CONTRIBUTION OF HYBRID CLASSIFICATION ON IKONOS SATELLITE IMAGERY IN MAPPING OF WETLAND'S HABITATS: Merja Zerga (Morocco)

Spatial accuracy is important information in the mapping of wetland habitats, hence the recourse to the use of data with very high spatial resolution such as the IKONOS satellite images. However, the mediocrity of these spectral images; the presence of mixed pixels or spectral confusion between different objects in the image, make the process of discrimination of wetlands habitats difficult. This difficulty is amplified because these areas are home to diversified habitats, and in most times have spectral similarities between them. Taking into consideration the problems mentioned above, this work proposes a hybrid classification approach to better discriminate the habitats from an IKONOS data covering the Wetland of Merja Zerga (Moroccan Wetland of International Importance). This approach combines a supervised classification (per pixel) and an object-oriented classification (unsupervised) using DBSCAN algorithm. This classification approach allows discriminating all wetland habitats of the Merja Zerga and produces a map with an accuracy of 0.86 according to the index Kappa. The results suggest that this classification approach may also provide better results by applying it on images having similar characteristics to the IKONOS image.