Spatial Data Catalog

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Layer information

Layer Name	SURFACE_LiDARDigitalGroundModelElevationHillshade_2021_original
Subject Category	Imagery
Title	2021 LiDAR Digital Ground Model (DGM) Elevation and Hillshade
Feature Count	1
Feature Type	Polygon
Published Date	Irregular
Spatial reference	NAD 1983 HARN StatePlane Washington North FIPS 4601 Feet
Open Data Availability	Yes
Place Keywords	King County, Seattle, Washington State, Pacific NW, WA
Theme Keywords	Lidar Digital Elevation Data, Digital Ground Model (DGM), Topography, Bare-Earth, Elevation Data, Virtually Deforested, Elevation
Supplemental Information	Last-return LiDAR data edited to remove 90-95% of vegetated and man-made elevated features. Depicts - within limits of operational accuracy, point density and editing efficiencies - a 'bare-earth' interpretation of the earth's surface. Also called Digital Ground Model (DGM), Virtually-Deforested (VDF) Model, or 'Mowed' surface. Data is stored as variably-spaced point files (LAS), ArcInfo Lattice Grids.

Attribute information

OBJECTID From Esri	Description Internal feature number. Domain Sequential unique whole numbers that are automatically generated.
SHAPE From Esri	Description Feature geometry. Domain Coordinates defining the features.
MosaicID No Source Noted	Description Not Found Domain Not Found
SHAPE_Length From Esri	Description Length of feature in internal units. Domain Positive real numbers that are automatically generated.
SHAPE_Area From Esri	Description Area of feature in internal units squared. Domain Positive real numbers that are automatically generated.

Contact information

Maintained by	KCGIS Center
Primary	KCGIS Center giscenter@kingcounty.gov

Constraints

Access	A cooperative data sharing arrangement between the Puget Sound LiDAR Consortium and King County allows certain formats of the LiDAR data to be distributed with out license or restriction. Certain processing and data handling charges for necessary cost recovery may apply. Access to raw mass point files is by special request and request evaluation only.
Use	These data products are based upon LiDAR returns which inherently contain some "non ground-surface" values. You should carefully determine the place-to-place accuracy and fitness of these data for your particular use. For many purposes a site- and use-specific field survey will be necessary.

Purpose

Comparable in purpose and use to the USGS Digital Elevation Model (DEM) data but generally of a higher level of accuracy and sample density.

Useful for a range of analytical and cartographic projects including flood hazard evaluation, geologic mapping, hydrologic modeling, slope and aspect determination, and line-of-sight calculations.

These data was processed through an extensive series of quality control steps by both the vendors and clients; however, they are still considered an interpretation or model of the earth's surface rather than an absolute point-to-point measure.

Further, the data are not without error due to incomplete editing, absence of sufficient point density, and other 'blunder' or erroneous points.

Finally, due to changing ground and vegetative conditions the quality and accuracy of the data vary considerably with areas of steep relief and/or dense vegetation exhibiting poorer quality than open flat areas.

This is due to a large variance in the number of points from area to area that are considered 'to-ground' values combined with the variance in absolute horizontal and positional accuracy of given points.

Users must make careful review of the fitness of these data for their particular use.

For many purposes a site- and use-specific field survey will be necessary.

In particular, derivation of contours, whether from the raw ascii points or a derived surface (i.

, lattice or tin), should be approached with caution due to the high variability of the data.

Contours generated at an interval finer than 5-feet may not meet necessary accuracy requirements for specific environmental or building purposes needs and do not take the place of a first-order ground .

Abstract

Last-return LiDAR data edited to remove 90-95% of vegetated and man-made elevated features.

Depicts - within limits of operational accuracy, point density and editing efficiencies - a 'bare-earth' interpretation of the earth's Also called Digital Ground Model (DGM), Virtually-Deforested (VDF) Model, or 'Mowed' Data is stored as variably-spaced point text files (ASCII), ArcInfo TIN (Triangulated Irregular Network) format, ArcInfo Lattice Grids, and hillshade TIFF images..

Change history

3/1/2023	King County DGM Process function The composite lattice is input to the ArcInfo HILLSHADE command with AZIMUTH = 315, ALTITUDE = 45 and ALL arguments.
3/1/2023	King County DGM Process Step 4: Any negative values in the resulting composite lattice are set to NULL. This is done to eliminate potential erroneous values and potentially confusing statistics. This tends to eliminate negative values associated with water features, as well as other spurious values. A 3x3 focalmean filter is executed against all NULL values to infill any inliers that have now been converted to NULL with an elevation approximation based on adjacent values. The 100 foot overlap of the input lattices reduces the possiblity of creating strong null value edges between tiles so this 3x3 filter is considered as filling only localized NULL 'holes' in the data. The original unaltered values of any given data point can be found in the underlying las point file if access to the unmassaged data is necessary.
7/1/2007	Added USGS 10m DEM data to tiles at the outer edge of the current data set. Two types of tiles were produced - tiles completely comprised of USGS elevation points and tiles that are a merge between the lidar elevation data and the USGS points. Only ASCII tiles were created. The USGS elevation data was not integrated into TINs, Hillshades or any higher-level products. 197 GS tiles were produced. The USGS DEM was clipped to the tile boundary, resampled to 12 foot, and exported as ID,X,Y,Elevation, where ID is a unique serial ID. For the JS tiles (170), both the existing lidar and new USGS point datasets were converted to coverages (USGS first to Lattice, then to point, Lidar first to TIN then to point). Using x_dgmasc.shp, which defines the extent of the lidar data, the USGS points that fell within the lidar extent were erased and the lidar points were clipped to the boundary to create a well-defined neat line. The two resulting coverages were unloaded to delimited files X,Y,Z and then appended. The appended file was then AWKed to create ID,X,Y,Z to create tileabb_dgmjs.asc The completed file was TINNed and hillshaded for quality control inspection. Finally, both the complete GS and JS tiles were zipped and placed in the SDW library.
6/1/2006	Add Bathemetry data for Puget Sound, Lake Washington, Lake Sammamish. Indentify which idxp7500 tiles that have bathymetry data to be processed and build tinlist. Digitize and replace waterbody outlines of coverage lakebathy using KC2002 2ft JP2 format imagery at scale 1:2500. Determine each lake in lakebathy surface elevation using lidar and adjust lakebathy contour line elevation values to the lidar. Append all waterbody Edge Of Water arcs into one coverage for erasing water surface data and EOW hardline for TIN production. run j:phase2\bathy\mktin_puget.aml , mktin_wash.aml, mktin_sam.aml Creates new tins using lidar tile tin to points from plibrary3, bathymetry points: reg_ps_bthy (Puget Sound), reg_wl_bthy (Lake Washington), reg_ls_bthy (Lake Sammamish) arcs for hard breakline around the lake. Build dgm grid, hillshade grid and image.
1/1/2003	King County DGM Process Step 1: After receipt from NV5, the data media was cataloged, and the media contents were logged. The tif files were retiled into the King County idxp7500 tiling scheme. This resulted in creation of larger files where several 1 x 1 km 3di tiles were appended and clipped to form one 7500 ft x 7500 King County tile. The las records were also appended with a integer identifier resulting in a final record format of identifier, easting, northing, and elevation value.
1/1/2002	Vendor DGM Production Step 1: LiDAR data processing was used to produce the x,y,z elevation points using vendor proprietary lidar data processing software. Within this integrated process an atmospheric correction was made, which is especially important in regions of relatively low elevation.
1/1/2002	Vendor DGM Production Step 2: Data by flight line was combined in a merge process that eliminates redundant points. Data was also clipped into more manageable one km x one km bounds. Noise or anomalous returns were filtered from all data during this processing step. The data was quality checked using commercial software, Spectra Precision TerraModel and TerraVista. In order to produce a ground surface DEM, vegetation removal was performed on the last return elevation points data by identifying the laser returns from above ground vegetation. This proprietary algorithm is capable of removing between 90-95% of the trees and most other prominent above ground vegetation from the data. The data was triangulated into contours and any remaining vegetation or manmade structures and buildings were identified visually and interactively removed from the data. The data was triangulated again, contoured and visualized to see the effect of the additional elevation point removal and for any final edits that might be necessary.
1/1/2002	Vendor DGM Production Step 4: Bare earth return point data was transferred to media for delivery to Client in a comma/space delimited ASCII file of format easting,northing,intensity-value.
1/1/2002	Vendor DGM Production Step 3: All elevation data was processed on a point by point basis for ellipsoid to orthometric height conversion using the National Geodetic Survey (NGS) Geoid Model, GEOID99. Datum and coordinate system conversion from WGS84 to the Washington State Plane coordinate system was performed using U.S. Army Corps of Engineers CorpsCon software algorithms.
Update 10	Ground LiDAR data from Watershed Science dated 2010 was integrated into master elevation database. See https://www5.kingcounty.gov/sdc/raster/elevation/LiDAR_Digital_Ground_Model_Elevation_Watershed_Science_2010.html for vendor metadata. The following townships were updated: T19R06 T20R06 T20R07 T21R05 T22R04 T22R06 T22R07 T23R05 T23R06 T23R08 T23R09 T24R05 T24R07 T24R08 T25R07 NOAA bathyemetry extented for Duwamish for T24R04
Update 11	Ground LiDAR ascii data from Watershed Science dated 2007 for parts of Snoqualmie, Green, & White River are integrated into master elevation database. This is the first update that was converted from Arc\Info GRID\AML to ARCGIS SDE RASTER\Python. See documentation: DGM Update Procedure.doc The following townships were updated: T20R05 T21R04 T21R05 T21R06 T23R08 T24R07 T25R07 T26R07
Update 12	Ground LiDAR data from Watershed Science dated 2011 was integrated into master elevation database. See https://www5.kingcounty.gov/sdc/raster/elevation/LiDAR_Digital_Ground_Model_Elevation_Watershed_Science_2011.html for vendor metadata. The following townships were updated: T19R06 T20R04 T20R05 T20R06 T21R04 T21R05 T22R04 T22R06 T22R07 T23R04 T23R05 T23R06 T23R07 T23R08 T23R09 T23R09 T24R07 T24R08 T24R09 T25R06 T25R07 T26R05 T26R06