Resource information
Land use/cover change (LUCC) is a major indicator of the impact of climate change and human activity, particularly in the Sahel, where the land cover has changed greatly over the past 50 years. Aerial and satellite sensors have been taking images of the Earth's surface for several decades. These data have been widely used to monitor LUCC, but many questions remain concerning what type of pre-processing should be carried out on image resolutions and which methods are most appropriate for successfully mapping patterns and dynamics in both croplands and natural vegetation. This study considers these methodological questions. It uses multi-source imagery from 1952 to 2003 (aerial photographs, Corona, Landsat Multispectral Scanner (MSS), Landsat Thematic Mapper (TM) and Satellite Pour l'Observation de la Terre (SPOT) 5 images) and pursues two objectives: (i) to implement and compare a number of processing chains on the basis of multi-sensor data, in order (ii) to accurately track and quantify LUCC in a 100 km² Sahelian catchment over 50 years. The heterogeneity of the spatial and spectral resolution of the images led us to compare post-classification methods aimed at producing coherent diachronic maps based on a common land-cover nomenclature. Three main approaches were tested: pixel-based classification, vector grid-based on-screen interpretation and object-oriented classification. Within the automated approaches, we also examined the influence of spectral synthesis and spatial homogenization of the data through the use of composite bands (principal component analysis (PCA) and indices) and by resampling images at a common resolution. Classification accuracy was estimated by computing confusion matrices, by analysing overall change in the relative areas of land use/cover types and by studying the geographical coherence of the changes. These analyses indicate that on-screen interpretation is the most suitable approach for providing coherent, valid results from the multi-source images available over the study period. However, satisfactory classifications are obtained with the pixel-based and object-oriented approaches. The results also show significant sensitivity, depending on the method considered, to the combinations of bands used and to resampling. Lastly, the 50-year trends in LUCC point out a large increase in croplands and erosional surfaces with sparse vegetation and a drastic reduction in woody covers.
