Granulometric Analysis on Remote Sensing Images: Application to Mapping Retrospective Changes in the Sahelian Ligneous Cover

This paper illustrates how the use of mathematical morphology can be a powerful tool for the mapping of ligneous cover in semi-arid lands. Ligneous cover plays a fundamental role in Sahel semi-arid regions since this resource is vital to the resilience of rural societies and can be used as an indicator of socio-environmental conditions. Grey tone vertical images from Sahelian villages in 1975 and 2010/2011 have been selected to perform a diachronic analysis to test the method. Granulometric profiles have been calculated for each pixel and then an unsupervised classification has been performed to obtain k classes that account for ligneous patches of different sizes. This method is particularly successful when the most recent images are used, given that these have better contrast and sharpness. Nested classifications were required to accomplish the ligneous mapping of images from 1975. The accuracy assessment for the most recent images classifications shows satisfactory results. The classification of ligneous cover according to different sizes is important for a better understanding of the ligneous dynamics.