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LiDAR/BareEarthDTM2017_Hillshade_DNR (ImageServer)

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Service Description:

In March 2016, Quantum Spatial (QSI) was contracted by the United States Geological Survey (USGS), in collaboration with the Washington Department of Natural Resources (WADNR), to collect Light Detection and Ranging (LiDAR) data for the Western Washington 3DEP QL1 LiDAR project site in the state of Washington. The Western Washington 3DEP LiDAR project area covers approximately 3.5 million acres within portions of thirteen counties in the state of Washington; Whatcom, Skagit, Snohomish, Thurston, Lewis, Clark, Cowlitz, Wahkiakum, Skamania, and Grays Harbor. Data were collected to aid USGS in assessing the topographic and geophysical properties of the study area.

For the Western Washington 3DEP LiDAR project, the monument coordinates contributed no more than the listed positional error to the geolocation of the final ground survey points and LiDAR, with 95% confidence.

Upon completion of data acquisition, QSI processing staff initiated a suite of automated and manual techniques to process the data into the requested deliverables. Processing tasks included GPS control computations, smoothed best estimate trajectory (SBET) calculations, kinematic corrections, calculation of laser point position, sensor and data calibration for optimal relative and absolute accuracy, and LiDAR point classification (Table 9). Processing methodologies were tailored for the landscape.

The ocean surrounding the Western Washington 3DEP site and other water bodies within the project area were flattened to a consistent water level. Bodies of water that were flattened include lakes and other closed water bodies with a surface area greater than 2 acres, all streams and rivers that are nominally wider than 100 feet, and all tidal waters bordering the project. Islands within water bodies with area greater than 1 acre were not hydroflattened, with select smaller islands and features remaining as feasible. The hydroflattening process eliminates artifacts in the digital terrain model caused by both increased variability in ranges or dropouts in laser returns due to the low reflectivity of water.

Hydroflattening of closed water bodies was performed through a combination of automated and manual detection and adjustment techniques designed to identify water boundaries and water levels. Boundary polygons were developed using an algorithm which weights LiDAR-derived slopes, intensities, and return densities to detect the water’s edge. The water edges were then manually reviewed and edited as necessary.

Once polygons were developed the initial ground classified points falling within water polygons were reclassified as water points to omit them from the final ground model. Elevations were then obtained from the filtered LiDAR returns to create the final breaklines. Lakes were assigned a consistent elevation for an entire polygon while rivers were assigned consistent elevations on opposing banks and smoothed to ensure downstream flow through the entire river channel.

Water boundary breaklines were then incorporated into the hydro-flattened DEM by enforcing triangle edges (adjacent to the breakline) to the elevation values of the breakline. This implementation corrected interpolation along the hard edge. Water surfaces were obtained from a TIN of the 3-D water edge breaklines resulting in the final hydroflattened model.



Name: LiDAR/BareEarthDTM2017_Hillshade_DNR

Description:

In March 2016, Quantum Spatial (QSI) was contracted by the United States Geological Survey (USGS), in collaboration with the Washington Department of Natural Resources (WADNR), to collect Light Detection and Ranging (LiDAR) data for the Western Washington 3DEP QL1 LiDAR project site in the state of Washington. The Western Washington 3DEP LiDAR project area covers approximately 3.5 million acres within portions of thirteen counties in the state of Washington; Whatcom, Skagit, Snohomish, Thurston, Lewis, Clark, Cowlitz, Wahkiakum, Skamania, and Grays Harbor. Data were collected to aid USGS in assessing the topographic and geophysical properties of the study area.

For the Western Washington 3DEP LiDAR project, the monument coordinates contributed no more than the listed positional error to the geolocation of the final ground survey points and LiDAR, with 95% confidence.

Upon completion of data acquisition, QSI processing staff initiated a suite of automated and manual techniques to process the data into the requested deliverables. Processing tasks included GPS control computations, smoothed best estimate trajectory (SBET) calculations, kinematic corrections, calculation of laser point position, sensor and data calibration for optimal relative and absolute accuracy, and LiDAR point classification (Table 9). Processing methodologies were tailored for the landscape.

The ocean surrounding the Western Washington 3DEP site and other water bodies within the project area were flattened to a consistent water level. Bodies of water that were flattened include lakes and other closed water bodies with a surface area greater than 2 acres, all streams and rivers that are nominally wider than 100 feet, and all tidal waters bordering the project. Islands within water bodies with area greater than 1 acre were not hydroflattened, with select smaller islands and features remaining as feasible. The hydroflattening process eliminates artifacts in the digital terrain model caused by both increased variability in ranges or dropouts in laser returns due to the low reflectivity of water.

Hydroflattening of closed water bodies was performed through a combination of automated and manual detection and adjustment techniques designed to identify water boundaries and water levels. Boundary polygons were developed using an algorithm which weights LiDAR-derived slopes, intensities, and return densities to detect the water’s edge. The water edges were then manually reviewed and edited as necessary.

Once polygons were developed the initial ground classified points falling within water polygons were reclassified as water points to omit them from the final ground model. Elevations were then obtained from the filtered LiDAR returns to create the final breaklines. Lakes were assigned a consistent elevation for an entire polygon while rivers were assigned consistent elevations on opposing banks and smoothed to ensure downstream flow through the entire river channel.

Water boundary breaklines were then incorporated into the hydro-flattened DEM by enforcing triangle edges (adjacent to the breakline) to the elevation values of the breakline. This implementation corrected interpolation along the hard edge. Water surfaces were obtained from a TIN of the 3-D water edge breaklines resulting in the final hydroflattened model.



Single Fused Map Cache: false

Extent: Initial Extent: Full Extent: Pixel Size X: 3.0

Pixel Size Y: 3.0

Band Count: 1

Pixel Type: U8

RasterFunction Infos: {"rasterFunctionInfos": [{ "name": "None", "description": "A No-Op Function.", "help": "" }]}

Mensuration Capabilities: None

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: Washington Department of Natural Resources (WADNR), United States Geological Survey (USGS), Quantum Spatial (QSI)

Service Data Type: esriImageServiceDataTypeGeneric

Min Values: 0

Max Values: 254

Mean Values: 215.20786876583873

Standard Deviation Values: 21.311114414859535

Object ID Field: OBJECTID

Fields: Default Mosaic Method: Northwest

Allowed Mosaic Methods: NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None

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Mosaic Operator: First

Default Compression Quality: 100

Default Resampling Method: Bilinear

Max Record Count: 1000

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: 20

Max Mosaic Image Count: 20

Allow Raster Function: true

Allow Copy: null

Allow Analysis: null

Allow Compute TiePoints: false

Supports Statistics: true

Supports Advanced Queries: true

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Histograms   Key Properties   Legend   Raster Function Infos

Supported Operations:   Export Image   Query   Identify   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query Boundary   Compute Pixel Location   Validate   Project