Data underlying Chapter 4 of the dissertation "Coastal Science for Sea Turtle Conservation"

DOI:10.4121/0a7cf460-e3da-4f80-aa20-f41eb7f9ef93.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/0a7cf460-e3da-4f80-aa20-f41eb7f9ef93

Datacite citation style

Christiaanse, Jakob C.; Vitousek, Sean; Ad J.H.M. Reniers; Antolínez, José A. A. (2025): Data underlying Chapter 4 of the dissertation "Coastal Science for Sea Turtle Conservation". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/0a7cf460-e3da-4f80-aa20-f41eb7f9ef93.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This dataset contains the data underlying the analyses presented in Chapter 4 of the PhD thesis "Coastal Science for Sea Turtle Conservation" by Jakob C. Christiaanse. In that study, we combined satellite-derived shorelines (CoastSat), shoreline modeling (CoSMoS-COAST), and global datasets to analyze the shoreline evolution, characteristics, and future vulnerability of nine globally important sea turtle nesting beaches. We identify seasonal and long-term shoreline change patterns, hindcast (1980-2024) and forecast (2025-2100) shoreline positions under various sea level rise scenarios, and quantify available accommodation space based on backbeach elevation and infrastructure footprints. This dataset includes the satellite satellite-derived shoreline positions, model input (hydrodynamics, slope, shorelines) and output (hindcast and forecast shoreline positions), and backbeach characteristics for each study site. The Matlab model code used to run the shoreline predictions is also included. The Chapter is currently in preparation to be submitted as a journal article. Until it is published, please cite this dataset and the dissertation when using this data:


Christiaanse, J. C. (2025). Coastal Science for Sea Turtle Conservation [Doctoral

dissertation, Delft University of Technology].

History

  • 2025-07-14 first online, published, posted

Publisher

4TU.ResearchData

Format

CSV, GeoJSON

Organizations

TU Delft, Faculty of Civil Engineering and Geosciences, Department of Hydraulic Engineering, Section of Coastal Engineering;
USGS Pacific Coastal and Marine Science Center Santa Cruz

DATA

Files (4)