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<tmEnd>2018-09-16</tmEnd>
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<idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;This shapefile represents the water's edge breaklines used to control the extent of refracted green laser returns. These lines were also used to classify water within the .las point cloud. Water boundary polygons were developed using an automated algorithm which weights LiDAR-derived slopes, intensities, and return densities to detect the water's edge, and then manually edited as needed. The horizontal datum for this dataset is NAD83 (2011), the vertical datum is NAVD88, Geoid 12B, and the data is projected in UTM Zone 10N. Units are in Meters. Quantum Spatial collected the Lake Tahoe LiDAR data for Spatial Informatics Group between 09/09/18 and 09/16/18.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
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<keyword>Water's Edge</keyword>
<keyword>California and Nevada</keyword>
<keyword>Lake Valley</keyword>
<keyword>Camp Richardson</keyword>
<keyword>Spring Creek</keyword>
<keyword>Emerald Bay</keyword>
<keyword>Rubicon Bay</keyword>
<keyword>Meeks Bay</keyword>
<keyword>Tahoma</keyword>
<keyword>Chambers Lodge</keyword>
<keyword>Homewood</keyword>
<keyword>McKinney Bay</keyword>
<keyword>Tahoe Pines</keyword>
<keyword>Hurricane Bay</keyword>
<keyword>Tahoe City</keyword>
<keyword>Dollar Point</keyword>
<keyword>Ridgewood</keyword>
<keyword>Carnelian Bay</keyword>
<keyword>Tahoe Vista</keyword>
<keyword>Agate Bay</keyword>
<keyword>Kings Beach</keyword>
<keyword>Crystal Bay</keyword>
<keyword>Glenbrook</keyword>
<keyword>Glenbrook Bay</keyword>
<keyword>Lincoln Park</keyword>
<keyword>Lakeridge</keyword>
<keyword>Skyland</keyword>
<keyword>Zephyr Cove</keyword>
<keyword>Stateline</keyword>
<keyword>Maria Bay</keyword>
<keyword>Elk Point</keyword>
<keyword>Bijou</keyword>
<keyword>South Lake Tahoe</keyword>
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<useLimit>Please contact Spatial Informatics Group for information regarding the use of this data.</useLimit>
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<adminArea>California</adminArea>
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<measDesc>LiDAR data has been collected and processed for all areas within the project study area.</measDesc>
<evalMethDesc>Flight plans are designed with sufficient sidelap to ensure there are no gaps between flightlines. Shaded relief images have been visually inspected for gaps.</evalMethDesc>
</report>
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<measDesc>Shaded relief images have been visually inspected for data errors such as pits, border artifacts, and shifting. LiDAR flightlines have been examined to ensure consistent elevation values across overlapping flightlines. The Root Mean Square Error (RMSE) of line to line relative accuracy for this dataset is 0.045 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.</measDesc>
<evalMethDesc>Data was examined at a 1:2000 scale. Relative accuracy of the flightlines was assessed in Microstation using TerraMatch. </evalMethDesc>
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<measDesc>The Non-vegetated Vertical Accuracy (NVA) of this dataset, tested at 95% confidence level is 0.083 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.</measDesc>
<evalMethDesc>Non-vegetated Vertical Accuracy was assessed using 44 ground check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data. </evalMethDesc>
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<measDesc>The Vegetated Vertical Accuracy (VVA) of this dataset, evaluated at the 95th percentile is . Please see the LiDAR data report for a discussion of the statistics related to this dataset.</measDesc>
<evalMethDesc>Vegetated Vertical Accuracy was assessed using VVA check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data. </evalMethDesc>
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&gt;
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<stepDesc>Acquisition. Quantum Spatial collected the Lake Tahoe LiDAR data between 09/09/18 and 09/16/18. The survey used a Riegl VQ-880-G laser system mounted in a Cessna Caravan. Ground level GPS and aircraft IMU were collected during the flight. Sensor: Riegl VQ-880-G
Maximum returns: unlimited
Nominal pulse density: 12 pulses/m^2
Nominal pulse spacing: 0.29 m
AGL: 500 m
Speed: 110 knots
FOV: 40°
Scan frequency: 80 lines per second
Pulse rate: 516.4 kHz
Pulse duration: 1.5 ns
Pulse width: 35 cm
Wavelength: 532 nm
Pulses in air mode: Multiple Times Around (MTA)
Beam divergence: 0.7 mrads
Swath width: 364 m
Overlap: 30%
Sensor: Riegl VQ-880-IR
Maximum returns: unlimited
Nominal pulse density: 12 pulses/m^2
Nominal pulse spacing: 0.29 m
AGL: 500 m
Speed: 110 knots
FOV: 40°
Scan frequency: Uniform Point Spacing
Pulse rate: 245 kHz
Pulse duration: 3 ns
Pulse width: 10 cm
Wavelength: 1064 nm
Pulses in air mode: Multiple Times Around (MTA)
Beam divergence: 0.2 mrads
Swath width: 364 m
Overlap: 30%
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<stepDateTm>2018-09-16</stepDateTm>
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<stepDesc>Water boundary polygons were developed using an algorithm which weights LiDAR-derived slopes, intensities, and return densities to detect the water's edge. </stepDesc>
<stepDateTm>2018-12-14</stepDateTm>
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<measDesc>Vertical accuracy was also assessed using ground control points that were used in the calibration and post processing of the LiDAR point cloud as they still serve as a good indication of the overall accuracy of the LiDAR dataset. The Root Mean Square Error (RMSE) of the vertical accuracy of the LiDAR dataset as compared to ground control points is 0.039 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.</measDesc>
<evalMethDesc>836 ground control points were collected and utilized in the calibration and post processing of the LiDAR data point cloud.</evalMethDesc>
<measResult>
<QuanResult>
<quanValType>RMSE</quanValType>
<quanVal>0.039</quanVal>
<quanValUnit>
<UOM>
<unitSymbol>m</unitSymbol>
</UOM>
</quanValUnit>
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</report>
<report dimension="vertical" type="DQQuanAttAcc">
<measDesc>Vertical accuracy was also assessed using bathymetric bottom check points collected over submerged bathymetric terrain. The Root Mean Square Error (RMSE) of the vertical accuracy of the LiDAR dataset as compared to bathymetric check points is 0.078 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.</measDesc>
<evalMethDesc>Bathymetric bottom vertical accuracy was assessed using 199 bathymetric bottom check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data.</evalMethDesc>
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<QuanResult>
<quanValType>RMSE</quanValType>
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<report dimension="vertical" type="DQQuanAttAcc">
<measDesc>Vertical accuracy was also assessed using wetted edge check points collected at the interface between water and terrain. The Root Mean Square Error (RMSE) of the vertical accuracy of the LiDAR dataset as compared to wetted edge check points is 0.065 m. Please see the LiDAR data report for a discussion of the statistics related to this dataset.</measDesc>
<evalMethDesc>Wetted edge vertical accuracy was assessed using 17 wetted edge check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data.</evalMethDesc>
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<quanValType>RMSE</quanValType>
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