Segmenting mangrove ecosystems drone images using SLIC superpixels

Zimudzi, Edward and Sanders, Ian and Rollings, Nicholas and Omlin, Christian (2018) Segmenting mangrove ecosystems drone images using SLIC superpixels. Geocarto International, TBC . TBC. ISSN 1010-6049

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Abstract

Mangrove ecosystems play a very important ecological role on land-ocean interfaces in tropical
regions. These ecosystems comprise of various tree species and aquatic animals, protecting
the environment and providing a habitat that supports many living organisms including
humans. The identification of image regions in mangrove ecosystems plays a significant
role in ecosystem monitoring and conservation. Recent studies have suggested
oversegmentation of colour images using superpixels as a solution to the segmentation of
image regions. This study used the SLIC superpixel algorithm and k-means clustering to
segment images taken from a camera mounted on a drone from a mangrove ecosystem in Fiji.
The SLIC superpixel algorithm performed well to demarcate image regions with similar
colour and texture information into patches and to use k-means for the segmentation of the
whole image. These results lend support to the use of superpixel algorithms for the
segmentation of mangrove ecosystems. Understanding how superpixels can be used for the
segmentation of drone images will assist conservation efforts in mangrove ecosystems.

Item Type:	Journal Article
Subjects:	G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography G Geography. Anthropology. Recreation > GE Environmental Sciences
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Geography, Earth Science and Environment
Depositing User:	Nicholas Rollings
Date Deposited:	26 Feb 2019 22:55
Last Modified:	16 Oct 2023 00:40
URI:	https://repository.usp.ac.fj/id/eprint/11109

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