2015 USFS Lidar DEM: Colville National Forest, WA

This digital elevation model (DEM) was created from a classified lidar point cloud encompassing the Colville National Forest project area, approximately 742 square miles. Each LAS/LAZ file contains LiDAR point information, which has been calibrated, controlled, and classified.

Ground Conditions: water at normal levels; no unusual inundation; no snow; leaf off

The United States Forest Service (USFS, Government), Colville National Forest (CNF), requested airborne LiDAR services and products for several project areas totalling 742 mi2 throughout the Colville National Forest in NE Washington. The primary goals of this project included providing high accuracy and density (8pls/m2) LiDAR to enhance project planning and implementation, and to provide engineering and timber sale preparation specialists more information for on-the-ground project planning. In addition, these data are used by researchers and scientists to characterize vegetation type and structure as it currently exists on the landscape and to provide a detailed, accurate, and precise benchmark for future change detection work. The data products potentially will also be used for vegetation mapping, hydrologic feature delineation, and landcover characterization applications including a canopy height model, understory vegetation prediction, and other stand metrics.

All Lidar data was acquired, calibrated, and used in the creation of Lidar derived products by Atlantic.

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "USFS

",

"ldrsens" : "Leica ALS70-HP

",

"ldrmaxnr" : "Unlimited

",

"ldrnps" : "0.35

",

"ldrdens" : "8.0

",

"ldranps" : "0.2425

",

"ldradens" : "18.3

",

"ldrfltht" : "2926

",

"ldrfltsp" : "110

",

"ldrscana" : "34

",

"ldrscanr" : "38

",

"ldrpulsr" : "209

",

"ldrpulsd" : "4

",

"ldrpulsw" : "0.46

",

"ldrwavel" : "1064

",

"ldrmpia" : "0

",

"ldrbmdiv" : "0.15

",

"ldrswatw" : "924

",

"ldrswato" : "50

",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12A

"

},

"ldraccur" : {

"ldrchacc" : "0.196

",

"rawnva" : "0.160

",

"rawnvan" : "60

",

"clsnva" : "0.158

",

"clsnvan" : "60

",

"clsvva" : "0.142

",

"clsvvan" : "56

"

},

"lasinfo" : {

"lasver" : "1.4

",

"lasprf" : "6

",

"laswheld" : "Withheld (ignore) points were identified in the files using the standard LAS Withheld bit.

",

"lasolap" : "Swath 'overage' points were identified in these files using the standard LAS overlap bit.

",

"lasintr" : "16

",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Undetermined/Unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare earth"

}

}}

Tiled LiDAR DEM for Colville NF

The data represented is the result of data collection and processing per contract specifications and indicates the general existing conditions at the time of data collection. As such, it is only valid for its intended use, content, time, and accuracy specifications. The user is responsible for the results of any application of the data for other than its intended purpose.

Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners

Data is available online for bulk or custom downloads

None

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.

CloudPro 1.2.0 Build 85620; GeoCue Version 2014.1.21.2; Windows 7 Operating System

\\tagwork38\GC_Warehouse_8\80670\46\*.las

1.04 TB

Horizontal error in lidar derived elevation data is largely a function of positional error as derived from the Global Navigation Satellite System (GNSS), attitude (angular orientation) error (as derived from the INS) and flying altitude; and can be estimated based on these parameters. Quantitative value: 14.4 cm, Test that produced the valued: As described in Section 7.5 of the ASPRS Positional Accuracy Standards for Digital Geospatial Data the horizontal errors in lidar data are largely a function of GNSS positional error, INS angular error, and flying altitude. Therefore lidar data collected with GNSS error of 0.05m and the IMU error of 0.03492 degrees at an altitude of 2926m; the expected radial horizontal positional error will be RMSEr = 14.4cm.

Vertical Accuracy of the point cloud and bare-earth lidar data was assessed and reported in accordance with the ASPRS Positional Accuracy Standards for Digital Geospatial Data;

One-Hundered and sixteen (116) surveyed points were measured for the purpose of assessing the accuracy of the Colville NF Lidar data. (60 NVA + 56 VVA)Quantitative value: 15.8 cm, Test that produced the value: This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10.0(cm) RMSEz Vertical Accuracy Class equating to NVA = +/-19.6cm at 95% confidence level and VVA =+/-29.4cm at the 95th percentile.

This data set was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10.0(cm) RMSEz Vertical Accuracy Class. Actual NVA accuracy of the point cloud was found to be RMSEz = 4.1cm, equating to +/-8.1cm at 95% confidence level. Actual NVA accuracy of the bare-earth was found to be RMSEz = 4.1cm, equating to +/-8.0cm at 95% confidence level. Actual VVA accuracy was found to be +/-14.3cm at the 95th percentile.

The raw LAS data files included all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Fundamental Vertical Accuracy specifications.Void areas (i.e., areas outside the project boundary but within the tiling scheme) are coded using a unique “NODATA” value. This value is identified in the appropriate location within the file header.

All LiDAR data and LiDAR Derived data covers the entire 742 square mile area. All LiDAR Point Cloud tiles show no edge artifacts or mismatches from tile to tile. Void areas (i.e. areas outside the project boundary but within the tiling scheme) are coded using a unique “NODATA” value. This value is identified in the appropriate location within the file header. Data cover the entire area specified for this project.

Data is backed up to tape and to cloud storage.