Salt marsh monitoring along the mid-Atlantic coast by Google Earth Engine enabled time series

Salt marshes provide a bulwark against sea-level rise (SLR), an interface between aquatic and terrestrial habitats, important nursery grounds for many species, a buffer against extreme storm impacts, and vast blue carbon repositories. However, salt marshes are at risk of loss from a variety of stres...

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Bibliographic Details
Published in:PloS one 2020-02, Vol.15 (2), p.e0229605
Main Authors: Campbell, Anthony Daniel, Wang, Yeqiao
Format: Article
Language:English
Subjects:
Animal behavior
Anthropogenic factors
Aquatic habitats
Atlantic Ocean
Biomass
Changing environments
Cloud cover
Coasts
Decomposition
Drownings
Earth Sciences
Ecological Parameter Monitoring
Ecology and Environmental Sciences
Ecosystem
Ecosystem management
Ecosystems
Environmental changes
Extreme weather
Herbivory
Human influences
Hydrology
Landsat
Landsat satellites
Monitoring
Natural resources
Nursery grounds
Nutrient dynamics
Nutrient enrichment
Nutrient loss
Physical Sciences
Regional analysis
Regional planning
Remote sensing
Research and Analysis Methods
Salt marshes
Sea level rise
Seasonal variations
Sediments
Sediments (Geology)
Soil erosion
Strategic management
Temporal resolution
Terrestrial environments
Tidal flooding
Tidal marshes
Time
Time series
Trends
Vegetation
Watersheds
Wetlands
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Summary:Salt marshes provide a bulwark against sea-level rise (SLR), an interface between aquatic and terrestrial habitats, important nursery grounds for many species, a buffer against extreme storm impacts, and vast blue carbon repositories. However, salt marshes are at risk of loss from a variety of stressors such as SLR, nutrient enrichment, sediment deficits, herbivory, and anthropogenic disturbances. Determining the dynamics of salt marsh change with remote sensing requires high temporal resolution due to the spectral variability caused by disturbance, tides, and seasonality. Time series analysis of salt marshes can broaden our understanding of these changing environments. This study analyzed aboveground green biomass (AGB) in seven mid-Atlantic Hydrological Unit Code 8 (HUC-8) watersheds. The study revealed that the Eastern Lower Delmarva watershed had the highest average loss and the largest net reduction in salt marsh AGB from 1999-2018. The study developed a method that used Google Earth Engine (GEE) enabled time series of the Landsat archive for regional analysis of salt marsh change and identified at-risk watersheds and salt marshes providing insight into the resilience and management of these ecosystems. The time series were filtered by cloud cover and the Tidal Marsh Inundation Index (TMII). The combination of GEE enabled Landsat time series, and TMII filtering demonstrated a promising method for historic assessment and continued monitoring of salt marsh dynamics.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0229605