Multi-temporal change detection of seagrass beds using integrated Landsat TM/ETM +/OLI imageries in Cam Ranh Bay, Vietnam

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Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/101705

Title:	Multi-temporal change detection of seagrass beds using integrated Landsat TM/ETM +/OLI imageries in Cam Ranh Bay, Vietnam
Authors:	陳繼藩;Chen, Chi-Farn;Lau, Va-Khin;Chang, Ni-Bin;Son, Nguyen-Thanh;Tong, Phuoc-Hoang-Son;Chiang, Shou-Hao
Contributors:	太空及遙測研究中心
Keywords:	aquatic environment;biofilters;Cam Ranh Bay;Change analysis;fish;infrastructure;Landsat;Landsat data;Linear mixture model;marine ecosystems;monitoring;reflectance;remote sensing;Seagrass beds;seagrasses;society;spawning;statistical models;temporal variation;Vietnam
Date:	2016-09-01
Issue Date:	2026-04-21 14:41:17 (UTC+8)
Publisher:	Elsevier;Elsevier B.V
Abstract:	摘要： Seagrass beds comprise a unique marine ecosystem that acts as a biofilter in marine environments and serves as a spawning ground and nursery for various species of fish. Long-term monitoring of seagrass beds is critical to understanding the dynamic relationships between the ecosystems and the stresses from natural systems and society. This study investigated temporal changes of seagrass beds in Cam Ranh Bay (CRB), Vietnam using multi-temporal Landsat data from 1996 to 2015. The data were processed through 5 main steps including: (1) image preprocessing to convert Landsat data to the top of atmosphere reflectance (TOA) and to correct atmospheric effects, (2) water column correction to eliminate effects on remotely sensed data of aquatic environments, (3) image classification using a linear mixed model, (4) accuracy assessment using the ground reference data, and (5) change detection of seagrass beds. The classification results compared with the ground reference data indicated that the overall accuracies and Kappa coefficients were higher than 91.7% and 0.8, respectively, in all cases. From 1996 to 2015, the total area of seagrass beds had declined by approximately 25% (66ha), mainly attributed to coastal development and infrastructure construction. •This study assessed changes of seagrass beds in Cam Ranh Bay using Landsat data.•The data were processed for 5 periods from 1996 to 2015 using linear mixture model.•Classification maps compared with the reference data revealed satisfactory results.•From 1996 to 2015, 66ha of seagrass beds had declined due to coastal development. 出版者： Elsevier B.V 出版日期： 2016-09 出處： Ecological Informatics, 2016-09, Vol.35, p.43-54 版權： 2016 Elsevier B.V. 識別號： ISSN: 1574-9541 識別號： ISSN: 1878-0512 識別號： DOI: 10.1016/j.ecoinf.2016.07.005
Appears in Collections:	[Center for Space and Remote Sensing Research ] journal & Dissertation

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