2017 USFS Lidar: Mantash Taneum

Product: Classified Lidar Point Cloud in LAZ format

The United States Forest Service, Region 6, (USFS) required leaf-on airborne lidar surveys to be collected over of national forestry in Oregon and Washington State. The following areas were requested to be covered: Gifford Pinchot National Forest (GIP) in Vancouver, Washington; Okanogan-Wenatchee National Forest (OKA) in Wenatchee, Washington; Malheur National Forest (MAL) in John Day, Oregon; Deschutes National Forest (DES) in Bend, Oregon, Willamette National Forest (WIL) in Eugene, Oregon, Umpqua National Forest (UMP) in Douglas, Lane, and Jackson Counties, Oregon. The following report applies to the Manatash Taneum AOI, which encompasses sixty one (61) square miles of the Okanogan-Wenatchee National Forest in Washington.

Aerial lidar data for this task order was planned, acquired, processed and produced at an aggregate nominal pulse spacing (ANPS) of 0.35 meters and aggregate nominal pulse density of 8 pulses per square meter.

The primary goals of this project are to provide high accuracy Light Detection and Ranging (lidar) data to enhance project planning and implementation; identify areas for the implementation of forest restoration treatments designed to restore forest structure in young-growth stands; and to provide engineering and resource specialists more information for on-the-ground project planning. In addition, these data will be 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 specified herein may also be used for vegetation mapping, road identification and mapping, hydrologic feature delineation, and landcover characterization applications including a canopy height model, understory vegetation prediction, and other stand metrics.

Tiling Scheme and Filenaming Convention

Tile Coverage: Tiles which lie completely within the project area will be complete to the tile edges. Tiles which lie partially outside the project boundary will be complete to the project boundary with enough overlap beyond the project boundary to ensure that no parts of the project are omitted.

Tile Size:

- Tile dimensions shall be 1,500 meters x 1,500 meters

- Tiled deliverables shall conform to the tiling scheme, without added overlap

- The tiling scheme shall be used for all tiled deliverables

- Tiled deliverables shall edge-match seamlessly in both the horizontal and vertical

Tile Naming: All tile-based deliverables shall be named according to the US National Grid naming convention. All

tile names shall include a project indicator and date of data collection, such as GIP for the Gifford Pinchot National

Forest and YYYYMMDD. Tiles shall also include indicator of data type, e.g. DTM for Digital Terrain Model (bare

earth). A general description of filenaming requirements is as follows:

Note: specific project site abbreviations will be provided post-award.

Example:

DTM_DESSWP_420000_943500_ 20170716

DTM: Data Type Abbreviation, e.g. digital terrain model

DES: Forest Abbreviation, e.g. Deschutes

SWP: Project Site Abbreviation, e.g. Swauk Pine

420000_943500: lower left coordinate identifier

20170716: collection date of July 16, 2017

YYYY: year, e.g. 2017

MM: month, e.g. 07 for July

DD: day, e.g. 16

Forest Abbreviations:

Deschutes: DES

Gifford Pinchot: GIP

Okanogan-Wenatchee: OKA

Malheur: MAL

Data Abbreviations:

DTM: digital terrain model

DSM: digital surface model

INT: intensity

FPC: full point cloud

GPC: ground point cloud

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "BOR-NGP Base Lidar Specification v1.2",

"ldrsens" : "Leica ALS70-HP",

"ldrmaxnr" : "unlimited",

"ldrnps" : "0.2907",

"ldrdens" : "11.8374",

"ldranps" : "0.3010",

"ldradens" : "11.0350",

"ldrfltht" : "2400",

"ldrfltsp" : "110",

"ldrscana" : "24",

"ldrscanr" : "40.5",

"ldrpulsr" : "239800",

"ldrpulsd" : "4",

"ldrpulsw" : "0.50",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.15",

"ldrswatw" : "933",

"ldrswato" : "52",

"ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B"

},

"ldraccur" : {

"ldrchacc" : "0",

"rawnva" : "0",

"rawnvan" : "0",

"clsnva" : "0.1738",

"clsnvan" : "10",

"clsvva" : "0",

"clsvvan" : "0"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

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

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

"lasintr" : "32",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Unclassified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Low point (noise)"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High Point (Noise)"

}

}}

All derived products for Forest Service R6 Data Resources Management

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.

The non-vegetated vertical accuracy of the point cloud was 0.0887 meters RMSEz (0.1738 meters 95% confidence level) based on 10 check points. These are the values provided by the lidar contractor. Statistically, they should be reported as 0.09 meters and 0.17 meters respectively.

Area of interest covers project area. 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 NVA 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 area of interest. 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.