Mangroves are very dense, spatially heterogeneous, and have limited height variations between neighboring trees. Delineating individual tree crowns is thus very challenging. This study compared methods for isolating mangrove crowns using object based image analysis. A combination of WorldView-2 imagery, a digital surface model, a local maximum filtering technique, and a region growing approach achieved 92 percent overall accuracy in extracting tree crowns. The more traditionally used inverse watershed segmentation method showed low accuracy (35 percent), demonstrating that this method is better suited to homogeneous forests with reasonable height variations between trees. The main challenges with each of the methods tested were the limited height variation between surrounding trees and multiple upward pointing branches of trees. In summary, mangrove tree crowns can be delineated from appropriately parameterized object based algorithms with a combination of high-resolution satellite images and a digital surface model. We recommend partitioning the imagery into homogeneous species stands for best results. � 2015 American Society for Photogrammetry and Remote Sensing.
Heenkenda Mudalige, M. K., Joyce, K., & Maier, S. (2015). Mangrove tree crown delineation from high-resolution imagery. Photogrammetric Engineering and Remote Sensing, 81(6), 471-479. https://doi.org/10.14358/PERS.81.6.471