20170607
14555500
1.0
FGDC CSDGM Metadata
FALSE
DEM_SalchaFloodStudy_2016_HydroEnforced.img
file://K:\gis\rasters\DEM_SalchaFloodStudy_2016_HydroEnforced.img
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20180319
13122900
20180319
13122900
150000000
5000
Quantum Spatial
2014 Merrill Field Drive
Anchorage
AK
99501
US
907-272-4495
http://www.quantumspatial.com
Quantum Spatial
Quantum Spatial
1
Raster Dataset
Nancy Durham
Fairbanks North Star Borough
809 Pioneer Road
Fairbanks
Alaska
99701
ndurham@fnsb.us
US
907-459-1263
raster digital data
Quantum Spatial
2014 Merrill Field Drive
Anchorage
AK
99501
US
907-272-4495
http://www.quantumspatial.com
Quantum Spatial
2016-07-01
Elevation_2016_DEM_Salcha_Flood_Study
Tanana River Floodplain Mapping LiDAR
2016-04-30
2016-04-30
Provide high resolution terrain elevation data from the Tanana River Floodplain Mapping LiDAR dataset.
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The hydro-flattened and enforced bare earth digital elevation model (DEM) represents the earth's surface with all vegetation and human-made structures removed. It is derived from NIR LiDAR data using TIN processing of the ground point returns. All rivers greater than 30 meters in width and lakes at least 2 acres in size (and smaller as feasible) have been flattened to consistent elevations. Water boundary polygons were developed using an algorithm which weights LiDAR-derived slopes, intensities, and return densities to detect the water's edge. Elevation values were then assigned to the water's edge from the LiDAR data creating 3D breaklines enforced during model creation to flatten water bodies. Additionally, hydro-enforcement breaklines were created at all artificial obstructions to flow found in the ground model (i.e. culverts) to break the obstruction and allow flow to continue. Some elevation values have been interpolated across areas in the ground model where there is no elevation data (e.g. under dense vegetation). The horizontal datum for this dataset is NAD83 (CORS96), the vertical datum is NAVD88, Geoid 06, and the data is projected in Alaska State Plane Coordinate System Zone 3. Units are in U.S. Survey Feet. Quantum Spatial collected the Tanana River Floodplain Mapping LiDAR data for the Fairbanks North Star Borough on 04/30/2016.</SPAN></P></DIV></DIV></DIV>
Fairbanks North Star Borough
LiDAR
Light Detection and Ranging
elevation data
topography
bare earth
hydro-flattened
hydro-enforced
breaklines
DEM
digital elevation model
Fairbanks North Star Borough
Alaska
Floodplain
Mapping
LiDAR
DEM
LiDAR, Light Detection and Ranging, elevation data, topography, bare earth, hydro-flattened, hydro-enforced, breaklines, DEM, digital elevation model
Fairbanks North Star Borough
Alaska
Floodplain, Mapping, LiDAR, DEM
3
This data is assembled by AOI and projected in Alaska State Plane Coordinate System Zone 3.
Nancy Durham
Fairbanks North Star Borough
809 Pioneer Road
Fairbanks
Alaska
99701
ndurham@fnsb.us
US
907-459-1263
Nancy Durham
Please contact the Fairbanks North Star Borough for information regarding the use of this data.
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>In some areas of heavy vegetation or 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. Elevation values for open water surfaces are derived from waters edge breaklines. Triangles were created across water surfaces by interpolating from the nearest breakline elevation points.</SPAN></P></DIV></DIV></DIV>
Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.4.1.5686
1
-147.378923
-147.049748
64.725523
64.560094
LiDAR data has been collected and processed for all areas within the project study area.
Flight plans are designed with sufficient sidelap to ensure there are no gaps between flight lines. Shaded relief images have been visually inspected for gaps.
Shaded relief images have been visually inspected for data errors such as pits, border artifacts, and shifting. LiDAR flight lines have been examined to ensure consistent elevation values across overlapping flight lines. The Root Mean Square Error (RMSE) of line to line relative accuracy for this dataset is 0.049 ft (0.015 m). Please see the LiDAR data report for a discussion of the statistics related to this dataset.
Data was examined at a 1:2000 scale. Relative accuracy of the flight lines was assessed in Microstation using TerraMatch.
RMSE
ft_US
0.049 ft (0.015 m)
The Non Vegetated Vertical Accuracy (NVA) of this dataset, tested at 95% confidence level is 0.295 ft (0.090 m). Please see the LiDAR data report for a discussion of the statistics related to this dataset.
Non Vegetated Vertical Accuracy was assessed using 61 ground check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data.
NVA
ft_US
0.295 ft (0.090 m)
Acquisition. Quantum Spatial collected the Tanana River Floodplain Mapping LiDAR data on 04/30/2016. The survey used a Leica ALS80 laser system mounted in a Cessna Caravan. Data was collected using a dual pulse flight plan. Ground level GPS and aircraft IMU were collected during the flight. Leica ALS80 Instrument Parameters:
Beam diameter: 37.4 cm,
Pulse rate: 324.80 kHz,
Maximum returns: 4,
Speed: 145 knots,
Overlap: 60 %,
Laser power: 100 %,
Field of view (FOV): 32°,
Beam wavelength: 1064 nm,
Frequency of GPS sampling: 2 Hz,
Frequency of IMU sampling: 200 Hz,
Swath width: 977 m,
AGL: 1700 m,
Average pulse density: 2
2016-04-30
1. Flight lines and data were reviewed to ensure complete coverage of the study area and positional accuracy of the laser points. 2. Laser point return coordinates were computed using ALS Post Processor and IPAS TC software based on independent data from the LiDAR system, IMU, and aircraft. 3. The raw LiDAR file was assembled into flight lines per return with each point having an associated x, y, and z coordinate. 4. Visual inspection of swath to swath laser point consistencies within the study area were used to perform manual refinements of system alignment. 5. 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.
6. Noise (e.g., pits and birds) was filtered using ALS postprocessing software, based on known elevation ranges and included the removal of any cycle slips. 7. Using TerraScan and Microstation, ground classifications utilized custom settings appropriate to the study area. 8. The corrected and filtered return points were compared to the RTK ground survey points collected to verify the vertical accuracy. 9. TIN processing of the ground point returns with water's edge and hydro-enforcement breaklines enforced was used to create this hydro-flattened and enforced bare earth DEM.
2016-07-01
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 0.094 ft (0.029 m). Please see the LiDAR data report for a discussion of the statistics related to this dataset.
331 ground control points were collected and utilized in the calibration and post processing of the LiDAR data point cloud.
RMSE
0.094 ft (0.029 m)
16831
3.000000
19850
3.000000
2
1
0
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ft_US
Layer_1
671.049988
500.320007
32
Digital Elevation Model
False
False
False
False
False
dataset
Esri
8.0.1
20180319