Data Management Plan

These data show aquatic vascular vegetation beds dominated by submerged, rooted, vascular species or submerged or rooted floating freshwater tidal vascular vegetation. This is not a complete collection of seagrasses on the seafloor, nor are the locations to be considered exact. The presence and location of the seagrasses have been derived from multiple state and federal sources.

Process Steps:

• 2013-10-01 00:00:00 - 1) Acquire original source data 2) IMPORT each shapefile into a File Geodatabase 3) PROJECT into NAD83 4) DISSOLVE each state feature class based on all fields except Object ID, Acres, Shape Length, and Shape Area to remove data overlap 5) EXPLODE all multipart features in each state feature class 6) APPEND all state feature classes into a single feature class 7) Check for overlapping features and MERGE into a single feature 8) RENAME field names to match the the proposed data dictionary 9) DELETE all superfluous fields 10) Execute the CHECK GEOMETRY function
• 2019-01-01 00:00:00 - 1) Acquire data from sources by URL download or email. Determine if the new source data supersedes existing national data set. DELETE the older, superseded features and replace with the newer source data 2) MERGE new data sets and features into the former national data set, carrying over values from the necessary source fields that match the current data's schema 3) For ShoreZone polyline features within the Washington state DNR data, features were buffered five feet in order to generate the polygon format required of this data set. In this case, coverage was denoted as 'Present', since the polygon does not represent the footprint of the seagrass here, just that it was present somewhere along this shoreline segment 4) Convert the multipart layer to singlepart and then project into an equal area projection (example: USA Contiguous Albers Equal Area Conic). Add a new field called Acreage and calculate the geometry of the features. (Special note for the Washington state DNR data: per request of the source, the acreage values for the ShoreZone features were set to Null, and the acreage values for the SVMP features were derived from the source and not calculated separately.) Project the data back into NAD83 5) Remove all unnecessary fields and populate others according to data dictionary 6) Visually inspect older features for overlap with newer data. For example, if data from the 1970s within a small estuary is immediately adjacent to and overlapping data from 2016, remove the data from the 1970s 7) Execute the REPAIR GEOMETRY function PLEASE NOTE: Per request of the Washington state DNR, the acreage values for the ShoreZone features were set to Null, and the acreage values for the SVMP features were derived from the source and not calculated separately
• 2015-03-01 00:00:00 - 1) Acquire source data PLEASE NOTE: For Washington state, a large percentage of the state's coastline was designated as having seagrass based on a crosswalk between survey units (polygons) and shoreline seagrass status (polylines). Where polylines that were attributed as "seagrass present", polygons that intersected these line segments were extracted. While the resulting polygons (i.e. survey units) express that seagrass is found therein, it does not represent the footprint of the seagrass extent. Conversely, in some cases seagrass footprints were provided, such as in: Willapa Bay, Padilla Bay, and areas of Snohomish County. [Survey units originated from the Submerged Vegetation Monitoring Project (for Puget Sound and Strait of Juan de Fuca) and the Washington Marine Vegetation Atlas (for the Pacific coast). Shoreline status was provided by Washington state's ShoreZone inventory.] 2) Polygon to polyline crosswalk (noted above) performed in Washington state 3) Shoreline data (denoting seagrass presence) from California DFW was buffered by 20 meters to create polygons (i.e. generalized footprints) 4) PROJECT each data set in NAD83 GRS 80 5) ADD fields (date, provider, location) to each data set then populated 6) ERASE data sets that overlap, and retain the newer data or data determined to be preferential to another 7) MERGE all data sets 8) Removed unnecessary fields and populated others according to data dictionary 9) SPLIT merged data by UTM (zone 10 and 11), explode features, and CALCULATE area of polygons in acres 10) MERGE data from both zones then execute the CHECK GEOMETRY function
• 2022-06-26 00:00:00 - 1) Execute the REPAIR GEOMETRY function to remove null features and fix non-simple features 2) Modify field names for usability, and to avoid common controlled vocabulary