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This is a continuous raster dataset identifying wetlands that are currently suitable for mottled duck brood-rearing activities in the Western Gulf Coast. The identification process is based on key biological parameters such as wetland type, number of years inundated, distance to brood nesting habitat, etc. Additionally, this raster dataset presents the data in a form that prioritizes habitat from more suitable to less suitable based on landscape metrics. The scale ranges from 9.9999 to .000005, higher value designating higher suitability ranking.
Hurricane Sandy, which made landfall on October 29, 2012, near Brigantine, New Jersey, had a significant impact on coastal New Jersey, including the large areas of emergent wetlands at Edwin B. Forsythe National Wildlife Refuge (NWR) and the Barnegat Bay region. In response to Hurricane Sandy, U.S. Geological Survey (USGS) has undertaken several projects to assess the impacts of the storm and provide data and scientific analysis to support recovery and restoration efforts. As part of these efforts, the USGS Coastal and Marine Geology Program (CMGP) sponsored Coastal National Elevation Database (CoNED) Applications Project in collaboration with the USGS National Geospatial Program (NGP), and National Oceanic and...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for Suisun marsh using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (6912 points, collected across public and private land in 2018), Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image (June 2018), a 1 m lidar DEM from September 2018, and a 1 m canopy surface model were used to generate models of predicted bias across the...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation mode (DEM) for tidal marsh areas around San Francisco Bay using the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). Survey-grade GPS survey data (6614 points), NAIP-derived Normalized Difference Vegetation Index, and original 1 m lidar DEM from 2010 were used to generate a model of predicted bias across tidal marsh areas. The predicted bias was then subtracted from the original lidar DEM and merged with the NOAA...
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Description of condition index value scores for estuarine tidal marsh along and within 10 km of the GCPO LCC Gulf Coast subgeography. A series of raster calculations were used in a dichotomous decision-based framework to compile a per-pixel draft condition index value at a 10 m resolution for GCPO estuarine tidal marsh based on the number of configuration and condition endpoints met within each marsh pixel. Pixels not identified as a estuarine marsh but that were identified as having the potential to be marsh were given a score of 1, provided the pixels were not classified as developed. Potential estuarine tidal marsh pixels were derived from a combination of potential estuarine tidal marsh classes in the Landfire...
Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: AQUATIC ECOSYSTEMS, AQUATIC ECOSYSTEMS, BIOSPHERE, BIOSPHERE, BIOSPHERE, All tags...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for wetlands throughout Collier county using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (15,223 points), NAIP-derived Normalized Difference Vegetation Index (2010), a 10 m lidar DEM from 2007, and a 10 m canopy surface model were used to generate a model of predicted bias across marsh, mangrove, and cypress habitats. The predicted bias was then subtracted from...
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The research was conducted at nine tidal marshes in coastal estuaries spanning the Washington and Oregon coastlines from Padilla Bay in northern Washington to Bandon located at the mouth of the Coquille River in southern Oregon. We performed bathymetric surveys using a shallow-water echo-sounding system comprised of an acoustic profiler, Leica Viva RTK GPS, and laptop computer mounted on a shallow-draft, portable flat-bottom boat. The RTK GPS enabled high resolution elevations of the water surface. The rover positions were received from the Leica Smartnet system (www.lecia-geosystems.com) or base station and referenced to the same bench mark used in the elevation surveys. We mounted a variable frequency transducer...
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Extent and approximate location of historic wetland habitats in Indiana, Iowa, and Wisconsin. Partial state coverage in Minnesota and South Dakota. NWI data last updated as of 1 May 2016. Data accessed 11 July 2016.
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The Gulf Coastal Plains and Ozarks (GCPO) Landscape Conservation Cooperative (LCC) has conducted an ecological assessment of various landscape characteristics, or endpoints, outlined in the LCC Integrated Science Agenda. This data layer addresses the forested wetland amount desired landscape endpoint for the forested wetland ecosystem in the Mississippi Alluvial Valley subgeography of the GCPO LCC. This data was created by reclassification of the 2011 National Land Cover Dataset (NLCD) to pull out only the woody wetlands class (90) from the NLCD dataset.
Categories: Data; Types: ArcGIS REST Map Service, ArcGIS Service Definition, Downloadable, Map Service; Tags: AQUATIC ECOSYSTEMS, AQUATIC ECOSYSTEMS, BIOSPHERE, BIOSPHERE, BIOSPHERE, All tags...
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Lidar-derived digital elevation models often contain a vertical bias due to vegetation. In areas with tidal influence the amount of bias can be ecologically significant, for example, by decreasing the expected inundation frequency. We generated a corrected digital elevation model (DEM) for the area surrounding Blackwater National Wildlife Refuge in Chesapeake Bay using a modification of the Lidar Elevation Adjustment with NDVI (LEAN) technique (Buffington et al. 2016). GPS survey data (3699 points, collected across four tidal marsh sites in Chesapeake Bay (Eastern Neck, Martin, Bishops Head, and Blackwater) in 2010 and 2017. Normalized Difference Vegetation Index (NDVI) derived from an airborne multispectral image...
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To assess the current topography of tidal marsh at the study sites we conducted survey-grade global positioning system (GPS) surveys between 2009 and 2014 using a Leica RX1200 Real Time Kinematic (RTK) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK GPS network coverage (Padilla, Port Susan, Nisqually, Siletz, Bull Island, and Bandon), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Skokomish, Grays Harbor, and Willapa), rover positions were received in real time from a Leica GS10 antenna base station via radio link. At sites where we used the...
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This data set contains vector point information. The original data set was collected through visual field observation by Jennke Visser (University of Louisiana-Lafayette). The observations were made while flying over the study area in a helicopter. Flight was along north/south transects spaced 2000 meters apart from the Texas / Louisiana State line to Corpus Christie Bay. Vegetative data was obtained at pre-determined stations spaced at 1500 meters along each transect. The stations were located using a Global Positioning System (GPS) and a computer running ArcGIS. This information was recorded manually onto field tally sheets and later this information was entered into a Microsoft Excel database using Capturx software...
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The values for this dataset were extracted from the Index of Ecological Integrity, Region-wide, Version 3.2 for all wetland systems. Created 02/2018. The metadata for the original dataset is as follows: This dataset was last updated 02/2017. This version includes a new tidal restrictions metric that assesses the effect of undersized culverts and bridges on tidal regime.The previous version (3.1) was updated on 05/2016 by incorporating a revised version of the land cover classification, DSLland Version 3.1, developed by UMass, which included the addition of The Nature Conservancy’s Northeast lakes and ponds classification. Click here: http://www.conservationgateway.org/ConservationByGeography/NorthAmerica/UnitedStates/edc/reportsdata/freshwater/Pages/Northeast-Lakes.aspx...
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We used WARMER, a 1-D cohort model of wetland accretion (Swanson et al. 2014), which is based on Callaway et al. (1996), to examine SLR projections across each study site. Each cohort in the model represents the total organic and inorganic matter added to the soil column each year. WARMER calculates elevation changes relative to MSL based on projected changes in relative sea level, subsidence, inorganic sediment accumulation, aboveground and belowground organic matter productivity, compaction, and decay for a representative marsh area. Each cohort provides the mass of inorganic and organic matter accumulated at the surface in a single year as well as any subsequent belowground organic matter productivity (root growth)...
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Coastal zone managers and researchers often require detailed information regarding emergent marsh vegetation types (that is, fresh, intermediate, brackish, and saline) for modeling habitat capacities and needs of marsh dependent taxa (such as waterfowl and alligator). Detailed information on the extent and distribution of emergent marsh vegetation types throughout the northern Gulf of Mexico coast has been historically unavailable. In response, the U.S. Geological Survey, in collaboration with the Gulf Coast Joint Venture, the University of Louisiana at Lafayette, Ducks Unlimited, Inc., and the Texas A&M University-Kingsville, produced a classification of emergent marsh vegetation types from Corpus Christi Bay,...
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This dataset contains four rasters that represents wetland restoration opportunities as well as wetland enhancement opportunities. Potential restoration opportunities are places that are not currently wetlands but have the potential to be restored to wetlands (based on presence of hydric soils or being located within tidal areas). Enhancement opportunities are all places that currently are wetlands. The restoration opportunities were created for both tidal and non-tidal wetlands. For tidal wetland restoration opportunities, the USGS Digital Elevation Model was used to establish the potential boundaries from 2 m above mean sea level to 0 m. For non-tidal wetland opportunities, the boundaries of the Chesapeake...
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This data set contains vector point information. The original data set was collected through Texas A&M University-Kingsville a helicopter survey was flown October 2-3rd of 2011 by Dr. Jenneke Visser (University of Louisiana at Lafayette) and Michael Mitchell. Data from this survey was used to produce this point file. Each feature includes the vegetation type at the point as well as the class used when classifying. Each feature is labeled either reference or accuracy assessment based on what it was used for during analysis. Flight was along north/south transects spaced 2000 meters apart from the Corpus Christi Bay to the Sabine River. Vegetative data was obtained at pre-determined stations spaced at 1500 meters along...
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The Gulf Coastal Plains and Ozarks (GCPO) Landscape Conservation Cooperative (LCC) has conducted an ecological assessment of various landscape characteristics, or endpoints, outlined in the LCC Integrated Science Agenda. This data layer addresses the forested wetland amount desired landscape endpoint for the forested wetland ecosystem in the Mississippi Alluvial Valley subgeography of the GCPO LCC. This data was created by reclassification of the 2011 National Land Cover Dataset (NLCD) to pull out only the woody wetlands class (90) from the NLCD dataset. We then overlaid the HUC12 watershed layer and calculated the total amount of forested wetland acreage within each watershed.
map background search result map search result map NLCD Woody Wetland Acres for the MAV (by HUC 12) MAV NLCD_2011 Woody Wetlands coastal Texas marsh survey points - 2011 Marsh types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama, in 2010 coastal Texas marsh survey points - 2012 Prioritization of Currently Suitable Brood Rearing Habitat for Mottled Ducks in the Western Gulf Coast NWI Emergent Wetlands (MRB) NWI Forested Wetlands (MRB) NWI Historic Wetlands Barcode Value for GCPO LCC Estuarine Tidal Marsh 2010: Delineation of Water Bodies in Emergent Wetlands in Coastal New Jersey Wetland Index of Ecological Integrity, Region-wide, Version 3.2, Northeast U.S. Wetland Restoration and Enhancement, Chesapeake Bay Watershed Bathymetry Digital Elevation Models for Eight Study Areas in Coastal Oregon and Washington, 2012 Digital Elevation Models for eight study areas in coastal Oregon and Washington, 2012 WARMER model projections of sea-level rise for eight tidal marsh study areas on coastal Oregon and Washington, 2010-2110 LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 LEAN-Corrected DEM for Suisun Marsh Blackwater LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 LEAN-Corrected Collier County DEM for wetlands LEAN-Corrected DEM for Suisun Marsh Blackwater LEAN-Corrected Chesapeake Bay Digital Elevation Models, 2019 2010: Delineation of Water Bodies in Emergent Wetlands in Coastal New Jersey coastal Texas marsh survey points - 2011 LEAN-corrected San Francisco Bay Digital Elevation Model, 2018 LEAN-Corrected Collier County DEM for wetlands WARMER model projections of sea-level rise for eight tidal marsh study areas on coastal Oregon and Washington, 2010-2110 Digital Elevation Models for eight study areas in coastal Oregon and Washington, 2012 coastal Texas marsh survey points - 2012 Bathymetry Digital Elevation Models for Eight Study Areas in Coastal Oregon and Washington, 2012 MAV NLCD_2011 Woody Wetlands NLCD Woody Wetland Acres for the MAV (by HUC 12) Prioritization of Currently Suitable Brood Rearing Habitat for Mottled Ducks in the Western Gulf Coast Wetland Restoration and Enhancement, Chesapeake Bay Watershed Marsh types from Corpus Christi Bay, Texas, to Perdido Bay, Alabama, in 2010 NWI Historic Wetlands Barcode Value for GCPO LCC Estuarine Tidal Marsh Wetland Index of Ecological Integrity, Region-wide, Version 3.2, Northeast U.S. NWI Forested Wetlands (MRB) NWI Emergent Wetlands (MRB)