Segmenting at higher scales to classify at lower scales. A mathematical morphology based methodology applied to forest cover remote sensing images

A methodology based on mathematical morphology to classify forest cover types in remote sensing images is presented. The information automatically extracted at higher scales (aerial photographs) by morphological segmentation approaches is afterwards used to classify different forest cover types at lower scales (satellite images). In this methodology the spectral process is guided by the spatial process, once the previous segmentation of the different textural elements is then used in the classification procedure, where the geometrical modelling of the shape of the training sets of points is also performed. Tests were done in a region of centre Portugal using aerial photographs and Landsat TM images for olive, cork oak, pine and eucalyptus trees.