20200212
11374400
1.0
FGDC CSDGM Metadata Abridged2
FALSE
Lidar_HydroFlat_BareEarth_HS_2013
Local Area Network
6119016.656046
6497017.168888
1797201.893708
2250801.921360
1
002
Projected
GCS_NAD_1983_2011
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_California_II_FIPS_0402_Feet_2011
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32
FALSE
Mixed
1
Cache/Mixed
TRUE
continuous
unsigned integer
20230602
05364400
20230602
05364400
500000
5000
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Watershed Sciences, Inc. (WSI)
503-505-5100
503-546-6801
421 S.W. 6th Ave., Suite 800
Portland
OR
97204
US
ArcGIS Metadata
1.0
Sonoma County Agricultural Preservation and Open Space District
Not Available
747 Mendocino Ave, Suite 100
Santa Rosa
CA
95401
US
Raster Dataset
2013-11-22
WSI
raster digital data
Lidar_HydroFlat_BareEarth_HS_2013
The Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) and the University of Maryland (under grant NNX13AP69G from NASA’s Carbon Monitoring System, Dr. Ralph Dubayah, PI) contracted LiDAR and orthophoto data collection for all of Sonoma County in late 2013. Also included in the data collection were two areas in Mendocino County - the Soda Spring Creek-Dry Creek Watershed and Lake Mendocino. This fine scale data will help provide an accurate, up-to-date inventory of the county’s landscape features, ecological communities and habitats. Project funders include: NASA, the University of Maryland, the Sonoma County Agricultural Preservation and Open Space District, the Sonoma County Water Agency, the California Department of Fish and Wildlife, the United States Geological Survey, the Sonoma County Information Systems Department, the Sonoma County Transportation and Public Works Department, the Nature Conservancy, and the City of Petaluma.
Sonoma County Vegetation Mapping and LiDAR Consortium, NASA, University of Maryland, Watershed Sciences, Inc., Tukman Geospatial LLC
Sonoma County, Mendocino Lake, Dry Creek
WSI, LiDAR, Light Detection And Ranging
LiDAR
Light Detection And Ranging
Sonoma County
Lake Mendocino
Sonoma Lake Watershed
This dataset was contracted by the Sonoma County Vegetation Mapping and LiDAR Consortium (the Consortium), a group of public and private organizations. This dataset may be available for public distribution, information regarding the use of this dataset should be directed to the Consortium.
<div style='text-align:Left;'><div><div><p><span>Data were provided by the University of Maryland and the Sonoma County Vegetation Mapping and LiDAR Program (http://sonomavegmap.org) under grant NNX13AP69G from NASA’s Carbon Monitoring System (Dr. Ralph Dubayah, PI). This data is available for unrestricted public use. However, users should acknowledge the source of the data in any reports, publications, or presentations where the data is used.</span></p></div></div></div>
-123.067521
-122.345272
38.103762
38.304223
Ground Condition - LiDAR: Leica ALS50 & Leica ALS70
2013-09-28
2013-10-07
Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388
1
-123.565033
-122.224632
39.342439
38.086871
<div style='text-align:Left;'><div><div><p><span>A bare earth digital elevation model (DEM) represents the earth's surface with all vegetation and human-made structures removed. The bare earth DEMs were derived from LiDAR data using triangulated irregular network (TIN) processing of the ground point returns. Hydro-flattened Bare Earth DEMs represent water bodies in a cartographically and aesthetically pleasing manner, and are not intended to accurately map water surface elevations. In a Hydro-flattened DEM, water surfaces are flat and level for lakes with a greater area than two acres, and gradated for rivers or other long impoundments (e.g., reservoirs) that are wider than 100 feet, and tidal areas. Any existing island larger than one acre was be delineated. Water surface edge elevations were at or below the immediately surrounding terrain. Each image corresponds to a 37,800-square-foot tile. Each pixel is 3 feet and represents an average elevation for that area. The specified coordinate system for this dataset is California State Plane Zone II (FIPS 0402), NAD83 (2011), with units in US Survey Feet for horizontal, and vertical units are NAVD88 (12A) US Survey Feet. The dataset encompasses a portion of Sonoma County. WSI collected the LiDAR and created this data set for the Sonoma County Vegetation Mapping and LiDAR Consortium.</span></p></div></div></div>
LiDAR flight lines have been examined to ensure that there was at least 60% sidelap, there are no 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 were examined at a 1:3000 scale.
LiDAR has been collected and processed for all areas within the project study Area. In some areas of heavy vegetation and forest cover, there may be relatively few ground points in the LiDAR data. Some elevation units have been interpolated across areas in the ground model where there are no elevation data (e.g., over water, over dense vegetation). TINing the points produces large triangles and hence the elevations may be less accurate within such areas. Some elevation units have been interpolated across areas in the ground model where there are no elevation data (e.g., over water, over dense vegetation).
Relative Accuracy measures the divergence between points from different flightlines. Relative Accuracy median is 0.03 meters (0.11 feet) out of 42,366,153,872 laser points over 405 flightlines. For more information regarding the internal consistency between ground-classified points from different overlapping flightlines please see LiDAR data report.
The Fundamental Vertical Accuracy (FVA) of the data set is 0.05 meters (0.15feet). Accuracy was assessed using 129 ground control (real time kinematic) points. These ground control points are distributed through out the project study area.
The FVA was tested using 129 independent ground control points (GCP's) located in open terrain. The GCPs were distributed throughout the project area. 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. The Root-Mean-Square (RMSE) was computed to be 0.05m. AccuracyZ has been tested to meet 0.05m FVA at 95 Percent confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines.
0.05 meters RMSEz at 95 percent Confidence Interval.
LiDAR Data Processing. Flight lines and data were reviewed to ensure complete coverage of the study area and positional accuracy of the laser points. Laser point return coordinates were computed using ALS Post Processor software and IPAS Pro GPS/INS software, based on independent data from the LiDAR system, IMU, and aircraft. The raw LiDAR file was assembled into flight lines per return with each point having an associated x, y, and z coordinate. Visual inspection of swath to swath laser point consistencies within the study area were used to perform manual refinements of system alignment. Custom algorithms were designed to evaluate points between adjacent flight lines. Automated system alignment was computed based upon randomly selected swath to swath accuracy measurements that consider elevation, slope, and intensities. Specifically, refinement in the combination of system pitch, roll and yaw offset parameters optimize internal consistency. Noise (e.g., pits and birds) was filtered using ALS post-processing software, based on known elevation ranges and included the removal of any cycle slips. Using TerraScan and MicroStation, ground classifications utilized custom settings appropriate to the study area. The corrected and filtered return points were compared to the RTK ground survey points collected to verify the vertical and horizontal accuracies. Points were output as laser points, TINed and GRIDed surfaces.
2013-11-22
Acquisition. LiDAR data acquisition was started September 28, 2013 and is still ongoing. The survey is utilizing a Leica ALS50 or ALS70 laser system mounted in a Piper Navajo PA-31-325 or Cessna Caravan 208B. Near nadir scan angles were used to increase penetration of vegetation to ground surfaces. Ground level GPS and aircraft IMU were collected during the flight.
2013-11-22
385873
0.979598
463047
0.979598
2
1
0
6119016.656046 1797201.893708
6119016.656046 2250801.921360
6497017.168888 2250801.921360
6497017.168888 1797201.893708
6308016.912467 2024001.907534
Band_1
32
This raster data set represents ground surface elevations derived from ground classified LiDAR point data.
WSI
dataset
20230602