  Individual tree detection and crown delineation (ITDD) are critical in forest
inventory management and remote sensing based forest surveys are largely
carried out through satellite images. However, most of these surveys only use
2D spectral information which normally has not enough clues for ITDD. To fully
explore the satellite images, we propose a ITDD method using the orthophoto and
digital surface model (DSM) derived from the multi-view satellite data. Our
algorithm utilizes the top-hat morphological operation to efficiently extract
the local maxima from DSM as treetops, and then feed them to a modi-fied
superpixel segmentation that combines both 2D and 3D information for tree crown
delineation. In subsequent steps, our method incorporates the biological
characteristics of the crowns through plant allometric equation to falsify
potential outliers. Experiments against manually marked tree plots on three
representative regions have demonstrated promising results - the best overall
detection accuracy can be 89%.
