Raster Dataset
Tags
elevation, environment, geoscientific information, DEM, LiDAR, topography, hypsography
Summary
To provide a very accurate DEM of the Assiniboine River area.
Description
The Assiniboine River LiDAR data is a raster layer in ArcInfo grid format. This dataset combines LiDAR captured in May 2007 and October 2008. In 2007, LiDAR data was captured within a 1.5km buffer of the Assiniboine River from the Shellmouth Dam to just downstream of the City of Brandon. Because the 2007 LiDAR was flown at bankfull stage, a 175m buffer of the river was re-flown in October 2008 when water levels were within operational levels of the Shellmouth Dam.
Credits
This data set was developed for Province of Manitoba by LiDAR Services International Inc.
Access and use limitations
none
The Assiniboine River LiDAR data is a raster layer in ArcInfo grid format. This dataset combines LiDAR captured in May 2007 and October 2008. In 2007, LiDAR data was captured within a 1.5km buffer of the Assiniboine River from the Shellmouth Dam to just downstream of the City of Brandon. Because the 2007 LiDAR was flown at bankfull stage, a 175m buffer of the river was re-flown in October 2008 when water levels were within operational levels of the Shellmouth Dam.
To provide a very accurate DEM of the Assiniboine River area.
none
This data set was developed for Province of Manitoba by LiDAR Services International Inc.
The Assiniboine River LiDAR data is a raster layer in ArcInfo grid format. This dataset combines LiDAR captured in May 2007 and October 2008. In 2007, LiDAR data was captured within a 1.5km buffer of the Assiniboine River from the Shellmouth Dam to just downstream of the City of Brandon. Because the 2007 LiDAR was flown at bankfull stage, a 175m buffer of the river was re-flown in October 2008 when water levels were within operational levels of the Shellmouth Dam.
To provide a very accurate DEM of the Assiniboine River area.
LiDAR data was collected using LiDAR Services International's (LSI) proprietary Helix LiDAR system - Novatel GPS and IMAR inertial unit, coupled to a Riegl Q560 digital waveform ranging laser and mounted in a Partinavia P68 Observer aircraft. LiDAR was collected at 600m AGL, and a ground speed of 225km/h.
ground condition
none
This data set was developed for Province of Manitoba by LiDAR Services International Inc.
Ground points were initially classified using an automatic classification routine. The ground surface model was edited and verified by creating a shaded relief model and identifying erroneous points and voids in the ground surface.
Data was verified by viewing shaded relief models. Points were checked against those from adjacent flightlines to ensure positional accuracy. The intensity of the LiDAR returns was viewed and compared against adjacent data to verify horizontal positional accuracy.
Horizontal accuracy is verified by comparison of horizontally identifiable features in the LiDAR data against similar features in another flightline of LiDAR data over the same geographic area.
Vertical accuracy is verified by comparison of points from the calibration flights to conventionally surveyed ground points at the calibration site.
Number of points 63 Average delta height (m) 0.093 Root mean square (m) 0.114 Standard Deviation (m) 0.067
At the Russell Airport: Number of points 300 Average delta height (m) 0.044 Root mean square (m) 0.076 Standard Deviation (m) 0.062
Control point used to build GPS network from which positions of kinematic GPS solution and calibration points were derived. NAD83 published coordinates are Lat: 50 26 09.92130, Long: -101 28 37.19845, Ellipsoid Height: 457.668m. Adjusted coordinates used for LiDAR positioning are Lat: 50 26 09.90287, Long: -101 28 37.19811, Ellipsoid Height: 457.635m. This point was occupied during kinematic GPS collection.
Control point used to build GPS network from which positions of kinematic GPS solution and calibration points were derived. NAD83 published coordinates are Lat: 49 43 27.4243, Long: -100 27 47.4164, Ellipsoid Height: 407.45m. Adjusted coordinates used for LiDAR positioning are Lat: 49 43 27.42433, Long: -100 27 47.41521, Ellipsoid Height: 407.407m. This point was occupied during kinematic GPS collection.
Control point used to build GPS network from which positions of kinematic GPS solution and calibration points were derived. NAD83 published coordinates are Lat: 50 04 10.6320, Long: -100 53 49.2559, Orthometric Height: 461.838m. Adjusted coordinates used for LiDAR positioning are Lat: 50 04 10.63183, Long: -100 53 49.25556, Ellipsoid Height: 438.786m. This point was occupied during kinematic GPS collection.
Control point used to build GPS network from which positions of kinematic GPS solution and calibration points were derived. NAD83 published coordinates are Lat: 49 53 09.2927, Long: -99 54 41.0582, Ellipsoid Height: 373.82m. Adjusted coordinates used for LiDAR positioning are Lat: 49 53 09.29240, Long: -99 54 41.05783, Ellipsoid Height: 373.848m. This point was occupied during kinematic GPS collection.
Control point used to build GPS network from which positions of kinematic GPS solution and calibration points were derived. Control and coordinates established in 2007. Coordinates used for LiDAR positioning are Lat: 50 46 11.65631, Long: -101 17 43.14824, Ellipsoid Height: 532.528m. This point was occupied during kinematic GPS collection.
Kinematic GPS data was processed using adjusted coordinates. Kinematic GPS and inertial information were combined to create the final position and attitude trajectories. The position and attitude trajectories were combined with data from the scanning laser to produce a raw XYZ point cloud.
Overlapping flight lines were compared at the calibration site and within the project area to determine the boresight corrections required to remove systematic errors. Raw point clouds were generated using the attitude information and scanning laser ranges.
Raw XYZ point clouds were combined and divided into 1km x 1km tiles. Redundant data between overlapping flightlines was removed.
LiDAR data was adjusted from ellipsoid to orthometric elevation using the CGVD28 height model.
An automatic ground classification routine was run on the LiDAR data using TerraScan, and the results were verified by viewing a shaded relief model. Points that existed above ground were classified to vegetation and then buildings were classified manually from the vegetation points using the shaded relief model to identify them. Points that could not be identified as vegetation or ground were classified as non-ground; bridges and transmission lines were classified to non-ground.
Gridded ASCII XYZ files with a horizontal spacing of 1m were created in TerraScan. Elevations were derived from triangle facets in the TIN model (built using ground points only) at the centre of the grid cell.
Gridded ASCII XYZ files with a horizontal spacing of 1m were created in TerraScan representing the ground, vegetation, building, and non-ground points. Elevations were derived from the highest point elevation within the grid cell.
Bare earth 1m grids in ascii (x,y,z) format were received from LSI in 2007 and 2008. The files were unzipped and the file extensions were renamed to .txt. An AML called td_lidar_fm_files.aml was run against the text files to create point coverages. Another AML called td_lidar_grid.aml was used to create 1-metre rasters in ArcInfo GRID format.
Rasters were mosaicked separately for 2007 and 2008 by loading them into file geodatabase raster catalogs. The Raster Catalog to Raster Dataset tool was used to mosaic the contents of the raster catalogs into new 32-bit-float raster datasets.
Nodata slivers in the 2008 data were corrected using the Focal Statistics tool. Nodata cells were masked out and mean values were reported using a 3x3 cell neighborhood.
2007 and 2008 rasters were mosaicked using the Mosaic to New Raster tool. 2008 cell values took precedence in overlap areas.
The only attributes assigned were point classification during the processing phase using TerraScan. See process steps for details.
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