OVERVIEW
This dataset contains shoreline position time series and related spatial data 
for multiple globally distributed sea turtle nesting beaches, underlying the 
analysis presented in Chapter 4 of the dissertation "Coastal Science for Sea 
Turtle Conservation" by Jakob C. Christiaanse (2025). 

For each study site, the data includes extracted shorelines, a reference 
shoreline, shoreline position time series (raw, filtered, and tide-corrected), 
shoreline decomposition results for three transects, and the transect geometries. 
The dataset is organized to facilitate reproducible coastal change analysis and 
supports research on coastal dynamics and sea turtle habitat. Data are provided 
in CSV and GeoJSON formats, compatible with common data analysis tools.

The Chapter is currently in preparation to be submitted as a journal article.
Until it is published, please cite the dissertation when using this data (see 
references).

CONTENTS
The data is divided in one folder per study site:
- AI_LB: Long Beach, Ascension Island
- AU_DH: Dirk Hartog Island, Australia
- BR_BV: Busca Vida, Brazil
- CR_TO: Tortuguero, Costa Rica
- CV_JB: Joao Barrosa, Cabo Verde
- CY_AL: Alagadi, Cyprus
- MX_LE: La Escobilla, Mexico
- MX_RN: Rancho Nuevo, Mexico
- OM_MI: Masirah Island, Oman

DATA STRUCTURE
Each study site folder contains the following nine files:

- **_**_mapped_shorelines.geojson
    The extracted shorelines as line-strings.  
    --Attributes--  
        - id: Unique identifier for each shoreline  
        - date: Acquisition date  
        - source: Data source or satellite  
        - geometry: LineString geometry of the shoreline  
        - [other site-specific attributes as needed]

- **_**_reference_shoreline.geojson
    Manually digitized reference shoreline used in the CoastSat extraction. 
    This is NOT the reference shoreline position referred to in the Chapter 
    (which is the median tide-corrected shoreline position between 2021-2024).
    --Attributes--  
        - geometry: LineString geometry  

- **_**_sds_timeseries_0_raw.csv
    Raw CoastSat-extracted shoreline position time series. Shoreline position 
    is given in metres from the landward end of the transect
    --Columns--
        - One column per transect (T1, T2, T3)

- **_**_sds_timeseries_1_filtered.csv
    CoastSat-extracted shoreline position time series filtered for outliers 
    and inaccurate georeferences (> 12m).
    --Columns--
        - One column per transect (T1, T2, T3)

- **_**_sds_timeseries_2_tide.csv
    Filtered CoastSat-extracted shoreline position time series, corrected for
    tidal water level using FES2022 and estimated beach face slope. These are
    the time series used for analysis in the Chapter.
    --Columns--
        - One column per transect (T1, T2, T3)

- **_**_T1_shoreline_decomposition.csv
    Shoreline time series decomposition at transect T1. Shoreline positions are
    given in metres. For the first three columns, this is relative to the 
    median tide-corrected shoreline position between 2021-2024 (reference).
    --Columns--
        - monthly_med: Monthly median shoreline position computed from the 
        tide-corrected time series
        - interpolated: Monthly median shoreline position with linearly
        interpolated gaps.
        - Y_lt: Long-term trend computed as a 4-year LOESS trend over the
        interpolated column.
        - detrended: detrended monthly median shoreline position computed by
        subtracting Y_lt from monthly_med (gaps not interpolated anymore).
        - Y_ss: seasonal shoreline position, computed as the bulk median for
        every month, over the entire time series (so values repeat every year).
        - Y_res: residual shoreline position, computed by subtracting Y_ss from
        the detrended column.

- **_**_T2_shoreline_decomposition.csv
    Same as previous but for transect T2.

- **_**_T3_shoreline_decomposition.csv
    Same as previous but for transect T3.

- **_**_transects.geojson
    Transects used for shoreline extraction and analysis, as linestring geometries.  
    --Attributes--  
        - transect: Transect id (T1, T2, T3) 
        - gcts_id: Unique ID of transct in GCTS database (Calkoen et al. 2025).
        - geometry: LineString geometry  

DATA FORMAT
Tabular data, provided in two formats:
- *.csv file (for all regular tables)
- *.geojson file (when geometry variables are included)

USAGE
Any software or programming language that can read *.geojson and/or *.csv files can 
be used to analyse the data (Python, R, C++, Julia). We have used Python for all 
processing and operations on the data. Required python packages are Pandas and
GeoPandas. The *.geojson files can then simply be read using GeoPandas.read_file(),
which will return a GeoDataFrame with the data.

REFERENCES
Christiaanse, J. C. (2025). Coastal Science for Sea Turtle Conservation [Doctoral 
dissertation, Delft University of Technology].

Calkoen, F. R., Luijendijk, A. P., Vos, K., Kras, E., & Baart, F. (2025). Enabling 
coastal analytics at planetary scale. Environmental Modelling & Software, 183, 106257. 
https://doi.org/10.1016/j.envsoft.2024.106257

LICENSE
CC BY 4.0