This data release includes 2022 data for the Louisiana Outer Coast Restoration Project for Whiskey Island. Specifically, this data release includes a detailed habitat map, general habitat map, and georeferenced imagery. These habitat maps are developed using the methods and classification scheme from Louisiana Coastal Protection and Restoration Authority’s (CPRA) Barrier Island Comprehensive Monitoring (BICM) program. For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (that is, dataset and recommended symbology). For more information about BICM habitat mapping, see Enwright and others (2020). Enwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program—Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16: U.S. Geological Survey Open-File Report 2020–1030, 57 p., https://doi.org/10.3133/ofr20201030.

Coastwide vegetation surveys have been conducted multiple times over the past 50 years (e.g., Chabreck and Linscombe 1968, 1978, 1988, 1997, 2001, and 2013) by the Louisiana Department of Wildlife and Fisheries (LDWF) in support of coastal management activities. The last survey was conducted in 2013 and was funded by the Louisiana Coastal Protection and Restoration Authority (CPRA) and the U.S. Geological Survey (USGS) as a part of the Coastal Wetlands Planning, Protection, and Restoration Act (CWPPRA) monitoring program. These surveys provide important data that have been utilized by federal, state, and local resource managers. The surveys provide information on the condition of Louisiana’s coastal marshes by mapping plant species composition and vegetation change through time. During the summer of 2021, the U.S. Geological Survey, Louisiana State University, and the Louisiana Department of Wildlife and Fisheries jointly completed a helicopter survey to collect data on 2021 vegetation types using the same field methodology at previously sampled data points. Plant species were identified and their abundance classified at each point. Based on species composition and abundance, each marsh sampling station was assigned a marsh type: fresh, intermediate, brackish, or saline marsh. The field point data were interpolated to classify marsh vegetation into polygons and map the distribution of vegetation types. We then used the 2021 polygons with additional remote sensing data to create the final raster dataset. We used the polygon marsh type zones (available in this data release), as well as National Land Cover Database (NLCD; https://www.usgs.gov/centers/eros/science/national-land-cover-database) and NOAA Coastal Change Analysis Program (CCAP; https://coast.noaa.gov/digitalcoast/data/ccapregional.html) datasets to create a composite raster dataset. The composite raster was created to provide more detail, particularly with regard to “Other”, “Swamp”, and “Water” categories, than is available in the polygon dataset. The overall boundary of the raster product was extended beyond past surveys to better inform swamp, water, and other boundaries across the coast. A majority of NLCD and CCAP classification during a 2010-2019 period was used, rather than creating a raster classification specific to 2021, as there was a desire to use published datasets. Users are cautioned that the raster dataset is generalized but more specific than the polygon dataset. This data release includes 3 datasets: the point field data collected by the helicopter survey team, the polygon data developed from the point data, and the raster data developed from the polygon data plus additional remote sensing data as described above.

This boundary was originally developed by the Louisiana Department of Natural Resources (DNR) and was downloaded from this site: http://www.dnr.louisiana.gov/index.cfm?md=pagebuilder&tmp=home&pid=928An ETL process was used to value-add to the feature.

These data provide an accurate high-resolution shoreline compiled from imagery of PORT OF SOUTH LOUISIANA, LA . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attribution scheme 'Coastal Cartographic Object At...

This data release includes 2022 data for the Louisiana Outer Coast Restoration Project for Chenier Ronquille. Specifically, this data release includes a detailed habitat map, general habitat map, and georeferenced imagery. These habitat maps are developed using the methods and classification scheme from Louisiana Coastal Protection and Restoration Authority’s (CPRA) Barrier Island Comprehensive Monitoring (BICM) program. For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (that is, dataset and recommended symbology). For more information about BICM habitat mapping, see Enwright and others (2020). Enwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program—Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16: U.S. Geological Survey Open-File Report 2020–1030, 57 p., https://doi.org/10.3133/ofr20201030.

This data release includes 2022 data for the Louisiana Outer Coast Restoration Project for North Breton Island. Specifically, this data release includes a detailed habitat map, general habitat map, georeferenced imagery, and a bare-earth digital elevation model (DEM) developed from light detection and ranging data. These habitat maps are developed using the methods and classification scheme from Louisiana Coastal Protection and Restoration Authority’s (CPRA) Barrier Island Comprehensive Monitoring (BICM) program. For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (that is, dataset and recommended symbology). For more information about BICM habitat mapping, see Enwright and others (2020).

Breton Island, Louisiana Baseline (Geographic, NAD83) consists of vector line data that were input into the Digital Shoreline Analysis System (DSAS) version 4.0, which is computer software used to compute rate of change statistics. A baseline was acquired from the Barrier Island Comprehensive Monitoring Program (BICM) 2009 report (http://lacoast.gov/reports/project/3890772~1.pdf). The baseline included in the BICM report covered the entire Louisiana coastline, so the baseline representing Breton Island had to be clipped then exported to a new shapefile named Breton_Baseline.shp. The position relative to Breton Island was determined to be the best possible baseline to use for the study. The baseline file was used to create the transect files, which are required by the DSAS program to calculate rate of change statistics.

This dataset corresponds to the annual total land change over coastal Louisiana, from 1988 to 2018. The data is derived from Lansat classification performed by NASA’s Delta-X project. Details on Delta-X can be found in https://deltax.jpl.nasa.gov

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Jensen, D. J., Cavanaugh, K. C., Thompson, D. R., Fagherazzi, S., Cortese, L., & Simard, M. (2022). Leveraging the Historical Landsat Catalog for a Remote Sensing Model of Wetland Accretion in Coastal Louisiana. Journal of Geophysical Research: Biogeosciences, 127(6). https://doi.org/10.1029/2022JG006794

This is a component of the Story Map: In Harm’s Way: Hurricane Ida’s Impact on Socially Vulnerable Communities.Land loss data (1932-2010) was acquired from the U.S. Geological Survey, National Wetlands Research Center, Scientific Investigations Map 3164. Projected future land loss data comes from the Louisiana Coastal Protection and Restoration Authority (CPRA) from 2017 Coastal Master Plans land change (Medium Scenario, 50 Year Projection, Future Without Action).Unofficial 2021 Hurricane Ida observations and track lines were acquired from the NOAA National Hurricane Center.

Moss Distribution and Habitat dataset current as of 2001. To update the Louisiana Coastal Marsh Vegetative Type Map of 1997, 1988, 1978, 1968 and 1949..

This data set contains vector lines representing the shoreline and coastal habitats of Louisiana classified according to the Environmental Sensitivity Index (ESI) classification system. This data set comprises a portion of the ESI for Louisiana. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three...

1922 Digitized Shoreline for Breton Island, Louisiana (Geographic, NAD83) consists of vector shoreline data that were derived from a set of National Ocean Service (NOS) raster shoreline maps (often called T-sheet or TP-sheet maps) created for Breton Island in 1922. In 2002, NOAA published digitized shorelines for T-sheet (T-3920), which were subsequently edited by USGS staff for input into the Digital Shoreline Analysis System (DSAS) Version 4.0, where area and shoreline change analyses could be conducted.

This data release includes 2022 data for the Louisiana Outer Coast Restoration Project for Shell Island. Specifically, this data release includes a detailed habitat map, general habitat map, and georeferenced imagery. These habitat maps are developed using the methods and classification scheme from Louisiana Coastal Protection and Restoration Authority’s (CPRA) Barrier Island Comprehensive Monitoring (BICM) program. For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (that is, dataset and recommended symbology). For more information about BICM habitat mapping, see Enwright and others (2020). Enwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program—Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015–16: U.S. Geological Survey Open-File Report 2020–1030, 57 p., https://doi.org/10.3133/ofr20201030.

This is a polygon dataset representing the extent of the LDNR regulatory area defined as the Louisiana Coastal Zone. This area comprises a band across the southern border of the state and ranges in width from approximately 30 miles at the west edge of the state to over 150 miles at the eastern and Mississippi River Delta areas of the state. A project to digitize the Coastal Zone boundary from the 7.5' quad maps was undertaken in June of 1997. This project was not only the creation of a digital line marking the boundary from digital maps, but also a thorough research project into where the line is actually located based upon records from legislative acts, the Louisiana Coastal Resources Program Final Environmental Impact Statement, and other information gathered from the files of the Coastal Management Division, the State Land Office and maps from the Office of Minerals Resources. This dataset is a product of that project. The data set Point of Contact has a file with copies of literature and references cited in this report.

The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products inventory coastal intertidal areas, wetlands, and adjacent uplands with the goal of monitoring changes in these habitats through time. The timeframe for this metadata is summer 2016. These maps are developed utilizing high resolution a...

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: https://coast.noaa.gov/slr. This metadata record describes the Louisiana Lake Pontchartrain digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available lidar known to exist at the time of DEM creation that met project specifications. This DEM includes data for Ascension, East Baton Rouge, Iberville, Jefferson, Livingston, Orleans, St. Charles, St. James, St. John the Baptist, St. Tammany, Tangipahoa, and West Feliciana Parishes. The DEM was produced from the following lidar data sets: 1. 2017 Upper Delta Plain LA Lidar 2. 2006 LA Statewide Lidar The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88, Geoid12B) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

These data were automated to provide an accurate high-resolution historical shoreline of Breton Island, Louisiana suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS...

description: The dataset includes Land Use/Land Cover types throughout the Chenier Eco-Region in Southwest Louisiana. Using the 2015 NAIP dataset (1m) as the basemap, E-Cognition image objects were derived from the multiresolution segmentation algorithm at 75 and 250 segments. Attempts to refine the data training methods using E-cognition, to extrapolate automating categories of this information to the entire map resulted with exceedingly low accuracy. Therefore, a raster was produced by piecing together several data resources, which provide reliable data for specific LULC categories. This process involved stitching together more reliable sources for specific categories to apply to higher resolution (75) segmentation product. Reference datasets include; 12,000 aerial points assigned to image objects derived from 75 segmentation settings (previously used to develop scripts for data training), mask created from NWI 2008 including water, wetland forested, upland forested and scrub/shrub categories, BOEM marsh classes, NLCD urban areas, and CDL data. The raster produced from this process was applied to the vector image objects derived from the 250 segmentation settings, using a majority filter (greater than 50 percent). The series of draft shapefiles were manually edited and merged, resulting in the final dataset.; abstract: The dataset includes Land Use/Land Cover types throughout the Chenier Eco-Region in Southwest Louisiana. Using the 2015 NAIP dataset (1m) as the basemap, E-Cognition image objects were derived from the multiresolution segmentation algorithm at 75 and 250 segments. Attempts to refine the data training methods using E-cognition, to extrapolate automating categories of this information to the entire map resulted with exceedingly low accuracy. Therefore, a raster was produced by piecing together several data resources, which provide reliable data for specific LULC categories. This process involved stitching together more reliable sources for specific categories to apply to higher resolution (75) segmentation product. Reference datasets include; 12,000 aerial points assigned to image objects derived from 75 segmentation settings (previously used to develop scripts for data training), mask created from NWI 2008 including water, wetland forested, upland forested and scrub/shrub categories, BOEM marsh classes, NLCD urban areas, and CDL data. The raster produced from this process was applied to the vector image objects derived from the 250 segmentation settings, using a majority filter (greater than 50 percent). The series of draft shapefiles were manually edited and merged, resulting in the final dataset.

There are three main components to the Environmental Sensitivity Index (ESI): shoreline habitats, sensitive biological resources, and human-use resources. The shoreline and intertidal areas are ranked based on sensitivity determined by: (1) Shoreline type (substrate, grain size, tidal elevation, origin)(2) Exposure to wave and tidal energy(3) Biological productivity and sensitivity(4) Ease of cleanup. The biology layers focus on threatened/endangered species, areas of high concentration, and areas where sensitive life stages may occur. Supporting data tables provide species/location-specific abundance, seasonality, status, life history, and source information human use resources mapped include managed areas (parks, refuges, critical habitats, etc) and resources that may be impacted by oiling and/or clean-up, such as beaches, archaeological sites marinas etc. ESI's are available for the majority of the US coastline, as well as the US territories. ESI data are available in GIS formats as well as PDF maps. For more information or to download complete ESI data sets go to: https://response.restoration.noaa.gov/esiFor the full metadata record please go to: https://www.fisheries.noaa.gov/inport/item/40883For online ESI query tools, see the Environmental Response Management Application (ERMA): https://response.restoration.noaa.gov/resources/maps-and-spatial-data/environmental-response-management-application-erma