Abstract : This PhD work aims at providing information on the forest structure through the analysis of canopy properties as described by the spatial distribution and the crown size of dominant trees. Our approach is based on the Marked Point Processes (MPP) theory, which allows modeling tree crowns observed in remote sensing images by discs belonging a two dimensional space. The potential of MPP to detect the trees crowns automatically is evaluated by using very high spatial resolution optical satellite images of both Eucalyptus plantations and mangrove forest. Lidar and simulated reflectance images are also analyzed for the mangrove application. Different adaptations (parameter settings, energy models) of the MPP method are tested and compared through the development of quantitative indices that allow comparison between detection results and tree references derived from the field, photo-interpretation or the forest mockups. In the case of mangroves, the estimated crown sizes from detections are consistent with the outputs from the available allometric models. Other results indicate that tree detection by MPP allows mapping, the local density of trees of young Eucalyptus plantations even if crown size is close to the image spatial resolution (0.5m). However, the quality of detection by MPP decreases with canopy closeness. To improve the results, further work may involve MPP detection using objects with finer shapes and forest data measurements collected at the tree plant scale.