The doi 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: 10.4121/20066333

Marieke Laengner; van der Wal, D. (Daphne) (2022): Data associated with the article "Satellite-derived Trends in Inundation Frequency Reveal the Fate of Saltmarshes”. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/20066333.v2

Dataset

x choose version: version 1 - 2022-07-13

• Land and Water Management
• Ecosystem Assessment and Management

intertidal, inundation frequency, Landsat TM images, Relative Sea Level (RSL), saltmarsh, sea level rise (SLR)

1986-2010

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Marieke Laengner , D. (Daphne) van der Wal

In the publication associated with this dataset we retrieve inundation frequency change in different tidal basins over 27 years using satellite data from the entire Landsat 5 TM dataset. The method to retrieve inundation frequency is applied in Google Earth Engine (GEE). We further retrieve habitat change from the same satellite dataset and investigate how changes in inundation frequency affect saltmarsh development. In this dataset we provide time series of mean inundation frequency over the respective tidal basin; time series of habitat change; the GEE scripts which generate those time series; a pixelwise comparison of generated inundation frequency with another published inundation frequency and an elevation dataset of the same basin, as well as the GEE scripts generating this pixelwise comparison; generated maps of significant inundation frequency change between 1986 and 2010; and generated habitat classification (saltmarsh, tidal flats, water) maps from 1986 and 2010.

• 2022-07-13 first online, published, posted

4TU.ResearchData

*.csv; *.tif; *.txt

Satellite-derived Trends in Inundation Frequency Reveal the Fate of Saltmarshes

• Saltmarshes under stress: thresholds for saltmarsh dynamics from global satellite data (MARSH) (grant code ALW-GO/16-37) [more info...] Dutch Research Council

NIOZ Royal Netherlands Institute for Sea Research, Department of Estuarine & Delta Systems and Utrecht University;
University of Twente, Faculty of Geo-Information Science and Earth Observation