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.
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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
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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 int ...
The dataset presented here represents a circa 1932 land/water delineation of coastal Louisiana used in part of a larger study to quantify landscape changes from 1932 to 2016. The original dataset was created by Dunbar, and Britsch, and Kemp (2006). The original dataset is citable as: Dunbar, J. B. and Britsch, L. D., 2006. Land Loss in Coastal Louisiana 1932-2001. Map 1. Engineer Research and Development Center, Vicksburg, MS, Technical Report, ERDC/GSL TR-05-13, Land Loss Map 1 through 7. The USGS Wetland and Aquatic Research Center altered the original data by improving the geo-rectification in specific areas known to contain geo-rectification error, most notably in coastal wetland areas in the vicinity of Four League Bay in western Terrebonne Basin. The dataset contains two categories, land and water. For the purposes of this effort, land includes areas characterized by emergent vegetation, upland, wetland forest, or scrub-shrub were classified as land, while open water, aquatic beds, and mudflats were classified as water. For additional information regarding this dataset (other than geo-rectification revisions), please contact the dataset originator, the U.S. Army Corps of Engineers (USACE).
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 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.
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).
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...
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 data release includes 2017 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.
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.
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..
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...
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 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.
This data set contains sensitive biological resource data for coastal habitats in Louisiana. Vector polygons represent various habitats, including marsh types, other wetlands, and seagrasses. Species-specific abundance, seasonality, status, life history, and source information are stored in relational data tables (described below) designed to be used in conjunction with this spatial data layer...
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...
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This product is a satellite-based habitat map time series from 2012 to 2020 for the Whiskey Island reach of the Louisiana Gulf shoreline to facilitate monitoring of the Natural Resource Damage Assessment (NRDA) Caillou Lake Headlands project area (TE-0100), also known as Whiskey Island. The project created 170 acres of marsh habitat and 917 acres of dune and beach habitat on Whiskey Island in Terrebonne Parish, Louisiana, using material dredged from Ship Shoal. For more information on this restoration project, see the project page on Louisiana Coastal Protection and Restoration Authority’s (CPRA) Coastal Information Management System (https://cims.coastal.la.gov/outreach/projects/ProjectView?projID=TE-0100). The time period for these maps spans before, during, and after the restoration project. Maps were produced using a random forest model that classified cover types (that is, bare, herbaceous vegetation, woody vegetation, and water) based on spectral indices from Sentinel-2 and ...
This product is a satellite-based habitat map time series from 2012 to 2019 for the Caminada Headland reach of the Louisiana Gulf shoreline to facilitate monitoring of the National Fish and Wildlife Foundation (NFWF) Caminada Headland Beach and Dune Restoration Incr2 project area (BA-0143). The project restored 489 acres of beach and dune habitat along more than seven miles of Caminada Headland in Jefferson and Lafourche Parishes in Louisiana through the direct placement of about 5.4 million cubic yards of sandy substrate from Ship Shoal. For more information on this restoration project, see the project page on Louisiana Coastal Protection and Restoration Authority’s (CPRA) Coastal Information Management System (https://cims.coastal.la.gov/outreach/projects/ProjectView?projID=BA-0143). The time period for these maps spans before, during, and after the restoration project. These maps were produced using a random forest model that classified cover types (that is, bare, herbaceous vegetation, woody vegetation, and water) based on spectral indices from Sentinel-2 and Landsat 8 imagery. These products complement habitat maps that were developed from orthoimagery and elevation data using a detailed 15-class habitat scheme developed by the CPRA’s Barrier Island Comprehensive Monitoring (BICM) Program. The BICM Program uses both historical data and contemporary data collections to assess and monitor changes to barrier islands. Habitat map products are one type of BICM dataset. For more information about the BICM Program, see Kindinger and others (2013); for more information about recent BICM habitat mapping, see Enwright and others (2020). These habitat maps were utilized with ecological data in an analysis of avian habitat occupancy and use/function for several focal species pre- and post-restoration activity. The results of this analysis will help land managers evaluate how restoration and subsequent natural ecological processes impact bird species of conservation concern, and target restoration activities that enhance island sustainability and preserve avian habitat availability.
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.