PJB-2018-58
MANGROVE TREE CROWNS DELINEATION WITH AUTOMATED OBJECT BASED REGION GROWING ALGORITHM
Hina Masood
Abstract
Delineating individual tree crown, especially mangrove is very challenging due to their density, limited variation in height and spatial heterogeneity. Recently, various research concentrated to detect individual tree crown of numerous vegetation using high resolution remotely sensed images with satisfactory results. Several approaches have been tested to quantifying the isolated tree crown. The aim of the present study was to investigate the automated individual tree crowns (ITCs) delineation of mangrove using a region growing algorithm with high resolution GeoEye 1 data. To obtain the information of tree crown is important for forest inventory and suitable management purposes. The canopy counting is becoming difficult when the trees are close together such as mangrove tree’s crown make a cluster. To achieve a better accuracy, it is possible to use very high spatial resolution imagery to isolate the tree crown of mangrove with appropriate algorithm.
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