25 of cropland over the period 1975 to 2013. The increase of cropland area of 30.97% from 1975 to 2013 26 can be related to the increase in population and their food demand, while the losses of forest area 27 and the decrease of savanna are further amplified by using wood as energy sources and the lack of 28 forest management. The three datasets were used to simulate future LULC changes using the Terrset 29 Land Change Modeler. The validation of the model using CILSS data for 2013 showed a quality of 30 50.94%, it is only 40.04% for ESA and 20.13% for Globeland30. CILSS data was utilized to simulate 31 the LULC distribution for the years 2020 and 2027 because of its satisfactory performances. The 32 results show that a high spatial resolution is not a guarantee of high quality. The results of this study 33 can be used for impact studies and to develop management strategies for mitigating negative effects 34 of land use and land cover change.