2009 - 2010 PSLC LiDAR: USGS Wenas Valley

The dataset encompasses portions of Wenas Valley in Kitittas and Yakima Counties, Washington.

The bare earth digital elevation models (DEMs) represent the earth's surface with all

vegetation and human-made structures removed. The bare earth DEMs were derived from

LiDAR data using TIN processing of the ground point returns. Some elevation values

have been interpolated across areas in the ground model where there is no elevation

data (e.g. over dense vegetation).

The DEM grid cell size is 3-ft. The projection is NAD83 (HARN) Washington State Plane,

South. The elevation units are in U.S. Survey Feet.

Watershed Sciences, Inc. collected the LiDAR and created this data set for the Puget

Sound LiDAR Consortium.

Watershed Sciences, Inc. (WS) initially collected 37,969 acres of Light Detection

and Ranging (LiDAR) data of the Wenas Valley area of interest (AOI) in Kittitas and Yakima

Counties, WA on October 28th, 2009. This data was delivered on November 21st, 2009.

After the AOI was clear of snow, the remaining 110,255 acres were collected on March

22nd and from June 12th to June 16th, 2010. The total deliverable area including a

100 m buffer is 148,224 acres.

Provide high resolution terrain elevation and land cover elevation data.

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A footprint of this data set may be viewed in Google Earth at:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2588/supplemental/wa2009_pslc_usgs_wenasvalley.KMZ

Reports explaining collection and quality assurance is available at:

https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/2588/supplemental/wa2009_pslc_usgs_wenasvalley.pdf

LiDAR points in LAZ format (ASPRS Classes 1,2)

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Any conclusions drawn from the analysis of this information are not the responsibility

of Watershed Sciences, PSLC, NOAA, the Office for Coastal Management or its partners.

This data can be obtained on-line at the following URL:

https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=2588

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Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data

may no longer represent actual surface conditions. Users should not use this data for critical applications without a full

awareness of its limitations. These data depict the heights at the time of the survey and are only accurate for that time.

Elevations are recorded in floating-point meters and the vertical datum is ellipsoidal (GEOID03).

Horizontal positional accuracy for LiDAR is dependent upon the quality of

the GPS/INS solution, sensor calibration and ground conditions at the time of data capture.

The standard system results for horizontal accuracy are less than 1 meter. Not reported, assumed as 1.0 m.

; Quantitative Value: 1.0 meters, Test that produced the value: See LiDAR data report.

The vertical accuracy of the LiDAR data is described as the mean and standard deviation

(sigma ~ ) of divergence of LiDAR point coordinates from RTK ground survey point

coordinates. To provide a sense of the model predictive power of the dataset, the root mean

square error (RMSE) for vertical accuracy is also provided. These statistics assume the error

distributions for x, y, and z are normally distributed, thus we also consider the skew and

kurtosis of distributions when evaluating error statistics.

Statements of statistical accuracy apply to fixed terrestrial surfaces only and may not be

applied to areas of dense vegetation or steep terrain. To calibrate laser accuracy for the

LiDAR dataset, 3120 RTK ground check points were collected on fixed, hard-packed road

surfaces within the survey area.

; Quantitative Value: 0.05 meters, Test that produced the value:

The Root Mean Square Error (RMSE) of the data set is

0.17 ft (5.19 cm). Accuracy was assessed using 3120 ground survey (real time kinematic) points.

Please see LiDAR data report for a discussion of statistics related to these datasets.

LiDAR data has been collected and processed for all areas within the project study area.

LiDAR flight lines have been examined to ensure that there was at least 60% sidelap, there are minimal gaps between

flightlines, and overlapping flightlines have consistent elevation values.

Shaded relief images have been visually inspected for data errors such as pits, border artifacts, gaps, and

shifting. The data was examined at a 1:2000 scale.