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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
20250411
ArcGIS Metadata
1.0
Sonoma County Agricultural Preservation and Open Space District
(707) 565-7369
747 Mendocino Ave, Suite 100
Santa Rosa
CA
95401
US
Lidar_Canopy_Density_2013
2014-02-19
Sonoma County Vegetation Mapping and LiDAR Program
raster digital data
<div style='text-align:Left;'><div><div><p style='margin:0 0 11 0;'><span>This intensity raster depicts the aboveground LiDAR return to the total count LiDAR return and provides a ratio of the two from 0.0 to 1.0, where 0.0 represents no canopy and 1.0 very dense canopy. Each image corresponds to a 37,800-square-foot tile. Each pixel is 3 feet and represents an average intensity 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 all of Sonoma County. WSI collected the LiDAR and created this data set for the Sonoma County Vegetation Mapping and LiDAR Consortium.</span></p><p style='margin:0 0 11 0;'><span /></p><p><span /></p></div></div></div>
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.
A pixel value of 0.0 represents no canopy and a pixel value of 1.0 represents very dense canopy.
Sonoma County Vegetation Mapping and LiDAR Consortium, NASA, University of Maryland, Watershed Sciences, Inc., Tukman Geospatial LLC
Sonoma County, Lake Mendocino, Sonoma Lake Watershed
LiDAR, Light Detection And Ranging
LiDAR
Light Detection And Ranging
Sonoma County
Lake Mendocino
Sonoma Lake Watershed
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.
<div style='text-align:Left;'><div><div><p><span style='font-size:10pt'>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). </span></p><p><span style='font-size:10pt'>You are free to: Share - copy and redistribute the data in any medium or format. Adapt - You may make derivative works, transform, and build upon the data for any purpose, even commercial. The licensor cannot revoke these freedoms as long as you follow the license terms.</span></p><p><span style='font-size:10pt'>License terms: Attribution - You must give appropriate credit (if supplied, you must provide the name of the creator and attribution parties, a copyright notice, a license notice, a disclaimer notice and a link to the material) and indicate if any changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you, your organization, or your use of the data. ShareAlike - if you modify, transform, or build on the data, you must distribute your contributions under the same license as the original.</span></p><p><span style='font-size:10pt'>No additional Restrictions - You may not apply legal terms or technological measures that legally restrict others form doing anything the license permits.</span></p><p><span style='font-size:10pt'>Notices: You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the data.</span></p><p><span style='font-size:10pt'>EXCEPT TO THE EXTENT REQUIRED BY APPLICABLE LAW, IN NO EVENT WILL LICENSOR BE LIABLE TO YOU ON ANY LEGAL THEORY FOR ANY SPECIAL, INCIDENTAL, CONSEQUENTIAL, PUNITIVE OR EXEMPLARY DAMAGES ARISING OUT OF THIS LICENSE OR THE USE OF THE DATA, EVEN IF LICENSOR HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.</span></p><p><span style='font-size:10pt'>The above is an easily understandable summary of and not a substitute for the license and disclaimer for the Attribution-ShareAlike 3.0 United States (CC BY-SA 3.0 US) the full text is available at creativecommons.org.</span></p><p><span style='font-size:10pt'>https://creativecommons.org/licenses/by-sa/3.0/us/legalcode</span></p></div></div></div>
Ground Condition - LiDAR: Leica ALS50 & Leica ALS70
2013-09-28
2013-11-26
-123.238581
-122.390681
38.298129
38.511668
Microsoft Windows Server 2016 Technical Preview Version 10.0 (Build 17763) ; Esri ArcGIS 13.4.0.55405
1
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A pixel value of 0.0 represents no canopy and a pixel value of 1.0 represents very dense canopy.
LiDAR has been collected and processed throughout study area. 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). In some areas of heavy vegetation and forest cover, there may be relatively few ground points in the LiDAR data. TINing the points produces large triangles and hence the elevations may be less accurate within such areas. In some areas with large bodies of water, competing water surface levels may be visible. This is due to seasonal water level fluctuation and intervals of time between acquisition of an area.
LiDAR has been collected and processed for all areas within the project study Area. For Canopy Cover, First-Return, only the highest hits, are shown (e.g. tree-tops, roofs, etc.). 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 was examined at a 1:3000 scale.
Relative Accuracy measures the divergence between points from different flightlines. Relative Accuracy median is 0.05 meters (0.17 feet) out of 106,255,665,985 laser points over 4,133 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 0.03 meters (0.09 feet). Accuracy was assessed using 9,685 ground control (real time kinematic) points. These ground control points are distributed through out the project study area. Supplemental Vertical Accuracy (SVA) is reported as the deviation between landcover classified laser points and landclass checkpoints at the 95th percentile. The SVA for individual land classes are 0.27 meters for shrub, 0.09 meters for short grass, 0.19 meters for tall grass, 0.19 meters for mixed forest, 0.05 meters for developed areas, 0.12 for herbaceous upland natural areas, 0.05 for non-natural woody areas and 0.07 for barren areas. The supplemental vertical accuracies were calculated using 417 individual landclass checkpoints. Consolidated Vertical Accuracy (CVA) is reported as the deviation between both ground and landcover classified laser points from all survey checkpoints, reported at the 95th percentile. CVA for this dataset is 0.06 meters, and was calculated from 10,102 ground and landclass checkpoints. See LiDAR data report.
The FVA was tested using 851 independent ground control points (GCPs) 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 0.03 m (0.09 ft.). AccuracyZ has been tested to meet 0.05 m (0.18 ft.) 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.
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Sonoma County Vegetation Mapping and LiDAR Program
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