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Comparing digital object based approaches for mangrove tree crown delineation using WorldView-2 satellite imagery

Heenkenda, Muditha K., Joyce, Karen E. and Maier, Stefan W. (2014). Comparing digital object based approaches for mangrove tree crown delineation using WorldView-2 satellite imagery. South-Eastern European Journal of Earth Observation and Geomatics,3(2S):169-172.

Document type: Journal Article
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IRMA ID 84376995xPUB50
Title Comparing digital object based approaches for mangrove tree crown delineation using WorldView-2 satellite imagery
Author Heenkenda, Muditha K.
Joyce, Karen E.
Maier, Stefan W.
Journal Name South-Eastern European Journal of Earth Observation and Geomatics
Publication Date 2014
Volume Number 3
Issue Number 2S
ISSN 2241-1224   (check CDU catalogue open catalogue search in new window)
Start Page 169
End Page 172
Total Pages 4
Place of Publication Greece
HERDC Category C1 - Journal Article (DIISR)
Abstract Mangroves are dense, spatially heterogeneous, and have limited height variations between neighbouring trees. Delineating individual tree crowns is thus very challenging. This study evaluated several different object-based image analysis approaches for isolating mangrove tree crowns using a WorldView-2 high spatial resolution image and a digital  surface model generated from true colour aerial photographs. The combination of WorldView-2 imagery, a local maxima filtering algorithm, and a region growing approach provided the best accuracy of the methods tested. The inverse watershed method of tree crown delineation showed the lowest accuracy, demonstrating that this method is only suitable for homogeneous forests with reasonable height variations between trees. Therefore, while isolating mangrove crowns using remote sensing is a challenging task, it is possible to achieve good results with very high spatial resolution imagery and appropriately parameterised object-based algorithms.
Keywords Mangroves
Object-based image analysis
Local maxima
Region growing
WorldView-2
 
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Created: Wed, 19 Aug 2015, 12:27:51 CST