Over time, as sea levels rise and land subsides, marsh transgression can occur. As shorelines erode and the marsh slowly transgresses landward into the upland, valuable coastal habitat simultaneously is lost and gained. If the shoreline erosion is faster than the rate of upland transgression, the result is a net loss in coastal wetlands. This dataset represents a marsh area change analysis for the Point Aux Chenes and Grand Bay estuaries in Mississippi and Alabama from 1848-1957/1958, 1848-2019/2022, and 1957/1958-2019/2022. Classified habitats are also included for 1848, 1957/1958 and 2022. Shoreline and upland boundary positional data were obtained from multiple data sources, including National Oceanic and Atmospheric Administration (NOAA) topographic sheets (t-sheets) and WorldView 2 high resolution satellite imagery. Two dates were chosen for the 1957/1958 (henceforth referred to as 1957), and 2019/2022 (henceforth be referred to as 2022) to provide complete coverage. Shorelines and upland lines were converted into raster data (.tif) to calculate marsh habitat area change over time. This data release contains a raster data for 1848, 1957, and 2022, as well as change rasters for 1848-1957, 1957-2022, and 1848-2022.

This U.S. Geological Survey (USGS) data release includes geospatial datasets that were created for the analysis of Virginia and Maryland Atlantic coastal wetland changes over time. Wetland change was determined by assessing two metrics: wetland persistence and land-cover switching. Because seasonal water levels, beach width, and vegetation differences can affect change analyses, only images acquired during the spring (March, April, and May) were included in the wetland-change metrics (N=10). Land-cover switching was evaluated using Landsat images for successive spring image-acquisition dates: 1985–1989, 1989–1994, 1994–1999, 1999–2004, 2004-2009, 2009-2011, 2011-2013, 2013-2014, and 2014-2015. To evaluate land-cover switching, land-cover types defined by Bernier and others (2015) were reclassified as 1 (water), 3 (wetland), or 7 (non-wetland). These values were chosen so the results of subtracting two dates will create unique values for each scenario. For example, if a cell in 1994 is classified as land and in 1989 was wetland, the result (1994-1989 or 7-3) is 4. If the cell in 1994 is wetland and in 1989 was water (3-1) the result is 2. With this analysis, each two-date combination results in a raster that identifies wetland-land-water conversions, such that water-to-land is -6, wetland-to-land is -4, water-to-wetland is -2, wetland-to-water equals 2, land-to-wetland is 4, and land-to-water is 6.

This U.S. Geological Survey (USGS) data release includes geospatial datasets that were created for the analysis of Virginia and Maryland Atlantic coastal wetland changes over time. Wetland change was determined by assessing two metrics: wetland persistence and land-cover switching. Because seasonal water levels, beach width, and vegetation differences can affect change analyses, only images acquired during the spring (March, April, and May) were included in the wetland-change metrics (N=10). To assess wetland-area trends, including wetland persistence, the total marsh and mixed vegetation classes land-cover types defined by Bernier and others (2015) were reclassified as 1 (wetland presence) and all other classes were reclassified as 0 (wetland absence). When the baseline data (1985) is subtracted from a later dataset, the outcome results in cells with three possible values: 0, 1, or -1, where -1 is wetland loss, 0 is no change (persistence), and 1 is wetland gain.

Unvegetated to vegetated marsh ratio (UVVR) in the Plum Island Estuary and Parker River (PIEPR) salt marsh complex was computed based on conceptual marsh units defined by Defne and Ganju (2018). UVVR was calculated based on U.S. Department of Agriculture National Agriculture Imagery Program (NAIP) 1-meter resolution imagery. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands, including the Plum Island Estuary and Parker River salt marsh complex, with the intent of providing Federal, State, and local managers with tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services. UVVR is planned to be an underlying parameter in the synthesis of these factors. References: Defne, Z., and Ganju, N.K., 2018, Conceptual marsh units for Plum Island Estuary and Parker River salt marsh complex, Massachusetts: U.S. Geological Survey data release, https://doi.org/10.5066/P9XF54QF

This data release contains coastal wetland synthesis products for the geographic region from Jamaica Bay to western Great South Bay, located in southeastern New York State. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, and mean tidal range, are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the intent of providing Federal, State, and local managers with tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services.

Biomass production is positively correlated with mean tidal range in salt marshes along the Atlantic coast of the United States of America. Recent studies support the idea that enhanced stability of the marshes can be attributed to increased vegetative growth due to increased tidal range. This dataset displays the spatial variation of mean tidal range (i.e. Mean Range of Tides, MN) in the Plum Island Estuary and Parker River (PIEPR) salt marsh complex based on conceptual marsh units defined by Defne and Ganju (2018). MN was based on the calculated difference in height between mean high water (MHW) and mean low water (MLW) using the VDatum (v3.5) database ( http://vdatum.noaa.gov/ ). Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands, including the Plum Island Estuary and Parker River salt marsh complex, with the intent of providing Federal, State, and local managers with tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services. Mean elevation of marsh units is planned to be an underlying parameter in the synthesis of these factors. References: Defne, Z., and Ganju, N.K., 2018, Conceptual marsh units for Plum Island Estuary and Parker River salt marsh complex, Massachusetts: U.S. Geological Survey data release, https://doi.org/10.5066/P9XF54QF

This data release contains coastal wetland synthesis products for the geographic region of north shore Long Island, New York. Metrics for resiliency, including unvegetated to vegetated ratio (UVVR), marsh elevation, mean tidal range, and shoreline change rate are calculated for smaller units delineated from a Digital Elevation Model, providing the spatial variability of physical factors that influence wetland health. Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands with the intent of providing Federal, State, and local managers with tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services. This dataset displays shoreline change rates for north shore Long Island. Shoreline change rates are based on analysis of digital vector shorelines acquired from historical topographic sheets provided by National Oceanic and Atmospheric Administration (NOAA). Analysis was performed using the Digital Shoreline Analysis System (DSAS), an extension for ArcMap, created by the U.S. Geological Survey. Linear Regression Rates (LRR) and End Point Rates (EPR) of shoreline change were averaged along the shoreline of each salt marsh unit to generate this dataset. LRR rates were used in areas where three or more historical shorelines were available while EPR was used in areas where two were available. Positive and negative values indicate accretion and erosion respectively.

The Bureau of Ocean Energy Management (BOEM) researchers often require detailed information regarding emergent marsh vegetation types (i.e., fresh, intermediate, brackish, and saline) for modeling habitat capacities and mitigation. In response, the U.S. Geological Survey, in collaboration with the Bureau of Ocean Energy Management produced a detailed change classification of emergent marsh vegetation types in coastal Louisiana from 2007 and 2013. This study incorporates decision-tree analyses to classify emergent marsh vegetation types using two existing vegetation surveys and independent variables such as Landsat and high-resolution airborne imagery from 2007 and 2013, bare-earth digital elevation models based on airborne light detection and ranging (lidar), alternative contemporary land cover classifications, and other spatially explicit variables. Image objects were created from 2007 and 2013 National Agriculture Imagery Program (NAIP) color-infrared aerial photography. The final classification consists of three 10-m raster datasets that were produced by using a majority filter to classify image objects according to the marsh vegetation type covering the majority of each image object. The classifications are dated 2007 and 2013 because the dates of the two vegetation surveys and of the high-resolution airborne imagery that was used to develop image objects. The seamless classification produced through this work can be used to help develop and refine conservation efforts for priority natural resources.

Elevation distribution in the Assateague Island National Seashore (ASIS) salt marsh complex and Chincoteague Bay is given in terms of mean elevation of conceptual marsh units defined by Defne and Ganju (2018). The elevation data is based on the 1-meter resolution Coastal National Elevation Database (CoNED). Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands, including the Assateague Island National Seashore and Chincoteague Bay salt marshes, with the intent of providing Federal, State, and local managers with tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services. References: Defne, Z., and Ganju, N.K., 2018, Conceptual marsh units for Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia: U.S. Geological Survey data release, https://doi.org/10.5066/P92ZW4D9.

Biomass production is positively correlated with mean tidal range in salt marshes along the Atlantic coast of the United States of America. Recent studies support the idea that enhanced stability of the marshes can be attributed to increased vegetative growth due to increased tidal range. This dataset displays the spatial variation of mean tidal range (i.e. Mean Range of Tides, MN) in the Assateague Island National Seashore and Chincoteague Bay based on conceptual marsh units defined by Defne and Ganju (2018). MN was based on the calculated difference in height between mean high water (MHW) and mean low water (MLW) using the VDatum (v3.5) database ( http://vdatum.noaa.gov/ ). Through scientific efforts initiated with the Hurricane Sandy Science Plan, the U.S. Geological Survey has been expanding national assessment of coastal change hazards and forecast products to coastal wetlands, including the Assateague Island National Seashore and Chincoteague Bay salt marshes, with the intent of providing Federal, State, and local managers with tools to estimate the vulnerability and ecosystem service potential of these wetlands. For this purpose, the response and resilience of coastal wetlands to physical factors need to be assessed in terms of the ensuing change to their vulnerability and ecosystem services. Mean elevation of marsh units is planned to be an underlying parameter in the synthesis of these factors. References: Defne, Z., and Ganju, N.K., 2018, Conceptual marsh units for Assateague Island National Seashore and Chincoteague Bay, Maryland and Virginia: U.S. Geological Survey data release, https://doi.org/10.5066/P92ZW4D9.