Full-color, fli-map, LiDAR, FLI-MAP, intensity image, Elm Creek, FLIMAP, Light Detection and Ranging, flimap, Intensity, intensity, Linescan, topography, Manitoba, high-resolution
Dataset created under request from Manitoba Infrastructure and Transportation
1 m resolution bare-earth DEM obtained from ground filtering of FLI-MAP LiDAR survey data in the Elm Creek project region.
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Data not to be used beyond the limits of the source scale
|Maximum (zoomed in)||1:5,000|
|Minimum (zoomed out)||1:150,000,000|
LiDAR Acquisition LiDAR acquisition for this project was performed by Fugro Horizons in a Twin Cessna 310 equipped with a Flimap Fx LiDAR system including an inertial measuring unit (IMU) and a dual frequency GPS receiver. Acquisition was accomplished between October 2nd 2012 and October 11th 2012. The LiDAR flight specifications follow: Field of View: 60 Degrees Altitude:2100 feet AMT Scan Rate:50 rps Pulse Rate:200 kHz Airspeed:130 knots Average Post Spacing: 4pts/m^2 Average Swath Width: 650 Meters Total Flight Lines: 47 Number of Lifts: 4 GPS Data Collection A GPS receiver was in constant operation over a control point during flight acquisition. The base station identification and location are listed in the following table. Base S1:49 48 46.10892, 97 58 57.04743, 220.363 Base S1a: 49 48 46.15541, 97 58 53.93487, 220.260 Base S2: 49 42 52.08990, 98 11 14.27833 , 265.333 Base S2a: 49 42 55.97045, 98 11 14.13693, 265.965 GPS Data Processing All GPS phase data was post processed with continuous kinematic survey techniques using “On the Fly” (OTF) integer ambiguity resolution. The GPS data was processed with forward and reverse processing algorithms. The results from each process, using the data collected at the airport, were combined to yield a single fixed integer phase differential solution of the aircraft trajectory. The differences between the forward to reverse solution within the project area were within project specifications (<10cm) in both the horizontal and vertical components, indicating a valid and accurate solution. IMU Data Processing An IMU (inertial measurement unit) was used to record precise changes in position and orientation of the LIDAR scanner at a rate of 200 Hz. All IMU data was processed post flight with a filter to integrate inertial measurements and precise phase differential GPS positions. The resulting solution contains geodetic position, omega, phi, kappa, and time for subsequent merging with the laser ranging information.
Data not to be used beyond the limits of the source scale
LIDAR Data Preprocess: (1) Flight Line Data Acquisition/Quality Control Check: LiDAR data and the IMU files were processed together using LIDAR processing software. The data set for each flight line was checked for project area coverage, data gaps between overlapping flight lines, and tension/compression areas (areas where data points are more or less dense than the average project specified post spacing). Based on this check it appears the entire project area is covered without gaps. (2) Boresighting Process: Pre-processing of LiDAR corrects for rotational, atmospheric, and elevation differences that are inherent to LiDAR data sets. This process is called boresighting. LiDAR data was collected for bi- and cross-directional flight lines over the project area. Using an iterative process that involves analyzing raster difference calculations the Omega, Phi, Kappa angle corrections of the LiDAR instrument were determined. The corrections were applied to the LiDAR data set for the project area. (3) Vertical Accuracy Check: Extensive comparisons were made of vertical and horizontal positional differences between points common to two or more LiDAR flight lines. This was done for the project area. All flight lines were within project specifications for vertical accuracy. (4) LiDAR Intensity Check: An intensity raster for each flight line was generated. The raster was checked and verified that intensity was recorded for each LiDAR point. (5) Project Coordinate System: LiDAR preprocessing software outputs data to its corresponding UTM zone in meters and a GRS80 ellipsoidal height. LiDAR data was transformed to a project coordinate system of NAD83 UTM zone 14 N CGVD 28 Geoid HT 2.0 Meters. (6) Vertical Bias Correction: LiDAR has a consistent vertical offset. LiDAR ground points were compared to independently surveyed and positioned ground control points at both the airport bore-sight area and the project area. Based on the results of these comparisons, the LiDAR data was vertically biased down to the ground. (7) Project Ground Control Check: Comparisons between on-site ground survey control points and LiDAR data.
LiDAR Data Surfacing Process: (1) Raw LiDAR Data Set: LiDAR data in overlap areas of project flight lines was removed and data from all swaths was merged into a single data set. The data set was trimmed to the digital project boundary including an additional buffer zone (buffer zone assures adequate contour generation from the DEM). Resulting data set is the Raw LiDAR data. The Raw LiDAR data set was processed through a minimum block mean algorithm and points were classified as either bare earth or non-bare earth. User developed “macros” that factor mean terrain angle and height from the ground, were used to determine bare earth point classification. (2) LiDAR Surfacing Process: The surfacing process is a 2D-edit procedure that ensures the accuracy of the automated feature classification. Editors used a combination of imagery, intensity of the LiDAR reflection and tin-editing software to assess points. The resulting data set is 2D Surfaced Bare Earth. The LiDAR data is filtered using a quadric error metric to remove redundant points. This method leaves points where there is a change in the slope of surfaces (road ditches) and eliminates points from evenly sloped terrain (flat field) where the points do not affect the TIN LiDAR data. The resulting data set is 2D Surfaced/Filtered Bare Earth