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A Preliminary Mapping Accuracy Assessment of UAV Photogrammetry

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1 A Preliminary Mapping Accuracy Assessment of UAV Photogrammetry
A Presentation at International Symposium on Remote Sensing (ISRS 2017) Nagoya, Japan 17th – 19th May 2017 A Preliminary Mapping Accuracy Assessment of UAV Photogrammetry Shofiyatul Qoyimah1 and Yi-Hsing Tseng2 1Master Student and 2Professor Department of Geomatics National Cheng Kung University, Taiwan (R.O.C)

2 Outline Motivation Methodology Result Conclusion 1
Background & Problem Methodology Study Area, Equipment, Data and Workflow Result IOP Evaluation and Aerial Triangulation Conclusion Australis, Pix4Dmapper, S.O.D.A 1 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

3 = / ≠ Unmanned Aerial Vehicle (UAV) ???? DRONE
Potential Growth in Commercial Use of UAS Entertaining / Recording Toys Hobbyists Aerial Photography Protecting / Inspecting Military Public Safety Wildlife Oil Rigs Agriculture Mining Bridges Evaluating / Managing Situational Awareness Operations Management Asset Tracking Modelling/mapping Environmental Monitoring Delivering / Transporting Online Retail Local Stores Restaurants Legal Papers Medical 2019 … … 2014 Unmanned Aerial Vehicle (UAV) ???? = / ≠ DRONE Source : Unmanned Aircraft Systems (UAS): Commercial Outlook for a New Industry, 2015 Motivation Methodology Result Conclusion Rescuer Drone Drone Sprayer Drone Delivery Express “Dronie” Drone Racing Source : 2 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

4 Motivation Methodology Result Conclusion
Source : Close Range Photogrammetry – Principles, Methods and Applications, 2006 Accuracy of Measurement Methods Motivation Methodology Result Conclusion Mapping Photogrammetric measurement platform using UAV that equipped with a photogrammetric measurement system (camera) (Eisenbeiss, 2008) UAV Photogrammetry Image Source : 3 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017 How good is UAV Photogrammetry applied in mapping ???

5 Motivation Methodology Result Conclusion
Taiwan (R.O.C) -Nantou County- Motivation Methodology Result Conclusion Study Area (NanGang Industrial Area) Taiwan (R.O.C) -Nantou County- Image Source : Google Earth 4 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

6 Australis Photometrix Image Station Automatic Triangulation (ISAT)
Motivation Methodology Result Conclusion Equipment SenseFly Sensor Optimized for Drone Application (S.O.D.A) Camera RGB sensor 1-inch sensor size 2.4 micron pixel pitch 20 MP resolution eBee Plus SenseFly UAV Wingspan UAV model 1.1 kg weight 3 km radio link range 59’ maximum flight time Source : Software Pix4Dmapper For Aerial Triangulation Australis Photometrix For IOP Evaluation Image Station Automatic Triangulation (ISAT) For Aerial Triangulation 5 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

7 Motivation Methodology Result Conclusion
Data Ground Control Point 29 GCPs in TWD97 coordinate system Measured and maintained by National Land Surveying and Mapping Center R.O.C (NLSC R.O.C) Accuracy: horizontal = 5cm, vertical = 10cm Geotagged Aerial Images 330 aerial images 1 km2 coverage area 80%, 70% overlap and sidelap 200 m flight height 4.610 cm GSD Image Source : Google Earth 6 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

8 Absolute Orientation Process Information
Motivation Methodology Result Conclusion GCP Position Geotagged Aerial Images Workflow 1 Aerial Triangulation (Pix4Dmapper) Original Tie Point 3 2 Corrected Tie Point Absolute Orientation Process Information Aerial Triangulation (ISAT) IOP Evaluation (Australis) 7 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

9 Motivation Methodology Result Conclusion
Ground Control Point (GCP) Position Tie Point Coordinate Exterior Orientation Parameter (EOP) Interior Orientation Parameter (IOP) Quality Report Motivation Methodology Result Conclusion 1 Aerial Triangulation (Pix4Dmapper) R1 R2 R3 Initial 0.124 -0.411 0.377 Optimized 0.123 -0.427 0.399 Geotagged Aerial Images GCP Position Aerial Triangulation (Pix4DMapper) EOP IOP GCP position Original Tie point (Case 1) Quality Report Problem: Different definition of radial distortion parameter in Pix4D IOP Evaluation 8 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

10 Lens Distortion Correction
Motivation Methodology Result Conclusion 2.1 IOP Evaluation (original tie point lens distortion correction from Pix4D) Image Coordinate x (mm) Image Coordinate y (mm) Radial Distortion from Pix4Dmapper Original Tie Point (Case 1) Radial Distortion Profile Radial Distance (micron) Distortion Value (micron) 17.9 16.6 IOP (Pix4D mapper) IOP from Pix4Dmapper IOP Value F (mm) px (mm) py (mm) R1 1.23E-01 R2 -4.27E-01 R3 3.99E-01 T1 -1.10E-03 T2 -2.13E-03 Lens Distortion Correction Pix4D Corrected Tie Point (Case 2) Hypothesis: There is some error in S.O.D.A internal camera parameter 9 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

11 Calibration & Distortion Correction
Radial Distortion Profile Radial Distance (micron) Distortion Value (micron) -54.8 -35.8 Motivation Methodology Result Conclusion 2.2 IOP Evaluation using Australis IOP from Australis Image Coordinate x (mm) Image Coordinate y (mm) Radial Distortion (K1,K2,K3,K4,K5) Radial Distortion (K1,K2,K3) Tie point IOP Value Standard Error C (mm) 2.15E-20 XP (mm) -0.091 YP (mm) 0.0266 K1 -1.08E-03 K2 3.31E-05 2.15E-24 K3 -2.74E-07 2.15E-30 P1 2.12E-04 P2 -1.10E-04 B1 -5.36E-33 B2 -3.99E-33 K4 2.17E-10 7.14E-12 K5 -3.98E-12 1.27E-13 Original Tie Point (Case 1) Calibration & Distortion Correction with and without K4&K5 Corrected Tie Point with K4&K5 parameter (Case 3) Corrected Tie Point without K4&K5 parameter (Case 4) Hypothesis: Something wrong with calibration process in Pix4Dmapper software There is some error in S.O.D.A internal camera parameter 10 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

12 Relative Orientation of Case 1
Relative Orientation Result (Case 1) Before gave threshold T = 10 pixel (24micron) T = 5pixel (12micron) T = 3 pixel (7.2 micron) T = 2 pixel (4.8 micron) T =1pixel (2.4 micron) Sigma (micron) 6.4 6.3 4.7 2.5 1 0.4 RMS image x (micron) 6.2 5 3 1.7 0.9 RMS image y (micron) 5.4 5.3 4.1 2.8 Degree of Freedom (DOF) 129451 129233 112583 71057 20646 9830 Gross image blunder 2 Gross control blunder Image blunders 328 162 Image point used 76161 76052 67727 46964 21757 16346 Motivation Methodology Result Conclusion 3 Aerial Triangulation (ISAT) Aerial Triangulation – Case 1 Sigma naught <= 1 pixel Give threshold to remove image blunder No Yes Case 1 Relative Orientation Absolute Orientation 10 control point 14 check point Tie point Case 1, Case 2 Case 3, Case 4 Relative Orientation (T = 2 pixel) Absolute Orientation Images EOP GCP position Process Information Tie Point Tie point Case 1, Case 2 Case 3, Case 4 Relative Orientation Absolute Orientation Images EOP GCP position Process Information Tie Point Relative Orientation of Case 1 Value Sigma (micron) 6.4 RMS image x (micron) 6.3 RMS image y (micron) 5.4 Degree of Freedom (DOF) 129451 Gross image blunder 2 Gross control blunder Image blunders 328 Image point used 76161 1 pixel = 2.4 micron 11 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

13 Gross control blunders
Motivation Methodology Result Conclusion Relative Orientation Result Relative Orientation Result Parameter Case 1 Case 2 Case 3 Case 4 Sigma (micron) 1 1.8 1.3 1.5 RMS x (micron) 1.7 2 1.2 1.4 RMS y (micron) DOF 20646 94831 121891 121465 Gross image blunders Gross control blunders Image blunders Image Point used 21757 58851 72366 72162 Case 1 = Original tie point data from Pix4Dmapper Case 2 = Tie point corrected by Pix4Dmapper lens distortion parameter Case 3 = Corrected tie point by Australis (K1,K2,K3,K4,K5) Case 4 = Corrected tie point by Australis (K1,K2,K3) 12 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

14 Motivation Methodology Result Conclusion
Relative Orientation Result Relative Orientation Result Case 3 has the lowest value of RMS image x and y Case 3 has the similar value of sigma naught with the case 1 (that has the lowest value) Case 3 has the highest number of image point used 13 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

15 Motivation Methodology Result Conclusion
Absolute Orientation Result RMS Control and Check Point (Absolute Orientation) RMS control point (m) RMS check point (m) X Y Z Case 1 0.048 0.035 0.084 0.119 0.205 1.073 Case 2 0.188 0.181 0.312 0.285 0.368 0.531 Case 3 0.046 0.075 0.115 0.051 0.128 Case 4 0.033 0.049 0.114 0.041 0.171 Compare the case 3 and case 4: Case 4 has the smallest different RMS value between control point and check point in X and Y direction Case 3 has the smallest different RMS value between control point and check point in Z direction 14 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

16 Motivation Methodology Result Conclusion
Absolute Orientation Result Sigma naught, RMS x and RMS y (Absolute Orientation) Sigma naught (micron) RMS image x (micron) RMS image y (micron) Case 1 0.9 1.9 1.8 Case 2 2 1.7 Case 3 1.3 1.2 Case 4 1.4 Case 3 has the smallest value of RMS image x and RMS image y While it is the second lowest value of sigma naught 15 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

17 Motivation Methodology Result Conclusion
Australis Calibrating the original tie point can increase the measured point number and makes aerial triangulation process more accurate Pix4Dmapper Has different definition in radial distortion parameter that the calibrated IOP need to be evaluate using another software S.O.D.A SenseFly camera Still has some error in its camera system that affect the aerial triangulation result 16 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

18 Reference Canis, B. (2015). UNmanned Aircraft Systems (UAS): COmmercial Outlook for a new Industry. Washington,D.C: Congressional Research Service. Eisenbeiss, H. (2008). UAV Photogrammetry in Plant Sciences and Geology. Povo (Torento), Italy: In : 6th ARIDA Workshop on "Innovations in 3D Measurement, Modelling and Visualization. Luhmann, T. R. (2006). Close Range Photogrammetry - Principles, Methods and Applications. Caithness: Whittles Publishing. SenseFly. (2017, January 20). eBee Plus Aerial efficiency, photogrammetric accuracy. Retrieved from sebseFly: 19 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

19 Thank you “Knowledge is that which benefits, not that which is memorized” - Imam al-Shafi’i (ra) -

20 Absolute Orientation Information
Absolute Orientation Result of Case 1 and Case 2 Absolute Orientation Information Case 1 Case 2 X/Omega/x Y/Phi/y Z/Kappa RMS control point (m) 0.048 0.035 0.084 0.188 0.181 0.312 RMS check point(m) 0.119 0.205 1.073 0.285 0.368 0.531 max ground residual (m) 0.057 0.139 0.352 0.306 0.534 Mean STD dev photo position (m) 0.232 0.239 0.215 0.065 0.069 0.063 Mean STD dev photo attitude (degree) 0.135 0.12 0.144 0.036 0.032 0.026 mean image residual (micron) RMS image residual (micron) 1.9 1.8 2 1.7 control point used 7 8 check point used 13 14 DOF 16555 95770 sigma naught measured point 18716 58322 gross blunder 2873 497 image blunder 169 32 International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017

21 Absolute Orientation Information
Absolute Orientation Result of Case 3 and Case 4 Absolute Orientation Information Case 3 Case 4 X/Omega/x Y/Phi/y Z/Kappa RMS control (m) 0.046 0.075 0.115 0.033 0.049 0.114 RMS check (m) 0.035 0.051 0.128 0.041 0.171 max ground residual (m) 0.076 0.182 0.19 0.057 0.113 0.21 Mean STD dev photo position (m) 0.023 0.022 0.026 0.025 Mean STD dev photo attitude (degree) 0.006 0.005 0.002 0.007 mean image residual (micron) RMS image residual (micron) 1.2 1.4 control point used 10 check point used 14 DOF 123914 123465 sigma naught measured point 72379 72162 gross blunder image blunder International Symposium on Remote Sensing 2017, Japan, 17th – 19th May 2017


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