CHC AA450 & AU10 LiDAR

Overview

Flights were performed using the X500 RTK drone. The drone was connected via APIS RTK stream during flight, data was later PPK processed. Each sensor was flown at 50m and 100m above ground level.

Data was copied to desktop PC, and post-processed using CoPre2 desktop post-processing suite to generate and export a LiDAR point cloud.

Using CoProcess2 terrain tools, the point cloud was processed to a ground filtered DEM surface using the same automated tool and parameters for each dataset. Height accuracy values were reported against GPS measurements using CoProcess2 'Check DEM' function.

GPS check data was collected using i83 base and i89 rover RTK GNSS. Points were separated into 'TOPO' with 75+ topographic shots throughout the scene and 'GCP' with a limited number of spray painted GCP targets on asphalt.

Coordinate system is New Mexico Central (ftus) Geoid18US.

TOPO check shots were collected using 2-10 epoch measurements, careful not to drive tip in ground, with roughly half collected at a time 6 days apart.

GCP check shots were collected using 10-15 epoch measurements and each point is a point average made up of 3-4 groupings. Day 1 each GCP was shot once, and the pole was rotated 180 deg. Additional groupings occurred at different times of day and across 6 day period.

Specifications and Example Results

Sample Data

[ AA450 & AU10 Sample Data Downloads ]

Sample Data Directory Structure

|_AA450_vs_AU10

|

|__AA450_vs_AU10_Data.pdf (summary of measurements)

|

|___1-GNSS

|____LandStar8_Project (folder, .zip of LandStar8 project for check data)

|____RINEX (folder, base static file for CoPre post-processing)

|____AA450_vs_AU10_GCP_LST_SQ.pdf (least squares report generated in LandStar for GCP)

|____AA450_vs_AU10_PCNEZ_USFT_GCP.csv (GCP shots)

|____AA450_vs_AU10_PCNEZ_USFT_TOPO.csv (75+ TOPO shots)

|____copre_coordinate_system.crd (used to select New Mexico Central ftus GEOID18 in CoPre)

|

|___2-Raw (folder, labeled full raw folder, copied from payload to PC)

|

|___3-Processing (folder, labeled CoPre projects folders, and contains CoProcess files)

|

|___4-Deliverable (folder, example for each payload and altitude)

|____SENSOR_ALTITUDE

|______Point Cloud (.las)

|______DEM ground filtered surface (.tif)

|______Check_DEM results export compared to TOPO shots (.csv)

Scanning

• Flight time for each payload is from SmartGo mission planner estimate
• Collect Time represents real flight time + time each sensor required on ground before and after takeoff
• Area covered is an estimate of acres from Pix4D Mapper processing of imagery

Each scanning mission was planned with 80% front overlap, 75% side overlap, and 7 m/s flight speed. These selections can be changed and were the defaults after selecting each payload and altitude.

100m AGL Mission

50m AGL Mission

CoPre Point Cloud Processing

[ See CoPre Point Cloud Processing Video ]

CoPre2 Post Processing

1. Import raw project data, use Auto Solve wizard

2. Select state plane coordinate system and geoid

3. Import base RINEX for PPK trajectory processing

4. Set noise filtering, and minimum distance from sensor filtering

5. Process images, turn off colorization (if colorization desired, use 'remove unshaded points' feature')

6. After Auto Solve, a .LAS is saved to project directory, JPG images are saved with a 'metashape.txt' file containing position and orientation data

7. Optionally, import GCP file and process orthomosaic in CoPre

'Remove unshaded points' when colorizing provides a high quality colorized point cloud. In some cases it can also cut the point cloud density by half or more. Processing without colorization provides maximum point cloud density.

CoProcess 2 DEM Processing

[ See CoProcess 2 DEM Video ]

CoProcess2 Ground Filtering and DEM

1. Import georeferenced point cloud
2. Select 'Terrains > Wizard' and 'Advanced Settings'
3. Break the job down into blocks, or process as single block
4. Choose whether to classify buildings and vegetation, or to just classify ground
5. Set ground filtering parameters for terrain
6. Set DEM resolution
7. Wizard will process and classify, when finished saving .tif DEM ground surface in same directory as .LAS
8. 'Check DEM' function used to bring in ground points and compare to the DEM surface

Point Cloud Comparison

[ See all sample data ]

Ground Filtered DEM Surface Check Shots

Using CoProcess2, a ground filtered DEM surface was created and exported as a .tif file and compared to TOPO check shots.

Point Cloud Density and Noise

Point cloud density in 1 sq/m area was measured using CoPre, selecting the same position in each cloud at a visible asphalt imperfection.

Point cloud vertical noise was measured using a .1 sft wide strip along asphalt centerline.

AA450 @50m AGL Intensity

AU10 @50m AGL Intensity

AA450 @50m AGL Intensity Blue, Green, Yellow, Red

AU10 @50m AGL Intensity Blue, Green, Yellow, Red

AA450 @50m AGL Intensity Top View

AU10 @50m AGL Intensity Top View

AA450 @100m AGL Vertical Noise

AU10 @100m AGL Vertical Noise

AA450 @50m AGL Vertical Noise

AU10 @50m AGL Vertical Noise

Camera Comparison

[ See all sample data ]

AA450 & AU10 payload datasheets show a 26mp and 24.3mp camera. In our testing, we found the camera in each payload to be the same model and specification. We see this in the data with the GSD and 3D RMS reported from Pix4D Mapper matching for each sensor at each altitude.

Orthomosaic Snapshot @50m AGL

GSD and 3D RMS Reported by Pix4D Mapper

Pix4D Mapper Camera Detail Matches

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