Attribute_Accuracy_Report:
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.
Data cover the area specified for this project, without any known issues.
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.
Process_Step:
Process_Description:
Step 1: Seafloor elevation 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 STT_ElevationChange.csv file was downloaded from Yates and others (2017a) data release and imported into ArcMap 10.7 to create a point shapefile named STT_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 sea level rise, 2014 lidar elevation data, longitude, latitude, and hydrographic sheet information attributes were renamed to HistE_SLRc, 2014_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]/(2014-[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.
Process_Date: 2020
Process_Step:
Process_Description:
Step 2: The habitat shapefile used in this analysis was downloaded from NOAA's National Centers for Coastal Ocean Science Data Collection site (NOAA, 2002). The original shapefile, stjt_fin.shp, was renamed to STT_Habitat.shp. The elevation-change dataset extended beyond the bounds of the available habitat data. An additional polygon was incorporated into the shapefile during an edit session to account for this discrepancy. The additional polygon was given the 'Unclassified' habitat class in the 'TYPE' attribute field. The 'TYPE' attribute was used in this analysis, which had the most similar definition to other US coral reef habitat maps. The habitat shapefile was then exported as STT_Habitat_UnclassifiedAdded.shp. Further information on the attributes and their definitions can be found in the DataDictionary_HabitatTypes_STT.pdf file in the STT_HabitatShapefile.zip download file.
Process_Date: 2020
Process_Step:
Process_Description:
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 RSLR and projected elevation change, and relative sea level rise (N_RSLR) based on NOAA's 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 = [2014_elev]+(N*[Rate]), N_e_diff = [N_e]-[2014_elev], N_WDepth = Abs([2014_elev]+(N*[Rate]))+(N*0.00177), and N_RSLR = (N*0.00177)–[N_e_diff]. The shapefile was then exported as STT_ProjectedElevationChangePoints_25yr_50yr_75yr_and_100yr_from_2014.shp. Further information on the attributes and their definitions can be found in the DataDictionary_Shapefile_STT.pdf file in the STT_ProjectedElevationChangePoints_25yr_50yr_75yr_and_100yr_from_2014.zip download file.
Process_Date: 2020
Process_Step:
Process_Description:
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.
Process_Date: 2020
Process_Step:
Process_Description:
Step 5: Elevation change statistics were determined for each habitat type using the XYZ points from the STT_Projected_Elevation_Change_25yr_50yr_75yr_and_100yr_from_2014.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: STT_ProjectedElevationChangePoints.shp shapefile; Relationship: INTERSECT; Selecting Features: STT_Habitat_UnclassifiedAdded.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 18 habitat types under 5 different scenarios: one between historical hydrographic data and contemporary lidar data, one for each projection based on elevation change rate, and one for each projection based on elevation change rate attribute and RSLR with the applied elevation change rate attribute. Elevation change statistics were compiled by habitat type into the following comma-separated values (CSV) files: STT_Historical.csv, STT_25e.csv, STT_50e.csv, STT_75e.csv and STT_100e.csv. Some entries that do not have a large enough sample size to compute statistics display a "N/A" in that cell. These statistics can be found in STT_ProjectedSECAT.zip. Further information on the attributes and their definitions can be found in the DataDictionary_HabitatTypes_STT.pdf and DataDictionary_ElevationChangeAnalysis_STT.pdf files in the STT_ProjectedSECAT.zip download file.
Process_Date: 2020
Process_Step:
Process_Description:
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 STT_ProjectionMaps.zip download file.
Process_Date: 2020