These datasets were created from high-resolution (1-m) datasets representing median conditions during a 2014-2019 time period. These datasets used National Agricultural Inventory Program (NAIP) imagery, as well as Sentinel-2 satellite imagery, to estimate the fractional composition of unvegetated, vegetated, and water in each pixel. Random samples from these high resolution datasets were used to inform calibration and validation of the moderate resolution (30-m) Landsat datasets. To facilitate comparability with the Landsat datasets, these data were aggregated up to 30-m resolution.

These datasets were created from high-resolution (1-m) datasets representing median conditions during a 2014-2019 time period. These datasets used National Agricultural Inventory Program (NAIP) imagery, as well as Sentinel-2 satellite imagery, to estimate the fractional composition of unvegetated, vegetated, and water in each pixel. Random samples from these high resolution datasets were used to inform calibration and validation of the moderate resolution (30-m) Landsat datasets. To facilitate comparability with the Landsat datasets, these data were aggregated up to 30-m resolution.

These datasets were created from high-resolution (1-m) datasets representing median conditions during a 2014-2019 time period. These datasets used National Agricultural Inventory Program (NAIP) imagery, as well as Sentinel-2 satellite imagery, to estimate the fractional composition of unvegetated, vegetated, and water in each pixel. Random samples from these high resolution datasets were used to inform calibration and validation of the moderate resolution (30-m) Landsat datasets. To facilitate comparability with the Landsat datasets, these data were aggregated up to 30-m resolution.

These datasets were created from high-resolution (1-m) datasets representing median conditions during a 2014-2019 time period. These datasets used National Agricultural Inventory Program (NAIP) imagery, as well as Sentinel-2 satellite imagery, to estimate the fractional composition of unvegetated, vegetated, and water in each pixel. Random samples from these high resolution datasets were used to inform calibration and validation of the moderate resolution (30-m) Landsat datasets. To facilitate comparability with the Landsat datasets, these data were aggregated up to 30-m resolution.

These datasets were created from high-resolution (1-m) datasets representing median conditions during a 2014-2019 time period. These datasets used National Agricultural Inventory Program (NAIP) imagery, as well as Sentinel-2 satellite imagery, to estimate the fractional composition of unvegetated, vegetated, and water in each pixel. Random samples from these high resolution datasets were used to inform calibration and validation of the moderate resolution (30-m) Landsat datasets. To facilitate comparability with the Landsat datasets, these data were aggregated up to 30-m resolution.

In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science Center made in-situ observations during 2018-2019 and 2022-2023 at two sites: Thompsons Beach, NJ and Stone Harbor, NJ. Marsh creek hydrodynamics and water quality including currents, waves, water levels, water temperature, salinity, pH, dissolved oxygen, turbidity, organic matter, chlorophyll-a, and suspended-sediment concentration and organic content were measured at both sites. Additionally, marsh accretion and erosion were evaluated and used to interpret sediment budgets. These ecological data will be coupled with topographic lidar and imagery to explain the processes responsible for coastline evolution, and to evaluate restoration techniques and assess whether storm vulnerability has decreased relative to unaltered environments.

In 2012, Hurricane Sandy struck the Northeastern US causing devastation among coastal ecosystems. Post-hurricane marsh restoration efforts have included sediment deposition, planting of vegetation, and restoring tidal hydrology. The work presented here is part of a larger project funded by the National Fish and Wildlife Foundation (NFWF) to monitor the post-restoration ecological resilience of coastal ecosystems in the wake of Hurricane Sandy. The U.S. Geological Survey Woods Hole Coastal and Marine Science Center made in-situ observations during 2018-2019 and 2022-2023 at two sites: Thompsons Beach, NJ and Stone Harbor, NJ. Marsh creek hydrodynamics and water quality including currents, waves, water levels, water temperature, salinity, pH, dissolved oxygen, turbidity, organic matter, chlorophyll-a, and suspended-sediment concentration and organic content were measured at both sites. Additionally, marsh accretion and erosion were evaluated and used to interpret sediment budgets. These ecological data will be coupled with topographic lidar and imagery to explain the processes responsible for coastline evolution, and to evaluate restoration techniques and assess whether storm vulnerability has decreased relative to unaltered environments.

Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of the 1) unvegetated fraction, 2) vegetated fraction, 3) water fraction and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the year 2007. Additionally, multi-year average values of vegetated ratio, its standard deviation and a UVVR based on the annually-averaged vegetated ratio are provided for the coastal wetlands of the contiguous United States.

Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of the 1) unvegetated fraction, 2) vegetated fraction, 3) water fraction and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the year 1999. Additionally, multi-year average values of vegetated ratio, its standard deviation and a UVVR based on the annually-averaged vegetated ratio are provided for the coastal wetlands of the contiguous United States.

Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of the 1) unvegetated fraction, 2) vegetated fraction, 3) water fraction and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the year 1999. Additionally, multi-year average values of vegetated ratio, its standard deviation and a UVVR based on the annually-averaged vegetated ratio are provided for the coastal wetlands of the contiguous United States.