Data Management Plan

This Light Detection and Ranging (LiDAR) dataset is a survey of the Pocomoke and Atlantic Coastal Watersheds in Maryland. The project area consists of approximately 500 square miles. The project design of the LiDAR data acquisition was developed to support a nominal post spacing of 0.70 meter. Fugro EarthData, Inc. acquired 151 flight lines in eight lifts on February 6, 7, 9, 13, 15, and 16, 2011; in tidal areas, data was collected within 2 hours (before or after) of mean low tide. The data was divided into 1500 by 1500 meter cells that serve as the tiling scheme. LiDAR data collection was performed with a Piper Navajo twin engine aircraft, utilizing a Leica ALS60 MPiA sensor, collecting multiple return x, y, and z as well as intensity data. LiDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This data of the Pocomoke and Atlantic Coastal Watersheds in Maryland, was collected at sufficient resolution to provide a nominal point spacing of 0.70 meter for collected points. Up to 4 returns were recorded for each pulse in addition to an intensity value.

Lineage Statement:
Original acquisition and processing of lidar data was completed by Fugro EarthData, Inc. and delivered to NRCS and Maryland. NOAA OCM obtained the data from Maryland iMAP and modified for ingest into the Digital Coast system.

Process Steps:

• 2011-06-27 00:00:00 - Fugro EarthData utilized commercial software as well as proprietary software for automatic filtering. The parameters used in the process were customized for each terrain type to obtain optimum results. Once the automated filtering was completed, the files were run through a visual inspection to ensure that the filtering was not too aggressive or not aggressive enough. In cases where the filtering was too aggressive and important terrain features were filtered out, the data was either run through a different filter or was corrected during the manual filtering process. Interactive editing was then completed in 3D visualization software which also provides manual and automatic point classification tools. Vegetation and artifacts remaining after automatic data post-processing were reclassified manually through interactive editing. The hard edges of ground features that were automatically filtered out during the automatic filtering process were brought back into ground class during manual editing. Auto-filtering routines were utilized as much as possible within fenced areas during interactive editing for efficiency. The technician reviewed the LiDAR points with color shaded TINs for anomalies in ground class during interactive filtering. Upon the completion of peer review and finalization of bare earth filtering, the classified LiDAR point cloud work tiles went through a water classification routine. Upon the completion of finalization of the classified LiDAR point cloud work tiles, the tiles were reprojected to NAD83 (HARN), UTM zone 18 north, meters; NAVD88, meters, using GEOID09 and cut to the approved tile layout in LAS format.
• 2011-06-24 00:00:00 - The hydrographic features were collected as vector linework using classified LiDAR datasets, intensity images, shaded-relief TIN surfaces, and contours. These features were classified as Inland Ponds and Lakes, Inland Streams and Rivers (single line), Inland Streams and Rivers (double line), Non-Tidal Boundary Waters, and Tidal Waters. After initial collection, linework was then checked for the following topological and attribution rules: non-bank lines must be digitized from an uphill to downhill direction, lines must be attributed with the correct feature code, dangles must exist only at the upstream headwater end of streams and at the downstream outfall, line intersections must be at nodes, non-bankline features must form a dendritic collection network, lakes that have a digitized inflow path must have a centerline as well, lakes that have a digitized outflow path but do not have a digitized inflow path should not have a centerline, isolated ponds that are not part of the drainage network should not have centerlines; lake and stream banklines must form closed polygons, single streams should not fall within bankline polygons and lake and stream connector lines should not fall outside of bankline polygons. Hydro features were collected as vector linework using LiDAR and its derived products listed above. This linework is initially 2D, meaning that it does not have elevation values assigned to individual line vertices. Vertex elevation values were assigned using a distance weighted distribution of LiDAR points closest to each vertex. After the initial 'drape', the linework elevation values were further adjusted based on the following rules: lake feature vertices were re-assigned (flattened) to lowest draped vertex value; lake connector line vertices were re-assigned (flattened) to lowest draped vertex value of the surrounding lake bankline, single stream and stream connector line vertices were adjusted so that subsequent vertices are lower than previous ones based on line direction, and double stream bankline vertices were re-assigned based on the vertices of the closest adjusted double stream connector line. After assignment of 3D values, the stream network is checked to ensure the following does not exist: large differences between initial drape and adjusted elevation values, elevation differences between nodes, and elevation values flowing in an 'uphill' direction. Data was provided to the terrain department for hydro-enforcement of the DEM.
• 2017-10-16 00:00:00 - NOAA OCM downloaded the data from Maryland iMAP as zip files by Block. (Citation: Lidar data from Maryland iMAP)
• 2018-02-26 00:00:00 - Lidar data were changed from NAVD88 (Geoid09) vertical coordinates to ellipsoid heights using the GEOID09 grids. The class scheme was not described in the original metadata, but research on the related data for the Worcester coastal area suggests class 10 is ignored ground near breaklines and class 11 is withheld. Examination of the data supports that hypothesis. Data were then ingested into the Digital Coast Data Access Viewer system for distribution.

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