RGCP-SEDQ_LiDAR_and_Orthoimagery_Report_2021_12_22.pdf

USIBWC – Rio Grande Canalization Project – LiDAR and Orthophotography Report Wilson & FNI JV June 12th, 2020 0

International Boundary and Water Commission

Rio Grande Canalization Project - LiDAR and Orthophotography Report

Submitted: 6/12/2020

4401 Masthead Street NE Suite 150, Albuquerque, NM 87109

505-348-4000 phone

505-348-4055 fax

Wilson & FNI JV June 12th, 2020 0

LiDAR and Orthophotography

Table of Contents 1 Project Overview

1.1 Rio Grande Canalization Project

1.2 Project Area

1.3 LiDAR and Ortho Area

2 Acquisition

2.1 Flightline Index

3 Remotely Sensed Data Post-Processing, Calibration, and Relative Accuracy

4 Aerial Mapping Targets and Control Points

5 Orthophotography

6 LiDAR Processing

6.1 LiDAR Specification

6.2 LiDAR Vertical Accuracy Assessment

7 Hydro-flattening of the Bare Earth

8 Orthophotography and LiDAR Tiling Scheme

9 Deliverables

Appendix I Professional Land Surveyor Certification

Appendix II City Mapper Calibration Report

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1 Project Overview

Rio Grande Canalization Project The Wilson-Freese and Nichols JV (Wilson & FNI JV) was contracted by the U.S. Section of the

International Boundary and Water Commission (USIBWC) to perform aerial LiDAR and orthophotography tasks for the Rio Grande Canalization Project hydraulic modeling, sediment accumulation, and flow capacity analysis (RGCP-SEDQ) study under RFP 191BWC20-XX. LiDAR and orthophotography tasks included the acquisition and processing 0.5’ pixel orthophotography and aerial topographic LiDAR to a modified USGS NGP QL2 accuracy and density specifications.

Project Area The Wilson & FNI JV has surveyed and mapped a specified corridor along the Rio Grande from the

Caballo Dam to the American Dam using field surveys, aerial LiDAR surveys, and aerial orthophotography for the USIBWC.

Figure 1.1. Project Area

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LiDAR and Ortho Area The project boundary was created by the team and approved by the USIBWC to accurately and efficiently include the areas of the floodplain required to meet the project objectives.

Figure 1.2. LiDAR and Ortho Area

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2 Acquisition The mission planning (and eventual processing) for this project was based upon modified USGS NGP specifications for Orthoimagery and Quality Level 2 LiDAR. The acquisition was time sensitive in order to capture on-site construction activities during low water through the end of February, but before the water was released from the dam on March 8th. Aerial acquisition took place over 3 missions on the consecutive days of 3/4/20 and 3/5/20. Acquisition occurred during a brief weather window that provided cloud-free conditions before overcast skies moved into the area and would have prevented acquisition prior to the release of water. For cost-efficiencies and expediency the acquisition was focused on the extents of the area of interest rather than an expanded tiling scheme.

The data acquisition was performed by a fixed wing aircraft equipped with the Leica CityMapper containing the RCD30 digital camera and Hyperion 2 LiDAR sensor for simultaneous acquisition. The system was planned to acquire 12cm pixel RGB imagery to produce 15cm (6”) pixel natural color orthophotography. At this altitude the H2 LiDAR sensor acquires approximately 14 points per meter in a single pass, exceeding the minimum 4 points per meter required to meet USGS QL2. The increased density provides added detail for surface feature detection.

Base stations were deployed on up to 6 project control monuments during acquisition to improve the accuracy of the INS solution.

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Flightline Index The Leica CityMapper is an integrated system in a single aircraft. Both LiDAR and imagery share the same flightlines

Figure 2.1. Flightline Index Over Geomorphic Subreach 1 & 2

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Figure 2.2. Flightline Index Over Geomorphic Subreach 2 & 3

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Figure 2.3. Flightline Index Over Geomorphic Subreach 4 & 5

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Figure 2.4 Flightline Index Over Geomorphic Subreach 5 & 6

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Figure 2.5. Flightline Index Over Geomorphic Subreach 7

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3 Remotely Sensed Data Post-Processing, Calibration, and Relative Accuracy

Keystone Aerial Surveys provided a detailed report of the imagery, LiDAR, and inertial navigation system (INS) post-processing, and the LiDAR calibration. These data were imported and checked for quality by the Wilson & FNI Team’s Photogrammetrists and LiDAR Specialists.

The next nine pages constitute the report.

USIBWC AERIAL SURVEY

APRIL 3, 2020

KEYSTONE, NM

100 BLUE SKIES DRIVE BELEN, NM 87002

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Wilson_USIBWC_12cm_14ppm

Wilson & Company

Created by Keystone, NM

Authors: Jordon Beem (Data Specialist), Ethan Lacher (Operations Supervisor)

On March 4, 2020 and March 5, 2020, Keystone, NM, collected aerial imagery and LiDAR data for Wilson

& Co. using a Leica Hyperion 2 CityMapper installed in a Cessna 206 Stationair, tail number N72608. The data collected includes 12cm GSD, 3-band, 8-bit imagery and 14ppm LiDAR. All imagery, LiDAR, and

ABGPS/IMU data were simultaneously collected by the Hyperion 2 CityMapper sensor system. Data was collected over the course of three flights. . Two flights on March 4th occurred between 8:37AM and

12:55PM local time, and between 1:37PM and 3:48PM local time, and one flight on March 5th occurring between 9:00AM and 12:58PM. The aircraft was basing out of Las Cruces International Airport (LRU) near Las Cruces, NM, for the duration of the project.

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Flight Path

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Flight Plan Specifications:

- Flight Height: 5089'-6283'AGL/9777'-10341'MSL

- Overlap: 60% forward overlap, 30% sidelap

- 60 Flight Lines totaling 816.8km and 2,334 exposures

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Base station data was provided by Wilson & Co. For the first day of collection, data for four stations were provided. One station was restarted, and ultimately the data was not used. For the first flight on

March 4th, two stations were used. The third station was too far from the flight area. For the second flight on March 4th, three stations were used. On March 5th, data was provided from five base stations and all five were used in the calculation of the trajectory. All base station position data were calculated in OPUS. The final solution was calculated in Inertial Explorer trajectory processing software and for flight 1 had a combined separation of less than 8cm. For flights 2 and 3 the combined separation was less than 5cm.

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The Position Dilution of Precision (PDOP) for the final trajectory is generally less than 1.5 and spikes at less than 2.

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The Imagery, Exterior Orientation (EO), and LiDAR processing were conducted in Leica’s Workflow

Manager software. Imagery, EO and LiDAR positions were calculated from the final solution acquired from Inertial Explorer. LiDAR positioning was further refined using line-to-line calibration. This produced a point cloud with approximately 99% of matched pairs possessing a standard deviation less than or equal to 3cm. The adjusted point cloud was then calibrated to the client provided ground control points.

The Workflow Manager software calculated an average deviance of 0.183m. The final .las files were exported from Workflow Manager with a -0.18m z-axis adjustment (1cm is the precision of the export tool in Workflow Manager). Imagery was manually color and gamma balanced by Keystone NM’s data specialist. The EO was automatically generated during image export with a projected datum in New

Mexico Central State Plane NAD83(2011), Geoid12 A/B, and units in US Survey Feet, per instruction by

Wilson and Co. Quality assurance reports from Leica’s Workflow Manager have been included as accompanying documents to this report.

After the LiDAR and imagery data were exported, they were visually inspected for quality by two individuals of the Keystone, NM, team to ensure there was no haze, clouds, cloud shadows, image blur, or discoloration in the imagery and that the LiDAR data were without gaps, free of “noise” points, and aligned properly.

[End of Keystone Aerial Surveys Report]

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4 Aerial Mapping Targets and Control Points The aerial mapping control points were established using appropriate GPS survey techniques prior to acquisition and were tied to primary project control points. Existing survey control monument information was provided by USIBWC and used as the basis for new control and all fieldwork. Of the 31 existing control monuments provided from the previous project, 21 were found to still be in place. To maintain adequate coverage throughout the 105 mile project, an additional 14 control monuments were set where needed. New control monuments consisted of 1 ½ inch diameter aluminum caps on 5/8 inch diameter rebar stamped with their respective names. After recovering existing and setting new control monuments, static GPS observations were used to verify coordinates and elevations of the existing monuments and establish coordinates and elevations on the newly set monuments. The observed coordinates and elevation on existing monuments were found to be very consistent with the published values from the survey in 2016. These coordinates and elevations were held as provided, with data reported on recovery data sheets. For the new control monuments, new coordinates and elevations are provided on new data sheets. The coordinate system and elevation details are as follows: Coordinates are NM State Plane Central Zone, NAD 83. Elevations are NAVD 88 using GEOID 12B.

Control for the orthophotography consisted of 28 photo identifiable control points and 20 aerial targets constructed in areas without usable photo identifiable features.

RGCP orthophotography showing an aerial target with a surveyed control point displayed.

Airborne LiDAR control consisted of utilizing appropriate photo control points and 27 additional control points on flat and open terrain. An additional 60 checkpoints were surveyed across the project area in varying land cover types to produce the LiDAR vertical accuracy assessment.

The cross-referencing of control, checkpoints, the 30 targeted cross sections, stereo-imagery, and LiDAR data was implemented for visual and quantitative quality checks across the project.

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5 Orthophotography The USIBWC included a request for 6” pixel natural color orthophotography to capture the current conditions of the Rio Grande corridor. In addition to the Hyperion 2 LiDAR scanner, the Leica

CityMapper is equipped with the RCD30 digital photogrammetric camera for simultaneous acquisition of both LiDAR and imagery. The simultaneous acquisition approach is advantageous for eliminating many temporal discrepancies between datasets and reduces the need to mobilize and acquire imagery with a second aircraft.

As detailed in section 3.0, there were 60 flightlines and 2,334 exposures acquired over two days. The imagery was post-processed with differentially corrected GNSS positioning, and aircraft attitude orientation angles recorded 200Hz. The resultant combined separation solution output high accuracy external orientations (EO) at each exposure station.

The georeferenced imagery was imported into Image Station Automatic Triangulation (ISAT) for aerotriangulation. The aerotriangulation process automatically locates tie points in overlapping imagery to build statistical confidence in the relative positioning. The 28 photo identifiable control points and 20 aerial targets were then used for absolute positioning to project control.

The high accuracy and high density LiDAR data acquired from the same sensor and INS solution provided an excellent surface from which to use for the ortho rectification process. Easily identifiable features within the high density point cloud are cross-referenced with the orthorectified imagery for built-in quality control checks.

Radiometric adjustments and seamline editing were performed in OrthoPro and OrthoVista. The project area spanned many land cover and geologic areas with distinct reflectance characteristics to be incorporated into project-wide tone balancing.

6 LiDAR Processing The calibrated and unclassified LiDAR data received from the acquisition team was imported and checked for relative and absolute accuracies as indicated by their provided processing report (sec. 3.1).

Our team assessed the point cloud data using visual inspection and accuracy reporting within TerraScan, TerraModeler, TerraMatch and LP360.

Once the point cloud was determined to meet the modified NGP QL2 accuracy and density standards, several preliminary bare earth classification algorithms were run and assessed for effectiveness within

TerraScan. The goal was to determine the best set of parameters for the automated and effective isolation of ground points over varying terrain and land cover.

The resultant point cloud was then edited by experienced LiDAR technicians for errors of omission and commission within the bare earth and other classes, and the reclassification of bridges and other non-

DTM features.

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Table 6.1. USGS NGP Point Classifications

LiDAR Specification Two major factors influenced the Wilson & FNI JV’s recommendation and the USIBWC’s acceptance for a modified USGS QL2 specification; the surface accuracy and the point density. One of the primary goals of this task is to produce an accurate and detailed surface for comparison with previous surfaces and cross-sections for sediment analysis. The proposed modified QL2 approach would provide a non-vegetated RMSEz of ≤ 10cm, and a greater-than-the-minimum 2ppm requirement of 14ppm. The increased point density provides greater detail for triangulation in ditches and canals, as well as more opportunities for ground returns in dense vegetation along the riverbanks. The minimum standards for these key specifications are listed below, and the tested results of the vertical accuracy of the LiDAR dataset is detailed in the following section.

Table 6.2. USGS Quality Level and Point Spacing

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Table 6.3. USGS Quality Level and Associated RMSEz

LiDAR Vertical Accuracy Assessment The absolute accuracy of the dataset is the culmination of minimizing error throughout the acquisition, calibration, and classification processes. Approximately 100 checkpoints were surveyed across varying land cover types to produce RMSEz values for non-vegetated vertical accuracy (NVA) and vegetated vertical accuracy (VVA). The resultant RMSEz values validate the positional accuracy of the dataset meets the QL2 criteria; NVA = 0.191’ and VVA = 0.221’

Non-vegetated Vertical Accuracy Assessment

Average DZ -0.047

Minimum DZ -0.387

Maximum DZ 0.329

Average DZ 0.162

RMSEz 0.191

Std Dev 0.186

Table 6.4. RGCP NVA in Survey Feet Chart 6.1. RGCP NVA Histogram in Survey Feet

Vegetated Vertical Accuracy Assessment

Average dz -0.162

Minimum dz -0.348

Maximum dz 0.139

Magnitude Avg 0.183

RMSEz 0.221

Std Dev 0.156

Table 6.5. RGCP VVA in Survey Feet Chart 6.2. RGCP VVA Histogram in Survey Feet

7 Hydro-flattening of the Bare Earth Once the bare earth edit was complete, the next step was the extraction of the water breaklines to reclassify the interior points to the water classification, and to provide a logical water surface that is flat from bank to bank, and descending (monotonic) in rivers and streams. For this project the Rio Grande was the subject of the hydro-flatting breaklines. All other ditches and canals were defined only by the higher density (14ppm) LiDAR points. Within the Rio Grande, the extracted breaklines are more detailed and exceed the NGP specifications to support the goals of the project.

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Water perimeter was digitized from the LiDAR data within TerraScan and assigned an elevation based upon the surrounding terrain. Ponding water vertices were assigned a constant elevation, and flowing water was assigned descending elevations based upon water levels. Flowing water is generally level bank-to-bank except where curving, rapidly moving, or partially dammed water is not level.

It should be noted that hydro-flattening pertains only to the creation of derived DEMs from lidar points and breaklines. Hydro-flattening makes no changes to the geometry of the originally computed lidar points. Breaklines developed for use in hydro-flattening were also used to support classification of the point data.

The hydro-flattened bare earth DEM’s are generated at 2ft pixels in LP360 by combining the water breaklines with the ground classified points. A proximity buffer is applied to the breaklines to reclassify ground points to “ignored ground” within 1.5’ either side of the breakline.

USGS NGP minimum requirements (applicable) for hydro-flattening:

1. Inland Ponds and Lakes

Waterbodies with a surface area of 0.8 hectare (ha; 2 acres) or greater (approximately equal to a round pond 100 m in diameter) at the time of collection shall be flattened.

Flattened waterbodies shall present a flat and level water surface (a single elevation for every bank vertex defining the waterbody’s perimeter).

The entire water surface edge shall be at or below the immediately surrounding terrain (the presence of floating waterbodies will be cause for rejection of the deliverable).

Long impoundments such as reservoirs, inlets, and fjords, whose water surface elevations decrease with downstream travel, shall be treated as streams or rivers.

2. Inland Streams and Rivers

Streams and rivers of a 30-m or greater nominal width shall be flattened.

Streams or rivers whose width varies above and below 30 m will not be broken into multiple segments; data producers will use their best professional cartographic judgment in determining when a stream or river has attained a nominal 30-m width.

Flattened streams and rivers shall present a flat and level water surface bank-to-bank (perpendicular to the apparent flow centerline).

Flattened streams and rivers shall present a gradient downhill water surface, following the immediately surrounding terrain.

In cases of sharp turns of rapidly moving water, where the natural water surface is notably not level bank-to-bank, the water surface will be represented as it exists while maintaining an aesthetic cartographic appearance.

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The entire water surface edge shall be at or below the immediately surrounding terrain.

Stream channels shall break at culvert locations leaving the roadway over the culvert intact.

Streams shall be continuous at bridge locations.

Bridges in all their forms shall be removed from the DEM.

When the identification of a structure as a bridge or culvert cannot be made definitively, the feature shall be regarded as a culvert.

5. Islands

Permanent islands 0.4 ha (1 acre) (approximately equal to a round island 72 m in diameter) or larger shall be delineated within all waterbodies. For this project, detectable islands of a ¼ acre and greater were delineated.

Table 6.6. USGS Optional Hydro-flattening Minimum Requirements

Many of the distance and area parameters were greatly improved from the minimum USGS requirements to support project goals and minimize triangulation errors for surface comparisons.

Hydro-flattening Examples:

Figure 7.1. Before and after hydro-flattening near Caballo Dam

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Figure 7.2. Before and after hydro-flattening around islands

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8 Orthophotography and LiDAR Tiling Scheme Due to the high point density (~14ppm), a project specific tiling scheme was generated by using 2000’ x

2000’ tiles. The tiles are numbered 001-1072, ascending north to south and west to east. These tiles and naming conventions are used by both LiDAR and orthoimagery datasets to allow for usable segments at full resolution. A digital tile index was provided with the datasets.

Figure 8.1. RGCP Tile Index Example

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9 Deliverables LiDAR and Orthoimagery Report and Data

Narrative of the data collected, process of collection, post processing, and assumptions

Maps showing flightline index for orthoimagery

LiDAR Data

Digital Elevation Models (DEM)

Point Data – Classified LAS files

Hydro-flattened breaklines

Geodatabase of classified LiDAR data

Metadata

Orthoimagery

Flight map in shapefile format

Digital orthophotography in 8-bit RGB uncompressed GeoTIFF in project coordinates

Digital orthophotography in 8-bit compressed MRSID format

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Appendix I Professional Land Surveyor Certification

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Appendix II City Mapper Calibration Report

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Leica Geosystems Leica

CityMapper Calibration

Certificate

Product Leica CityMapper

Serial Number 95538

Date 09 August 2019

Inspector Kevin Spruill

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Leica Geosystems AG

Heinrich-Wild-Strasse

CH-9435 Heerbrugg

Schweiz

Document Code: 855923 www.leica-geosystems.com http://www.leica-geosystems.com/

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1. System Components

Component Type Serial Number

Pod CityMapper Pod 95538

GNSS/IMU Litef LCI-100C 500 Hz 1153

LiDAR Unit Hyperion II 5537

Camera Head CH82 82652

Lens NAT-D 2.8/80 80251

Camera Head CH81m 81828

Lens SAT-D 4.0/150 150236

Camera Head CH81m 81829

Lens SAT-D 4.0/150 150237

Camera Head CH81m 81830

Lens SAT-D 4.0/150 150238

Camera Head CH81m 81831

Lens SAT-D 4.0/150 150239

2. Estimation Process

Passed Date Inspector

Image Flight completed ok 01.05.2019 Kevin Bless

Image Quality Check checked ok 03.05.2019 Rene Heierli

Image Calibration completed ok 05.05.2019 Muzaffer Adigüzel

Image Misalignment Update completed

LiDAR Flight completed ok 01.05.2019 Kevin Bless

LiDAR Quality Check checked ok 03.05.2019 Philip Kurt Benz

LiDAR Calibration and Accuracy completed ok 07.05.2019 Xu Wang

LiDAR Misalignment Update completed ok 09.08.2019 Kevin Spruill

3. Inspectors

Name Bernhard Riedl 09.08.2019

Position Production Manager

Name Xu Wang 09.08.2019

Position Support Engineer

Name Michael Vetter 09.08.2019

Position Support Engineer

4. Remarks

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5. LiDAR Calibration Results

The calibration results for the LiDAR Unit are only valid for:

• IMU and Pod as listed in the System Components section

5.1 LiDAR Geometric Calibration Results

IMU Misalignment Value Unit ω -0.011454 degree

Φ -0.011615 degree κ -0.013289 degree

Boresight Value Unit

Θ -0.000871 degree

Φ -0.002450 degree

Receiver 1 Value Unit

Range Δ Offset 0.000000 meters

Wedge 0 Value Unit

Wedge Δ Alpha 0.028332 degree

Wedge Position Δ Offset 0.140803 degree

Position Correction X -0.020381 degree Y 0.006169 degree

Mount Roll 0.248296 degree

Pitch 0.576408 degree

Rotation Axis Roll 0.077505 degree

Pitch 0.243510 degree

Wedge 1 Value Unit

Wedge Δ Alpha -0.022392 degree

Wedge Position Δ Offset 0.292223 degree

Position Correction X 0.014140 degree Y 0.008778 degree

Mount Roll -0.024847 degree

Pitch -0.036991 degree

Speed Pitch 1.50E-06 degree/rps2

Rotation Axis Roll -0.020874 degree

Pitch -0.017270 degree

LiDAR Geometric Calibration File

HYPERION_GEOMETRY_LIDARUNIT-5537-C-855570-DATETIME-20190806-190823.XML

Date 09.08.2019

LiDAR Misalignment Flight Date 23.07.2019

LiDAR Misalignment Update Completed Date 09.08.2019

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5.2 LiDAR Unit Accuracy Check

Accuracy checks:

• Deviation of two perpendicular lines to GCP’s

• Difference of two perpendicular lines

• Difference of forward and backward scan of one line

5.2.1 Multi-line accuracy of two perpendicular lines to ground control points

Figure 1 Vertical distance to ground control points at 1000 m AGL.

5.2.2 Difference of forward and backward scan of one line

Figure 2 Vertical difference betweeen forward and backward scan at 1000 m AGL.

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5.2.3 Multi-line accuracy between two perpendicular lines

Figure 3 Vertical difference betweeen two perpendicular lines at 1000 m AGL.

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6. Imaging Sensors Estimation Results

The estimation results for the camera head and lens combination are only valid for:

• IMU and Pod as listed in the System Components section.

• Camera Head, lens and specified position as listed in the Estimation Results sections.

6.1 Camera Model of distortion free images

All factory calibration results contain fixed nominal focal lengths and zero principal point offsets.

Leica HxMap applies the grid to create distortion-free images of nominal focal length and pixel size.

6.1.1 CH8x Model

Component

Camera Head CH82

Lens NAT-D 2.8/80

Camera Model

Focal Length Distance [mm] c 83.00

Radial Symmetric Distorsion Distance [mm] k0 0.0000 k1 0.0000 k2 0.0000

Decentering Distortion Distance [mm] p1 0.0000 p2 0.0000

Non-Orthogonality Distortion Distance [mm] b1 0.0000 b2 0.0000

Pixel Size (Height and Width) Distance [mm]

RGB 0.0052

NIR 0.0120

Rows and Columns Rows Columns

Active RGB 7752 10320

Raw RGB 7788 10336

Active NIR 3654 4478

Raw NIR 3366 4500

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6.1.2 CH81m Model

Component

Camera Head CH81m

Lens SAT-D 4.0/150

Camera Model

Focal Length Distance [mm] c 156.00

Radial Symmetric Distorsion Distance [mm] k0 0.0000 k1 0.0000 k2 0.0000

Decentering Distortion Distance [mm] p1 0.0000 p2 0.0000

Non-Orthogonality Distortion Distance [mm] b1 0.0000 b2 0.0000

Pixel Size (Height and Width) Distance [mm]

RGB 0.0052

Rows and Columns Rows Columns

Active RGB 7752 10320

Raw RGB 7788 10336

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6.2 Results of Geometric Calibration

6.2.1 Calibration method for Green Reference Band

Estimation of additional parameters (focal length, principal point, radial symmetric distortion, correction grid) and IMU misalignment in simultaneous bundle adjustment

Reference band (green) Distance [mm]

Resulting sigma naught of bundle adjustment: 0.0015

Final bundle adjustment results after elimination of tie point blunders:

6.2.2 Calibration method for Other Spectral Bands

Estimation of additional parameters (correction grid), based on the result for green in simultaneous bundle adjustment

Other Spectral Bands Distance [mm]

Co-registration to green better than: 0.002

Leica HxMap applies the grid to create distortion-free images of nominal focal length and fixed pixel size of 0.0052 mm.

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6.3 Estimation Results for Nadir Camera Head and Lens

Component Serial Number

Camera Head CH82 82652

Lens NAT-D 2.8/80 80251

View Direction in Pod Position Nadir

IMU Misalignment Angle [degree] ω 0.01719

Φ -0.05469 κ -0.24903

Principal Point Distance [mm] x 0.0000 y 0.0000

Focal Length Distance [mm] c 83.00

Geometric Calibration File

RCD30_Geometry_CameraHead-82652-E-798528_LensSystem-80251-B-785423_DateTime-

20190504-084224.xml

Geometric Calibration Date 04.05.2019

Radiometric Calibration Date 26.03.2019

Misalignment Flight Date -

Misalignment Update Completed Date -

Remaining image space residuals after applying the calibration results

Radius of circles is 0.0015 mm

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6.4 Estimation Results for Forward Camera Head and Lens

Camera Head CH81m 81828

Lens SAT-D 4.0/150 150236

View Direction in Pod Position Forward

IMU Misalignment Angle [degree] ω -0.15056

Φ 0.08262 κ -0.07931

Principal Point Distance [mm] x 0.0000 y 0.0000

Focal Length Distance [mm]

156.00

Geometric Calibration File

RCD30_Geometry_CameraHead-81828-D-842157_LensSystem-150236-B-

819435_DateTime-20190505-215558.xml

Geometric Calibration Date 05.05.2019

Radiometric Calibration Date 28.03.2019

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6.5 Estimation Results for Backward Camera Head and Lens

Camera Head CH81m 81829

Lens SAT-D 4.0/150 150237

View Direction in Pod Position Backward

IMU Misalignment Angle [degree] ω 0.05575

Φ 0.04064 κ -0.07323

Principal Point Distance [mm] x 0.0000 y 0.0000

Focal Length Distance [mm]

156.00

Geometric Calibration File

RCD30_Geometry_CameraHead-81829-D-842157_LensSystem-150237-B-

819435_DateTime-20190505-215628.xml

Geometric Calibration Date 05.05.2019

Radiometric Calibration Date 29.03.2019

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6.6 Estimation Results for Left Camera Head and Lens

Camera Head CH81m 81830

Lens SAT-D 4.0/150 150238

View Direction in Pod Position Left

IMU Misalignment Angle [degree] ω -0.10267

Φ 0.01911 κ -0.08819

Principal Point Distance [mm] x 0.0000 y 0.0000

Focal Length Distance [mm]

156.00

Geometric Calibration File

RCD30_Geometry_CameraHead-81830-D-842157_LensSystem-150238-B-

819435_DateTime-20190505-215703.xml

Geometric Calibration Date 05.05.2019

Radiometric Calibration Date 01.04.2019

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6.7 Estimation Results for Right Camera Head and Lens

Camera Head CH81m 81831

Lens SAT-D 4.0/150 150239

View Direction in Pod Position Right

IMU Misalignment Angle [degree] ω 0.13175

Φ -0.01092 κ -0.17540

Principal Point Distance [mm] x 0.0000 y 0.0000

Focal Length Distance [mm]

156.00

Geometric Calibration File

RCD30_Geometry_CameraHead-81831-D-842157_LensSystem-150239-B-

819435_DateTime-20190505-215716.xml

Geometric Calibration Date Date 05.05.2019

Radiometric Calibration Date Date 01.04.2019