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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Satellite-derived time-series of shoreline change along the Pacific Rim

Authors: Kilian Vos;

Satellite-derived time-series of shoreline change along the Pacific Rim

Abstract

This repository contains 40 years of tidally-corrected shoreline change time-series for most sandy coastlines around the Pacific Rim derived from Landsat imagery. The time-series were last updated in May 2025. For the latest data always refer to http://coastsat.space/. The dataset was used to investigate the impact of ENSO on beach erosion and accretion in:- Vos, K., Harley, M.D., Turner, I.L. et al. Pacific shoreline erosion and accretion patterns controlled by El Niño/Southern Oscillation. Nat. Geosci. 16, 140–146 (2023). https://doi.org/10.1038/s41561-022-01117-8 CoastSat was used to map shoreline changes on Landsat 5, Landsat 7 and Landsat 8 imagery between 1984 and 2025. The Coastsat toolbox is publicly available at https://github.com/kvos/CoastSat and described in Vos et al. 2019, https://doi.org/10.1016/j.envsoft.2019.104528. The time-series of shoreline change were tidally-corrected along cross-shore transects using tide levels from a global tide model (FES2022) and a satellite-derived estimate of the beach slope (as described in Vos et al. 2020, "Beach slopes from satellite-derived shorelines", https://doi.org/10.1029/2020GL088365). This dataset covers wave-dominated sandy coasts in the Pacific basin where Landsat imagery was available, including a total of 3,000 beaches and more than 100,000 cross-shore transects (100-m alongshore spaced). This includes coastlines in Australia, New Zealand, Japan, Chile , Peru, Mexico and USA (California and Hawaii only). The data is structured as follows: There is a folder for each country (e.g. Australia) In the country folder, there is a folder for each site (e.g. aus0001, aus0002 etc) In the site folder, there are 4 CSV files: time_series_tidally_corrected.csv: this file contains the tidally-corrected time-series of shoreline change along each transect belonging to the site (e.g. aus0001-0001, aus0001-0002 etc). This is the final product used for coastal change analyses. time_series_raw.csv: this file contains the raw time-series of shoreline change, which have not be tidally-corrected. Note that each image is taken at a different stage of the tide. tide_levels_fes2022: this file contains the tide levels at the time of image acquisition extracted from FES2022 (global tide model publicly available on AVISO+). transect_coordinates_and_beach_slopes.csv: this file contains the coordinates (in WGS84 lat/lon coordinates) as well as the estimated beach slope for each transect, including confidence intervals. In addition, there are four geospatial layers (.GEOJSON) which contain important spatial information: polygons.geojson: this layer contains the polygons that were used to run CoastSat for each beach. shorelines.geojson: this layer contains the sandy shorelines that were used to generate the cross-shore transects (also used as reference shorelines in CoastSat). Each beach has the following attributes: beach length, median orientation, median slope, and mean springs tidal range. transects.geojson: this layer contains the cross-shore transects, which are spaced 100 m along each beach. Each transect has the following attributes: orientation, beach slope, linear trend (in m/year), alongshore distance relative to the northern end of the beach (absolute and normalised). transects_edit.geojson: this layer is the same as transects.geojson but the transects that are not suitable for shoreline mapping were manually deleted (rocky shores, submerged reef, coastal lagoons and inlets, coastal defences etc...). transects_ENSO.geojson: this layer (similar to transects.geojson) contains the transects that were used to analyse ENSO effects on shoreline changes in the Pacific (a total of 83,000).

Related Organizations
Keywords

satellite-derived shorelines, ENSO, CoastSat, Landsat, coastal change

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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