12 June 2017 Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery
Hoang Hai Nguyen, Hien Tran, Wooyeon Sunwoo, Jong-hyuk Yi, Dongkyun Kim, Minha Choi
Author Affiliations +
Abstract
A series of multispectral high-resolution Korean Multi-Purpose Satellite (KOMPSAT) images was used to detect the geographical changes in four different tidal flats between the Yellow Sea and the west coast of South Korea. The method of unsupervised classification was used to generate a series of land use/land cover (LULC) maps from satellite images, which were then used as input for temporal trajectory analysis to detect the temporal change of coastal wetlands and its association with natural and anthropogenic activities. The accurately classified LULC maps of KOMPSAT images, with overall accuracy ranging from 83.34% to 95.43%, indicate that these multispectral high-resolution satellite data are highly applicable to the generation of high-quality thematic maps for extracting wetlands. The result of the trajectory analysis showed that, while the variation of the tidal flats in the Gyeonggi and Jeollabuk provinces was well correlated with the regular tidal regimes, the reductive trajectory of the wetland areas belonging to the Saemangeum province was caused by a high degree of human-induced activities including large reclamation and urbanization. The conservation of the Jeungdo Wetland Protected Area in the Jeollanam province revealed that effective social and environmental policies could help in protecting coastal wetlands from degradation.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2017/$25.00 © 2017 SPIE
Hoang Hai Nguyen, Hien Tran, Wooyeon Sunwoo, Jong-hyuk Yi, Dongkyun Kim, and Minha Choi "Integrated change detection and temporal trajectory analysis of coastal wetlands using high spatial resolution Korean Multi-Purpose Satellite series imagery," Journal of Applied Remote Sensing 11(2), 026030 (12 June 2017). https://doi.org/10.1117/1.JRS.11.026030
Received: 22 January 2017; Accepted: 23 May 2017; Published: 12 June 2017
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Satellite imaging

Satellites

Earth observing sensors

Spatial resolution

Image classification

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