Delineation of Individual Tree Crowns Using High Spatial Resolution Multispectral WorldView-3 Satellite Imagery

Fei Tong, Hengjian Tong, Rakesh Kumar Mishra, Yun Zhang
2021 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
Delineation of individual tree crowns can provide valuable information for sustainable forest management and environmental protection. However, it is hard to find a reliable tree crown delineation method that can continually generate expected results in high spatial resolution multispectral satellite images, because most of the existing methods need user-assigned parameters that greatly affect the quality of the delineation results. In this paper, we propose a method based on the
more » ... d watershed segmentation to delineate individual tree crowns using high spatial resolution multispectral WorldView-3 satellite imagery. A gradient binarization process is proposed to accurately locate tree crown borders. The threshold for the binarization is determined by a supervised searching process. Markers used in marker-controlled watershed segmentation are spatial local maxima detected from the information provided by tree crown borders. Moreover, the definition of spatial local maxima from the literature is improved to eliminate false treetops. To validate the performance of the proposed delineation method, delineation results are compared with those obtained from the Spectral Angle Segmentation (SAS) method that has been proposed in literature because the quality of delineation results generated by SAS does not rely on user-assigned parameters. The experiment results in two test images demonstrate that the proposed method outperforms SAS in terms of both delineation accuracy and visual quality of the delineation map. What's more, it is proved that the modified spatial local maxima are more reliable for detecting treetops. Index Terms-Gradient binarization, individual tree crown delineation, WorldView-3 satellite imagery, tree crown borders, treetop detection, spatial local maxima. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.
doi:10.1109/jstars.2021.3100748 fatcat:t6bmgi3ccnf5jekbibmuxnqfpm