Koubodana, H.D.; Diekkrüger, B.; Näschen, K.; Adounkpe, J.; Atchonouglo, K. 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. International Journal of Advanced Remote Sensing and GIS2019, 8, 3073–3095, doi:10.23953/cloud.ijarsg.422
Koubodana, H.D.; Diekkrüger, B.; Näschen, K.; Adounkpe, J.; Atchonouglo, K. 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. International Journal of Advanced Remote Sensing and GIS 2019, 8, 3073–3095, doi:10.23953/cloud.ijarsg.422
Koubodana, H.D.; Diekkrüger, B.; Näschen, K.; Adounkpe, J.; Atchonouglo, K. 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. International Journal of Advanced Remote Sensing and GIS2019, 8, 3073–3095, doi:10.23953/cloud.ijarsg.422
Koubodana, H.D.; Diekkrüger, B.; Näschen, K.; Adounkpe, J.; Atchonouglo, K. 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. International Journal of Advanced Remote Sensing and GIS 2019, 8, 3073–3095, doi:10.23953/cloud.ijarsg.422
Abstract
The results reveal CILSS as the most accurate data set with a Kappa coefficient of 68% and an overall accuracy of 83%. CILSS data shows a decrease of savanna and forest whereas an increase of cropland over the period 1975 to 2013. The increase of cropland area of 30.97% from 1975 to 2013 can be related to the increase in population and their food demand, while the losses of forest area and the decrease of savanna are further amplified by using wood as energy sources and the lack of forest management. The three datasets were used to simulate future LULC changes using the Terrset Land Change Modeler. The validation of the model using CILSS data for 2013 showed a quality of 50.94%, it is only 40.04% for ESA and 20.13% for Globeland30. CILSS data was utilized to simulate the LULC distribution for the years 2020 and 2027 because of its satisfactory performances. The results show that a high spatial resolution is not a guarantee of high quality. The results of this study can be used for impact studies and to develop management strategies for mitigating negative effects of land use and land cover change.
Keywords
land cover maps; land cover scenario; Land Change Modeler (LCM); transition probabilities
Subject
Environmental and Earth Sciences, Soil Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
