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Article: Continuous monitoring of coastline dynamics in western Florida with a 30-year time series of Landsat imagery

TitleContinuous monitoring of coastline dynamics in western Florida with a 30-year time series of Landsat imagery
Authors
KeywordsTrend analysis
Satellite imagery
Coastline dynamics
Issue Date2016
Citation
Remote Sensing of Environment, 2016, v. 179, p. 196-209 How to Cite?
Abstract© 2016 Elsevier Inc.. Continuous monitoring of coastline dynamics is of crucial importance to the understanding of relative contributions of various potential driving factors behind the long-term coastline change. While a large number of efforts have been made to extract coastline and detect coastline change with remotely sensed data, the temporal frequency and spatial resolution of coastline datasets obtained are generally not fine enough to reflect the detailed process of coastline retreat and/or advance, particularly in coastlines with subtle variability. To overcome these limitations, we developed a method to continuously monitor the dynamics of a muddy coastline with subtle variability in western Florida at annual and subpixel scales using time-series Landsat data (1984-2013). First, robust indicators were used to indicate the annual "average" location of the dynamic coastline. Due to the complexity of muddy-coast morphology, the annual average location is represented not by the coast "line", but by the fractional inundated "area" of coastline pixels (pixels where the coastline is located), namely annually inundated area. Second, the annually inundated area of coastline pixels was estimated with a model proposed in this study, and the uncertainty was estimated with the Monte Carlo method. The retrievals were validated at 10 sites with aerial imagery, and the overall RMSE (root mean square error) is 11.48%. Third, the long-term trend for the time series of annually inundated area was derived with a statistical model. The results indicate that the muddy coast in western Florida continues to shrink with an average rate of 0.42 ± 0.05 km2/year during the three decades. This study demonstrates the feasibility of time-series Landsat data in continuous monitoring of coastline dynamics.
Persistent Identifierhttp://hdl.handle.net/10722/296775
ISSN
2023 Impact Factor: 11.1
2023 SCImago Journal Rankings: 4.310
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Wenyu-
dc.contributor.authorGong, Peng-
dc.date.accessioned2021-02-25T15:16:39Z-
dc.date.available2021-02-25T15:16:39Z-
dc.date.issued2016-
dc.identifier.citationRemote Sensing of Environment, 2016, v. 179, p. 196-209-
dc.identifier.issn0034-4257-
dc.identifier.urihttp://hdl.handle.net/10722/296775-
dc.description.abstract© 2016 Elsevier Inc.. Continuous monitoring of coastline dynamics is of crucial importance to the understanding of relative contributions of various potential driving factors behind the long-term coastline change. While a large number of efforts have been made to extract coastline and detect coastline change with remotely sensed data, the temporal frequency and spatial resolution of coastline datasets obtained are generally not fine enough to reflect the detailed process of coastline retreat and/or advance, particularly in coastlines with subtle variability. To overcome these limitations, we developed a method to continuously monitor the dynamics of a muddy coastline with subtle variability in western Florida at annual and subpixel scales using time-series Landsat data (1984-2013). First, robust indicators were used to indicate the annual "average" location of the dynamic coastline. Due to the complexity of muddy-coast morphology, the annual average location is represented not by the coast "line", but by the fractional inundated "area" of coastline pixels (pixels where the coastline is located), namely annually inundated area. Second, the annually inundated area of coastline pixels was estimated with a model proposed in this study, and the uncertainty was estimated with the Monte Carlo method. The retrievals were validated at 10 sites with aerial imagery, and the overall RMSE (root mean square error) is 11.48%. Third, the long-term trend for the time series of annually inundated area was derived with a statistical model. The results indicate that the muddy coast in western Florida continues to shrink with an average rate of 0.42 ± 0.05 km2/year during the three decades. This study demonstrates the feasibility of time-series Landsat data in continuous monitoring of coastline dynamics.-
dc.languageeng-
dc.relation.ispartofRemote Sensing of Environment-
dc.subjectTrend analysis-
dc.subjectSatellite imagery-
dc.subjectCoastline dynamics-
dc.titleContinuous monitoring of coastline dynamics in western Florida with a 30-year time series of Landsat imagery-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.rse.2016.03.031-
dc.identifier.scopuseid_2-s2.0-84962668800-
dc.identifier.volume179-
dc.identifier.spage196-
dc.identifier.epage209-
dc.identifier.isiWOS:000375506100016-
dc.identifier.issnl0034-4257-

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