2017 NRCS Lidar: East Sacramento Foothills, CA

Original Dataset Product: Processed, classified lidar point cloud data tiles in LAS 1.4 format.

Original Dataset Geographic Extent: Approximately 1,399 square miles across several counties in central California. The counties are: Amador, Calaveras, Madera, Merced, Sacramento, San Joaquin, Stanislaus

Original Dataset Description: The CA Central Valley Lidar 2016 D16 lidar project called for the planning, acquisition, processing, and production of derivative products of lidar data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications were based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal datum/projection of NAD83 (2011) UTM Zone 10 (EPSG 6339) meters, and a vertical datum of NAVD88 (GEOID12B), US Survey Feet. Classified lidar point cloud data was delivered as LAS 1.4 files formatted to 1,931 individual 1,500-meter x 1,500-meter tiles.

Original Dataset Ground Conditions: Lidar was collected from December 3, 2017 through December 7, 2017 by Woolpert, while no snow was on the ground and rivers were at or below normal levels. Saturated or partially flooded farm fields were identified following data acquisition. Through technical guidance discussions with USGS and the California Department of Water, it was determined such areas shall not be considered hydrologic features. In all cases, best professional judgement was used in determination of treatment. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established 42 ground control points that were used to calibrate the lidar to known ground locations established throughout the project area. An additional 165 independent accuracy checkpoints (89 NVA points and 76 VVA points), were collected and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services.

Data was collected to be used for the following: terrain mapping, conservation planning and design, support of easement/land stewardship programs, support of special emphasis programs, support of soil projects, fill gaps in existing lidar, water resource management.

USGS Contract No. G16PC00022 Task Order No. G16PD01047. CONTRACTOR: Woolpert

The following are the USGS lidar fields in JSON:

{

"ldrinfo" : {

"ldrspec" : "USGS NGP Base Specifications v1.2",

"ldrsens" : "Leica ALS 80",

"ldrmaxnr" : "Unlimited",

"ldrnps" : "0.7",

"ldrdens" : "2",

"ldranps" : "0.7",

"ldradens" : "2",

"ldrfltht" : "2377",

"ldrfltsp" : "150",

"ldrscana" : "40",

"ldrscanr" : "35.5",

"ldrpulsr" : "346.0",

"ldrpulsd" : "5",

"ldrpulsw" : "2.5",

"ldrwavel" : "1064",

"ldrmpia" : "1",

"ldrbmdiv" : "0.20",

"ldrswatw" : "1165",

"ldrswato" : "40",

"ldrgeoid" : "GEOID12B"

},

"ldraccur" : {

"ldrchacc" : "0",

"rawnva" : "0.080",

"rawnvan" : "89",

"clsnva" : "0.074",

"clsnvan" : "89",

"clsvva" : "0.216",

"clsvvan" : "76"

},

"lasinfo" : {

"lasver" : "1.4",

"lasprf" : "6",

"laswheld" : "Geometrically unreliable points were identified using a combination of automated and manual techniques and subsequently classified as high or low noise and given the standard Withheld bit.",

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

"lasintr" : "16",

"lasclass" : {

"clascode" : "1",

"clasitem" : "Processed but not classified"

},

"lasclass" : {

"clascode" : "2",

"clasitem" : "Bare earth ground"

},

"lasclass" : {

"clascode" : "7",

"clasitem" : "Noise"

},

"lasclass" : {

"clascode" : "9",

"clasitem" : "Water"

},

"lasclass" : {

"clascode" : "10",

"clasitem" : "Ignored ground"

},

"lasclass" : {

"clascode" : "17",

"clasitem" : "Bridge Decks"

},

"lasclass" : {

"clascode" : "18",

"clasitem" : "High Noise"

}

}}

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 and 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.

Microsoft Windows 10 Version 1607 (Build 14393.2189); ArcMap 10.3; ArcCatalog 10.3; TerraScan ver. 17; TerraModeler ver. 17; Geocue 2017.2.20.0.

The project specifications require that only Non-Vegetated Vertical Accuracy (NVA) be computed for raw lidar point cloud swath files. The required accuracy (ACCz) is: 19.6 cm at a 95% confidence level, derived according to NSSDA, i.e., based on RMSE of 10 cm in non-vegetated land cover classes.

The NVA was tested with 89 checkpoints located in bare earth and urban (non-vegetated) areas. These check points were not used in the calibration or post processing of the lidar point cloud data. The checkpoints were distributed throughout the project area and were surveyed using GPS techniques. Elevations from the unclassified lidar surface were measured for the x,y location of each check point. Elevations interpolated from the lidar surface were then compared to the elevation values of the surveyed control points. AccuracyZ has been tested to meet 19.6 cm or better Non-Vegetated Vertical Accuracy at 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standard for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.

Tested 0.080 meters NVA at a 95% confidence level using RMSE(z) 0.041 x 1.9600 as defined by the National Standard for Spatial Data Accuracy (NSSDA). The NVA of the raw lidar point cloud swath files was calculated against TINs derived from the final calibrated and controlled swath data using 89 independent checkpoints located in non-vegetated land cover categories.

These LAS data files include 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.

Data covers the entire area specified for this project.

Data is backed up to cloud storage.

The NOAA Office for Coastal Management (OCM) ingested references to the USGS Entwine Point Tiles (EPT) hosted on Amazon Web Services (AWS) into the Digital Coast Data Access Viewer (DAV). The DAV accesses the point cloud as it resides on AWS under the usgs-lidar-public-container.