Projected Seafloor Elevation Change and Relative Sea Level Rise Surrounding Maui, Hawaii 25, 50, 75, and 100 Years from 1999

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Frequently anticipated questions:

What does this data set describe?

Title:
Projected Seafloor Elevation Change and Relative Sea Level Rise Surrounding Maui, Hawaii 25, 50, 75, and 100 Years from 1999
Abstract:
The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center conducted research to quantify bathymetric changes surrounding Maui, Hawaii. Changes in seafloor elevation were calculated using historical bathymetric point data from the 1960s (see Yates and others, 2017a) and light detection and ranging (lidar)-derived data acquired in 1999 (NOAA, 2013) using methods outlined in Yate and others (2017b). An elevation change analysis between the 1960s and 1999 data was performed to quantify and map historical impacts to seafloor elevation and to determine elevation-change statistics for 12 habitat types found surrounding Maui. Annual elevation-change rates were calculated for each elevation-change data point. Seafloor elevation-change surrounding Maui was projected 25, 50, 75 and 100 years from 1999 using these historical annual rates of elevation change. Water depth was projected 25, 50, 75 and 100 years from 1999 using historical rates of annual elevation change plus 1999 local sea level rise (SLR) data from the National Oceanic and Atmospheric Administration (NOAA).
Supplemental_Information:
The 1999 lidar dataset was collected by the U.S. Army Core of Engineers (USACE) Scanning Hydrographic Operational Airborne Lidar Survey (SHOALS) system, which consists of an airborne laser transmitter/receiver capable of measuring 400 soundings per second. The system operates from a deHavilland DHC-6 Twin Otter aircraft flying at altitudes between 200 and 400 meters (m) with a ground speed of about 100 knots. The SHOALS airborne system acquires a tremendous volume of raw data during a single mission. The lidar data are unique and require a specialized Data Processing System (DPS) for post-processing. For more information, see the NOAA metadata file available at, https://www.fisheries.noaa.gov/inport/item/49739. Relative sea level trend data were retrieved from the NOAA Tides and Currents portal via Station 1615680 at Kahului, Hawaii (NOAA, 2020).
  1. How might this data set be cited?
    Yates, Kimberly K., and Fehr, Zachery W., 20220321, Projected Seafloor Elevation Change and Relative Sea Level Rise Surrounding Maui, Hawaii 25, 50, 75, and 100 Years from 1999:.

    This is part of the following larger work.

    Yates, Kimberly K., and Fehr, Zachery W., 20220321, Projected Seafloor Elevation Change and Relative Sea Level Rise Surrounding Maui, Hawaii 25, 50, 75, and 100 Years from 1999: U.S. Geological Survey data release doi:10.5066/P9DIYQV4, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -156.729192
    East_Bounding_Coordinate: -155.953513
    North_Bounding_Coordinate: 21.047835
    South_Bounding_Coordinate: 20.557650
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 1961
    Ending_Date: 2099
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: Tabular and vector digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
      This is a Vector data set.
    2. What coordinate system is used to represent geographic features?
      Grid_Coordinate_System_Name: Universal Transverse Mercator
      Universal_Transverse_Mercator:
      UTM_Zone_Number: 4
      Transverse_Mercator:
      Scale_Factor_at_Central_Meridian: 0.9996
      Longitude_of_Central_Meridian: -159.0
      Latitude_of_Projection_Origin: 0.0
      False_Easting: 500000.0
      False_Northing: 0.0
      Planar coordinates are encoded using coordinate pair
      Abscissae (x-coordinates) are specified to the nearest 0.6096
      Ordinates (y-coordinates) are specified to the nearest 0.6096
      Planar coordinates are specified in METERS
      The horizontal datum used is North American Datum of 1983 National Spatial Reference System (2007).
      The ellipsoid used is GRS_1980.
      The semi-major axis of the ellipsoid used is 6378137.0.
      The flattening of the ellipsoid used is 1/298.257222101.
      Vertical_Coordinate_System_Definition:
      Altitude_System_Definition:
      Altitude_Datum_Name: Mean Lower Low Water
      Altitude_Resolution: 0.2
      Altitude_Distance_Units: meters
      Altitude_Encoding_Method:
      Explicit elevation coordinate included with horizontal coordinates
  7. How does the data set describe geographic features?
    Entity_and_Attribute_Overview:
    The detailed attribute descriptions for the elevation change data, projected elevation change analysis, and habitat definitions are provided in the included data dictionaries (DataDictionary_Shapefile_Maui.pdf, DataDictionary_HabitatTypes_Maui.pdf, and DataDictionary_ElevationChangeAnalysis_Maui.pdf). These metadata are not complete without these files.
    Entity_and_Attribute_Detail_Citation:
    The entity and attribute information were generated by the individual and/or agency identified as the originator of the dataset. Please review the rest of the metadata record for additional details and information.

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Kimberly K. Yates
    • Zachery W. Fehr
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Kimberly K. Yates
    Southeast Region: ST. PETE COASTAL & MARINE SC
    Research Oceanographer
    600 4Th Street South
    St. Petersburg, FL
    United States

    727-502-8059 (voice)
    kyates@usgs.gov

Why was the data set created?

These data were used to generate projected elevation-change and water depth values surrounding Maui, Hawaii for twelve habitat types located within the study area.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 2020 (process 1 of 6)
    Step 1: Seafloor elevation and volume change analyses were performed using methods described in Yates and others (2017b). Historical elevation change data were downloaded from the Yates and others (2017a) data release. The Maui_ElevationChange.csv file was downloaded from the data release and imported into ArcMap 10.7 to create a point shapefile named Maui_SeafloorElevationChangePoints.shp. Original column headers in the .csv data were too long for shapefile attribute names, so attributes were either renamed or deleted if not required. The historical sounding elevation data corrected for SLR, 1999 lidar elevation data, longitude, latitude, and hydrographic sheet information attributes were renamed to HistE_SLRc, 1999_elev, POINT_X, POINT_Y, and Survey, respectively. A new attribute was added to this shapefile and named 'Rate' and values were populated in the field by using the Field Calculator and the following expression: Rate = [Diff_m]/(1999-[Year]), where [Diff_m] is the elevation difference between the historical hydrographic data and modern lidar data and [Year] is the attribute value containing the hydrographic survey collection year.
    Date: 2020 (process 2 of 6)
    Step 2: The habitat shapefile used in this analysis was downloaded from NOAA NCCOS Data Collection site (NOAA, 2007). The original shapefile, Maui.shp, was renamed to Maui_Habitat.shp. The habitat type attribute used in this analysis was the [D_STRUCT] attribute, which had the most similar definitions to other US coral reef habitat maps. Further information on the attributes and their definitions can be found in the DataDictionary_HabitatTypes_Maui.pdf file in the Maui_HabitatShapefile.zip download file.
    Date: 2020 (process 3 of 6)
    Step 3: Additional fields were added to the attribute table to represent projected elevations (N_e) based on elevation change rates, projected elevation change (N_e_diff) based on N_e elevations, projected water depth (N_WDepth) after accounting for relative sea level rise (RSLR) and projected elevation change, and relative sea level rise (N_RSLR) based on NOAA SLR rates and projected elevation change rates, where N represents the number of years projected from the collection date of the most recent bathymetry used in the analysis: 25_e, 50_e, 75_e, 100_e, 25_e_diff, 50_e_diff, 75_e_diff, 100_e_diff, 25_WDepth, 50_WDepth, 75_WDepth, 100_WDepth, 25_RSLR, 50_RSLR, 75_RSLR, and 100_RSLR. The Field Calculator was used to populate values for each of these attributes using the following equations: N_e = [1999_elev]+(N*[Rate]), N_e_diff = [N_e]-[1999_elev], N_WDepth = Abs([1999_elev]+(N*[Rate]))+(N*0.00202), and N_RSLR = (N*0.00202)–[N_e_diff]. The shapefile was then exported as Maui_ProjectedElevationChangePoints_25yr_50yr_75yr_and_100yr_from_1999.shp. Further information on the attributes and their definitions can be found in the DataDictionary_Shapefile_Maui.pdf file in the Maui_ProjectedElevationChangePoints_25yr_50yr_75yr_and_100yr_from_1999.zip download file.
    Date: 2020 (process 4 of 6)
    Step 4: A visual inspection of the projected elevation change data and comparison to existing aerial imagery was conducted and erroneous elevation change points were removed using methods of Yates et al., 2017b. Additional points were identified for visual inspection and potential removal using the select features tool and a demarcating Rate value of +/- 0.20 m per year in ArcMap 10.7. Any point that was subaerial at the 100-year water depth projection (100_WDepth) was also selected and removed. These points were assumed to be due to substantial sediment transport events such as landslides and slumps that occur on these dynamic shorelines. Satellite imagery and topographic maps from various time periods were used in determining likely landslide and slump activity at these points.
    Date: 2020 (process 5 of 6)
    Step 5: Elevation change statistics were determined for each habitat type using the XYZ points from the Maui_ProjectedElevationChangePoints_25yr_50yr_75yr_and_100yr_from_1999.shp shapefile. The "Select Layer by Location (Data Management)" tool was used to extract points within or on the boundary of a specific habitat type by using the following parameters: Input Feature Layer: Maui_ProjectedElevationChangePoints_25yr_50yr_75yr_and_100yr_from_1999.shp shapefile; Relationship: INTERSECT; Selecting Features: Maui_Habitat.shp shapefile; Search Distance: left blank; and Selection type: NEW_SELECTION. The Seafloor Elevation Change Analysis Tool (SECAT) was created to automate the process, since these steps had to be repeated for 12 habitat types under 5 different scenarios: one between historical hydrographic data and contemporary lidar data (diff_m), and one for each N_e_diff attribute. Elevation change statistics were compiled by habitat type into the following comma-separated values (CSV) files: Maui_Historical.csv, Maui_25e.csv, Maui_50e.csv, Maui_75e.csv, and Maui_100e.csv. Entries that do not have a large enough sample size to compute statistics display "N/A" in the associated cell. These statistics can be found in Maui_ProjectedSECAT.zip. For more information on SECAT and its capabilities see Zieg and Zawada (2021). Further information on the attributes and their definitions can be found in the DataDictionary_HabitatTypes_Maui.pdf and DataDictionary_ElevationChangeAnalysis_Maui.pdf files in the Maui_ProjectedSECAT.zip download file.
    Date: 2020 (process 6 of 6)
    Step 6: Maps were rendered for each projected change attribute calculated in Step 3. Maps appended in ‘N_e_diff' depict projected elevation change at each point N years into the future. Projected RSLR maps that consider projected elevation change analyses were developed using separate symbology palettes and were appended ‘N_RSLR’. All maps are available within the Maui_ProjectionMaps.zip download file.
  3. What similar or related data should the user be aware of?
    Yates, Kimberly K., Zawada, David G., Smiley, Nathan A., Tiling-Range, Ginger, and Resnick, Jessica P., 20170308, Seafloor elevation change in Maui, St. Croix, St. Thomas, and the Florida Keys: U.S. Geological Survey data release doi:10.5066/F7WQ01W0, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

    Online Links:

    Other_Citation_Details: 2017a
    Yates, Kimberly K., Zawada, David G., Smiley, Nathan A., and Tiling-Range, Ginger, 20170420, Divergence of seafloor elevation and sea level rise in coral reef ecosystems: Biogeosciences, Munich, Germany.

    Online Links:

    Other_Citation_Details: 2017b
    NOAA Office for Coastal Management (OCM), 20130301, 1999 USACE bathymetric LiDAR: Hawaiian Islands: NOAA, Charleston, South Carolina.

    Online Links:

    United States Army Corps of Engineers (USACE), 20131130, EM-1110-2-1003 hydrographic surveying: Department of the Army, Washington, District of Columbia.

    Online Links:

    Zieg, Jonathan A., and Zawada, David G., 20210211, Seafloor elevation change analysis tool: U. S. Geological Survey, St. Petersburg, Florida.

    Online Links:

    NOAA Tides & Currents, 20200801, Kahului, Kahului Harbor, Hawaii - station ID: 1615680: NOAA, Washington, District of Columbia.

    Online Links:

    NOAA National Centers for Coastal Ocean Science (NCCOS), 20070705, Benthic Habitat Shapefiles Data: NOAA, Silver Spring, Maryland.

    Online Links:

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    Digital elevation maps were visually inspected by cross-checking them with other contemporary, overlapping datasets such as satellite and airborne imagery and/or other digital elevation maps in Esri ArcGIS for identification of anomalous elevations or data inconsistencies.
  2. How accurate are the geographic locations?
    The horizontal accuracy of the data is better than plus or minus 3.0 meters (1 standard deviation). SHOALS has demonstrated capabilities that meet USACE Hydrographic Survey accuracy requirements for Class 1 surveys and the International Hydrographic Organization nautical charting standards for Order 1. For more information, see USACE (2013).
  3. How accurate are the heights or depths?
    The vertical accuracy is better than plus or minus 0.15 centimeters (cm), collected to meet value (meters) at 1 standard deviation. SHOALS has demonstrated capabilities that meet US Army Corps of Engineers Hydrographic Survey accuracy requirements for Class 1 surveys and the International Hydrographic Organization nautical charting standards for Order 1. For more information, see USACE (2013).
  4. Where are the gaps in the data? What is missing?
    This dataset is considered complete for the information presented, as described in the abstract section. Users are advised to read the rest of the metadata record and Yates and others (2017b) for additional details.
  5. How consistent are the relationships among the observations, including topology?
    Data cover the area specified for this project, without any known issues.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints None
Use_Constraints Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. The U.S. Geological Survey requests to be acknowledged as originator of these data in future products or derivative research.
  1. Who distributes the data set? (Distributor 1 of 1)
    Kimberly K. Yates
    Southeast Region: ST. PETE COASTAL & MARINE SC
    Research Oceanographer
    600 4Th Street South
    St. Petersburg, FL
    United States

    727-502-8059 (voice)
    kyates@usgs.gov
  2. What's the catalog number I need to order this data set?
  3. What legal disclaimers am I supposed to read?
    Although these data have been processed successfully on a computer system at the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display 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. The USGS shall not be held liable for improper or incorrect use of the data described or contained herein. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 21-Mar-2022
Metadata author:
Kimberly K. Yates
Southeast Region: ST. PETE COASTAL & MARINE SC
Research Oceanographer
600 4th Street South
St. Petersburg, FL
United States

727-502-8059 (voice)
kyates@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/Maui_Projected_Elevation_Change_25yr_50yr_75yr_and_100yr_from_1999.faq.html>
Generated by mp version 2.9.51 on Mon Mar 21 17:08:25 2022