U.S. Geological Survey, Wetland and Aquatic Research Center Beck, Holly J. Couvillion, Brady Dugas, Jason Garber, Adrienne Mouton, Kelly 20210820 raster digital data Lafayette, LA U.S. Geological Survey, Wetland and Aquatic Research Center https://doi.org/10.5066/P9AZOHQU Coastal Protection and Restoration Authority of Louisiana U.S. Department of Commerce, National Oceanic Atmospheric Administration U.S. Department of Agriculture, Natural Resources Conservation Service U.S. Department of Interior, U.S. Fish and Wildlife Service U.S. Department of the Army, Corp of Engineers U.S. Environmental Protection Agency 2021 document http://www.lacoast.gov Wetland restoration efforts conducted by the Coastal Wetlands Planning, Protection and Restoration Act (CWPPRA) in Louisiana rely on monitoring efforts to determine the efficacy of these efforts. The Coastwide Reference Monitoring System (CRMS) was developed to assist in a multiple-reference approach that uses aspects of hydrogeomorphic functional assessments and probabilistic sampling for monitoring. The CRMS program includes a suite of approximately 398 sites that encompass the range of hydrological and ecological conditions for each stratum. As part of CRMS, land and water classifications are created from Digital Orthophoto Quarter Quadrangles (DOQQs) approximately every three years at all CRMS sites. A DOQQ is a raster image in which displacement in the image caused by sensor orientation and terrain relief has been removed and combines the image characteristics of a photo with geometric qualities of a map. The DOQQs generated for this project consist of 2018 Color Infrared (CIR) Digital Imagery. These images were classified into land and water categories using a threshold of the near infrared (NIR) band, followed by supervised and unsupervised classification. Initial classification results are then reviewed by multiple image analysts to identify and manually recode errors. The final land-water classifications are intended to serve as both geographic and quantitative assessments of landscape composition on the date of acquisition. Four previous assessments have been conducted (2005, 2008, 2012, and 2015/2016). Once the program creates enough data points for statistical analyses, these data will be used for land area change rate calculation. The intended use of this data set is to provide information to aid efforts in the conservation, restoration, creation, and enhancement of Louisiana's coastal wetlands. The land-water data is used to measure the occurrence, locations, and rates of land loss/land gain for CRMS Site 0583. Author ORCIDs: Beck, H.J.(0000-0002-0567-9329); Couvillion, B.(0000-0001-5323-1687); Dugas, J.(0000-0001-6094-7560);Garber, A.(0000-0003-1139-8256);Mouton, K.(0000-0002-7692-8206) 20181027 publication date Complete None planned 29.843480652800505 29.834449304479516 -92.92198652165966 -92.91163201642942 ISO 19115 Topic Category imageryBaseMapsEarthCover None CRMS DOQQ land-water wetland mapping restoration marsh protection coastal cartography Geographic Information System Marine Realms Information Bank (MRIB) keywords alteration of wetland habitats wetland wetland restoration Coastal and Marine Ecological Classification Standard Emergent Wetland Forested Wetland Scrub-Shrub Wetland USGS Thesaurus wetland ecosystems USGS Metadata Identifier USGS:611d2c73d34e40dd9c012a28 None Louisiana Geographic Names Information System State of Louisiana coastal Louisiana It is strongly recommended that these data are directly acquired from the U.S. Geological Survey, Wetland and Aquatic Research Center and not indirectly through other sources which may have changed in some way. The distributor makes no claim as to the data's suitability for other purposes. Acknowledgement of the U.S. Geological Survey (USGS), Wetland and Aquatic Research Center (WARC) as a data source would be appreciated in products developed from these data. Such acknowledgement as is standard for citation and legal practices for data sources is expected by users of this data. Sharing new data layers developed directly from these data would be appreciated by the USGS WARC staff. Users should be aware that comparison with other datasets for the same area from other time periods may be inaccurate because of inconsistencies resulting from changes in mapping conventions, data collection procedures, and computer processes over time. The distributor shall not be liable for improper or incorrect use of these data, based on the description of appropriate/inappropriate uses described in this metadata document. These data are not legal documents and are not to be used as such. U.S. Geological Survey, Wetland and Aquatic Research Center Holly J. Beck Geographer mailing

7920 NW 71st Street

Gainesville FL 32653 USA 352-264-3496 hbeck@usgs.gov The U.S. Geological Survey (USGS) Wetland and Aquatic Research Center (WARC) would like to acknowledge the assistance of the Coastal Protection and Restoration Authority of Louisiana, U.S. Department of Commerce, U.S. Department of Agriculture, U.S. Department of the Interior, U.S. Department of the Army, and the U.S. Environmental Protection Agency. Environment as of Metadata Creation: Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.3.1 (Build 4959) Service Pack N/A (Build N/A) Hexagon Geospatial 20180301 Version: 16.5 (v16.5.0.852) Software Previous examinations have investigated the accuracy of these datasets and the methodology used to produce them in detail. Further information regarding those previous accuracy assessments is available in the metadata of the datasets available at the following location: Couvillion, B.R., Beck, H.J., Dugas, J., Garber, A., and Mouton, K., 2018, Coastwide Reference Monitoring System (CRMS) 2015 land-water classifications: U.S. Geological Survey data release, https://doi.org/10.5066/F7930RDX. Couvillion, B.R., Beck, H.J., Dugas, J., Garber, A., and Mouton, K., 2018, Coastwide Reference Monitoring System (CRMS) 2016 land-water classifications: U.S. Geological Survey data release, https://doi.org/10.5066/P90RE64M. The same methodology used to produce the 2015 and 2016 datasets mentioned above were used in this analysis and as such, the accuracy assessment investigation for those analyses is informative to this effort as well. Those previous investigations determined a simple overall accuracy of 96.49% for these datasets, however when point selection bias and landscape composition were accounted for, an adjusted accuracy for the overall dataset of 98.88% was attained. This overall accuracy is representative of the methodology used to create the data set as a whole. In other words, it is indicative of average values of all CRMS sites, not necessarily specific CRMS sites. Specific CRMS sites may have accuracies less than or greater than this overall value. In general, the more dis-aggregated a landscape, and the more aquatic vegetation it contains, the higher the probability of error, and consequently the lower the accuracy of land cover classifications will be in that location. All land-water classification data has gone through several iterations of quality assurance/quality control to ensure quality. The initial, largely automated, classification results are reviewed by multiple image analysts to identify and manually recode errors. The QAQC efforts ensure error-prone classes such as floating aquatic vegetation (FAV), shadows, and vegetative overhang are recoded to their appropriate category. This data represents the landscape composition on the date of acquisition (DOA) of the imagery. Land area in this highly dynamic environment is a very fluid parameter, and normal environmental variability can lead to variability in this measure from day to day. The accuracy of the horizontal positions is based on the accuracy of the georeferenced data source (2018 DOQQ). The sources used vary from project to project. All USGS Mapping products adhere to the National Mapping Accuracy Standard. A formal accuracy assessment of the vertical positional information in the data set has either not been conducted, or is not applicable. Digital Aerial Solutions LLC 20190420 remote-sensing image http://nationalmap.gov Digital and/or Hardcopy 20181027 20190105 Date of source photography 2018 DOQQ Aerial, color-infrared (CIR) imagery collected in the fall and winter of 2018 which served as the primary data source for classification of land-water data. Preprocessing-Imagery Clips: All of the 2018 aerial images were clipped to the 1 km CRMS site boundaries to remove as much of the surrounding environment as possible. This is done to remove areas which are not part of the classification analysis and accompanying sources of noise or complexity contained within those areas. This lessens the chance of the classifier incorporating confusing patterns introduced by non-interest areas of the image. 2020 Holly J Beck U.S. Geological Survey, Southeast Region Geographer mailing address

7920 NW 71St Street

Gainesville FL 32653 US 352-264-3496 352-378-4956 hbeck@usgs.gov Preprocessing-NIR threshold: DOQQ imagery was remarkably well color-balanced and the NIR band in particular was consistent throughout the images. The NIR wavelengths are particularly useful for discriminating land and water categories. As such, the first step in land/water classification was to determine a threshold of NIR values above which pixels were generally land and below which pixels were generally water. This initial dichotomous split between categories enables separate supervised classifications to be run on the two different portions of the imagery. In doing so, incorrectly classified pixels stick out more in the next step. 2018 DOQQ 2020 Holly J Beck U.S. Geological Survey, Southeast Region Geographer mailing address

7920 NW 71St Street

Gainesville FL 32653 US 352-264-3496 352-378-4956 hbeck@usgs.gov Unsupervised Classification: Each separate portion of the imagery from the above step was sent through an unsupervised classification (Erdas 2018) with 254 classes, 0.95 convergence threshold, and 20 maximum iterations. The resulting isodata signatures were examined by skilled image analysts and error candidate categories were investigated in depth. If a category was determined to be in error at this stage in the processing, it was flagged and recoded to the opposite category. 2020 Holly J Beck U.S. Geological Survey, Southeast Region Geographer mailing address

7920 NW 71St Street

Gainesville FL 32653 US 352-264-3496 352-378-4956 hbeck@usgs.gov Supervised Classification: Signatures from known error-prone classes such as floating aquatic vegetation were used in supervised classification (Erdas 2018) to further identify these troublesome areas. Pixels identified in this classification were examined for accuracy, and those classes determined to represent FAV were recoded to water. 2020 Holly J Beck U.S. Geological Survey, Southeast Region Geographer mailing address

7920 NW 71St Street

Gainesville FL 32653 US 352-264-3496 352-378-4956 hbeck@usgs.gov Draft land-water dataset compilation: The draft land-water classification was compiled by recoding changes from the previous two steps and creating one compiled land-water classification. A clump and sieve, using 8 connected neighbors was run to eliminate features less than the Minimum Mapping Unit of 4 square meters. Features of less than 4 square meters were recoded to the opposite land cover category and are therefore not represented in this dataset. 2020 Holly J Beck U.S. Geological Survey, Southeast Region Geographer mailing address

7920 NW 71St Street

Gainesville FL 32653 US 352-264-3496 352-378-4956 hbeck@usgs.gov Data Improvements: The draft land-water classification was further edited to ensure accuracy. Experienced image analysts, meticulously analyzed the initial classification created in the previous steps, and edited the classification as needed. When errors were identified the analyst would digitize the extent of the error and attribute the resulting polygon with the correct raster value. 2020 Holly J Beck U.S. Geological Survey, Southeast Region Geographer mailing address

7920 NW 71St Street

Gainesville FL 32653 US 352-264-3496 352-378-4956 hbeck@usgs.gov Final Dataset Compilation: The errors digitized in the previous step were rasterized and sent through a model to correct the value in the draft land-water classification to the analyst-identified correct value. The output of this model constituted the final QAQC’d land/water classification. 2020 Holly J Beck U.S. Geological Survey, Southeast Region Geographer mailing address

7920 NW 71St Street

Gainesville FL 32653 US 352-264-3496 352-378-4956 hbeck@usgs.gov This dataset was then QAQC’d further by additional image interpreters not involved in the classification process. Any errors identified by these reviewers were recoded following the same methodology outlined in the previous two steps. 2020 Holly J Beck U.S. Geological Survey, Southeast Region Geographer mailing address

7920 NW 71St Street

Gainesville FL 32653 US 352-264-3496 352-378-4956 hbeck@usgs.gov Coastal Louisiana Raster Grid Cell 1000 1001 Universal Transverse Mercator 15 0.999600 -93.000000 0.000000 500000.000000 0.000000 coordinate pair 0.000008 0.000008 meters North American Datum of 1983 Geodetic Reference System 80 6378137.000000 298.257222 CRMS_LW_2018_CRMS0583.TIF Attribute table for raster dataset Producer defined OID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Value Data identifier created by spatial software ESRI 1 2 Count Number of pixels in that class Producer defined 119731.0 880269.0 Number of pixels in that class Red Red value in the RGB set of the color which represents this class Producer defined 0 210 Green Green value in the RGB set of the color which represents this class Producer defined 0 180 Blue Blue value in the RGB set of the color which represents this class Producer defined 140 255 Opacity Transparency Producer defined 255 255 Transparency All areas characterized as emergent vegetation, wetland forest, scrub-shrub, or uplands are classified as land, while open water aquatics, and mud flats are classified as water. Items within the attribute table in addition to ArcInfo items (e.g., area. perimeter) include: 1) Class- classified as either land or water, 2) Acres- acreage figures Producer defined U.S. Geological Survey - ScienceBase mailing and physical

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 USA 1-888-275-8747 sciencebase@usgs.gov Downloadable data Although these data have been processed successfully on a computer system at the U.S. Geological Survey, Wetland and Aquatic Research Center, no warranty expressed or implied is made regarding the accuracy or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This disclaimer applies both to individual use of the data and aggregate use with other data. It is strongly recommended that these data are directly acquired from a U.S. Geological Survey server, and not indirectly through other sources which may have changed the data in some way. It is also strongly recommended that careful attention be paid to the contents of the metadata file associated with these data. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and/or contained herein. Digital Data https://doi.org/10.5066/P9AZOHQU None None 20220908 U.S. Geological Survey, Wetland and Aquatic Research Center Holly Beck Geographer mailing and physical address

7920 NW 71st Street

Gainesville FL 32653 USA 352-264-3496 hbeck@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998 local time None Acknowledgement of the U.S. Geological Survey, Wetland and Aquatic Research Center as the metadata source would be appreciated. Please cite the original metadata when using portions of the record when creating a similar record for slightly altered data for reprojection or subsetting. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. http://www.esri.com/metadata/esriprof80.html ESRI Metadata Profile