1. SHADED-RELIEFS MATCHING AS AN EFFICIENT TECHNIQUE FOR 3D GEO-REFERENCING OF HISTORICAL DIGITAL ELEVATION MODELS Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability http://www.ual.es/GruposInv/ProyectoCostas/index.htm F.J. Aguilar a, I. Fernández a, M.A. Aguilar a, J.L. Pérez b, J. Delgado b, J.G. Negreiros c a Dept. of Agricultural Engineering, Almería University, Spain b Dept. of Cartographic Engineering, Geodesy and Photogrammetry, Jaén University, Spain C ISEGI – Nova de Lisboa University, Portugal Kyoto, Japan. 10 August 2010 Corresponding Author: F.J. Aguilar (faguilar@ual.es)

2. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Nowadays Coastal Elevation Models production (e.g. for shoreline extraction) is efficiently accomplished by means of LiDAR technology which is contributing to a wide range of coastal scientific investigations 1

3. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 2 Because LiDAR is a relatively new technology, historical data beyond the past decade are practically unavailable (LiDAR mapping systems were not become available commercially till the late 90s). 1977 Agriculture Photogrammetric Flight Approximated scale 1:18000 Analogic B&W flight No camera calibration certificate Focal length around 152,77 mm INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS

4. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 3 Z = f(x,y) ESTEREOMATCHING Coastal Elevation Model INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS

5. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 4 The latter approach requires a number of ground control points (GCPs) to compute the absolute orientation of every stereo pair, a surveying task that usually becomes inefficient and costly because the difficulty to accurately identify and survey a suitable set of ground points which could be pointed on the corresponding historic photographs. INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS

6. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 5 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS 1:33000 scale1:18000 scale1:5000 scale

7. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 6 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS To avoid the necessity of ground control points, a new approach to historical CEMs 3D geo-referencing is proposed along this work.

8. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS BACK

9. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Matched 3D points allow computing an iterative least squares registration between both CEMs by means of a robust seven parameters 3D Helmert transformation. The outliers found after each iteration were discarded and not taken into account in the next one by establishing a threshold value to avoid gross errors due to landscape changes BACK

10. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 7 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS

11. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 8 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS DTM 2001 (10X10 m grid spacing) Photogrammetric Flight 1:20000 scale produced by Junta de Andalucía© DSM 1977 (10x10 m grid spacing) Photogrammetric Flight 1:18000 scale

12. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 9 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Pre-oriented model by means of automatic relative orientation. Preliminary course-orientation. Average Error = 16.12 m Maximum Error = 63.29 m Minimum Error = -35.03 m Standard deviation = 22. 15 m

13. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 10 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS 135º solar azimuth and 45º solar elevation Automatic matching algorithm based on the Scale Invariant Feature Transform (SIFT*; Lowe, 2004) to identify conjugated points in image space (pixel coordinates). 26 conjugated points were correctly found

14. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 11 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Shaded-relief image matching. Results from 3D Helmert adjustment Parameter Estimated parameters Solar azimuth 270º Solar elevation 45º Solar azimuth 135º Solar elevation 45º ValueAccuracyValueAccuracy ΔX-36.15 m0.74 m-38.81 m0.99 m ΔY-8.35 m0.77 m-7.65 m1.01 m ΔZ-10.97 m0.74 m-9.42 m1.00 m ΔΩ0.0081º0,00377º0.0141º0,00418º ΔΦ0.0174º0,00172º0.0162º0,00372º ΔΚ-0.0116º0,00489º-0.0123º0,00503º λ1.00060,000770.99540,00253

15. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 12 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Surface Matching Results between 1977 and 2001 (270º solar azimuth and 45º solar elevation shaded-relief) Average Error = -1.03 m Maximum Error = 11.45 m Minimum Error = -20.92 m Standard deviation = 2.70 m

16. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 13 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Surface Matching Results between 1977 and 2001 (135º solar azimuth and 45º solar elevation shaded-relief) Average Error = -0.31 m Maximum Error = 7.79 m Minimum Error = -15.18 m Standard deviation = 1.89 m

17. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 14 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Surface Matching Results between 1977 and 2001. Absolute vertical residuals distribution (135º solar azimuth and 45º solar elevation shaded-relief)

18. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 14 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Comparison between the 1977 Photogrammetrically Oriented DSM and the Shaded-relief Matching Oriented DSM DSM/DTM comparison Maximum (m) Minimum (m) Standard deviation (m) DSM (135º/45º) – PhotoDSM (1977) 6.40-6.051.57 DSM (240º/45º) – PhotoDSM (1977) 5.28-6.762.56 2001 DTM – 1977 PhotoDSM 8.34-7.281.60

19. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 15 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS The results obtained from this work may be deemed as very promising, showing a good co-registration between reference and historical CEMs in heavily developed coastal areas. The point is the high efficiency and robustness demonstrated for historical CEM 3D geo-referencing when it was compared to costly and time-consuming traditional methods such as photogrammetric absolute orientation based on surveyed ground control points and self-calibrating bundle adjustment techniques. As a further work, this preliminary approach could be used as a previous course matching to be subsequently refined by 3D robust surface matching. For instance our approach could be used as a first step headed up to later apply a Least Z-Difference (LZD) based surface matching algorithm to refine the initial matching as much as possible. This second step should include weight functions based on M-estimators to make the computation more robust and resisting to the presence of outliers

20. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability 16 Kyoto, Japan. 10 August 2010 Thank you very much for your kind attention INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS

21. Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability Kyoto, Japan. 10 August 2010 INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Pre-oriented model by Shaded-relief image matching Differential model computation dZi Binary weighting for every point Least Squares estimation applying weights (Helmert 3D) Iterating till convergence Solution refining M-estimator Tukey’s Biweight Least squares estimation applying weights (Helmert 3D) till convergence