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:	26 Feb 2019 22:55
URI:	http://repository.usp.ac.fj/id/eprint/11109

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