Characterizing the spatial structure of Mangrove features for optimizing image-based mangrove mapping

Kamal, Muhammad, Phinn, Stuart and Johansen, Kasper (2014) Characterizing the spatial structure of Mangrove features for optimizing image-based mangrove mapping. Remote Sensing, 6 2: 984-1006. doi:10.3390/rs6020984

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Author Kamal, Muhammad
Phinn, Stuart
Johansen, Kasper
Title Characterizing the spatial structure of Mangrove features for optimizing image-based mangrove mapping
Journal name Remote Sensing   Check publisher's open access policy
ISSN 2072-4292
Publication date 2014-01-01
Year available 2014
Sub-type Article (original research)
DOI 10.3390/rs6020984
Open Access Status DOI
Volume 6
Issue 2
Start page 984
End page 1006
Total pages 23
Place of publication Basel, Switzerland
Publisher M D P I AG
Language eng
Abstract Understanding the relationship between the size of mangrove structural features and the optimum image pixel size is essential to support effective mapping activities in mangrove environments. This study developed a method to estimate the optimum image pixel size for accurately mapping mangrove features (canopy types and features (gaps, tree crown), community, and cover types) and tested the applicability of the results. Semi-variograms were used to characterize the spatial structure of mangrove vegetation by estimating the size of dominant image features in WorldView-2 imagery resampled over a range of pixel sizes at several mangrove areas in Moreton Bay, Australia. The results show that semi-variograms detected the variations in the structural properties of mangroves in the study area and its forms were controlled by the image pixel size, the spectral-band used, and the spatial characteristics of the scene object, e.g., tree or gap. This information was synthesized to derive the optimum image pixel size for mapping mangrove structural and compositional features at specific spatial scales. Interpretation of semi-variograms combined with field data and visual image interpretation confirms that certain vegetation structural features are detectable at specific scales and can be optimally detected using a specific image pixel size. The analysis results provide a basis for multi-scale mangrove mapping using high spatial resolution image datasets.
Keyword Mangrove
Multi-scale
Object-based
Optimum pixel size
Segmentation
Semi-variogram
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
Official 2015 Collection
 
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Citation counts: TR Web of Science Citation Count  Cited 8 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 9 times in Scopus Article | Citations
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Created: Tue, 11 Mar 2014, 10:51:27 EST by System User on behalf of School of Geography, Planning & Env Management