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Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing

Raster data shows landscape scale trajectories of change as four potential scenarios based on Normalized Difference Vegetation Index (NDVI) trends and standard deviation trends using full time series (Scenarios_All_FULL_TS.tif) as well as time series up to LandTrendr breakpoint if detected (Scenarios_All_LT_TS.tif). Time series analysis for trend use Landsat surface reflectance imagery from 1985 to 2021. Scenarios: 1) Abrupt Transition – ecosystem is unstable and transitioning to alternate state (regime shift, exhibiting EWS); 2) Slowly Transitioning – ecosystem is transitioning slowly to alternate state (no EWS detected); 3) Recovering ecosystem – ecosystem is unstable but also becoming re-vegetated over the years; 4) Stable – becoming “greener” and more stable over time.

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Author(s) Melinda Martinez orcid, Marcelo Ardon, Joshua Gray
Publication Date 2024-09-16
Beginning Date of Data 1985-08-01
Ending Date of Data 2021-12-31
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DOI https://doi.org/10.5066/P145DV8T
Citation Martinez, M., Ardon, M., and Gray, J., 2024, Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing: U.S. Geological Survey data release, https://doi.org/10.5066/P145DV8T.
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Metadata Date 2024-09-16
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Citations of these data No citations of these data are known at this time.
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License http://www.usa.gov/publicdomain/label/1.0/
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Harvest Source: ScienceBase
Harvest Date: 2024-09-17T04:55:17.053Z