Research Project RNM 3575 Multisource Geospatial Data Integration

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/Grupos. Inv/Proyecto. Costas/index. htm SHADED-RELIEFS MATCHING AS AN EFFICIENT TECHNIQUE FOR 3 D GEO-REFERENCING OF HISTORICAL DIGITAL ELEVATION MODELS F. J. Aguilara, I. Fernándeza, M. A. Aguilara, J. L. Pérezb, J. Delgadob, J. G. Negreirosc Dept. of Agricultural Engineering, Almería University, Spain Dept. of Cartographic Engineering, Geodesy and Photogrammetry, Jaén University, Spain C ISEGI – Nova de Lisboa University, Portugal a b Corresponding Author: F. J. Aguilar (faguilar@ual. es) Kyoto, Japan. 10 August 2010

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

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

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

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS 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. RESULTS & DISCUSSION CONCLUSIONS Kyoto, Japan. 10 August 2010 4

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

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

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

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION Matched 3 D points allow computing an iterative least squares registration between both CEMs by means of a robust seven parameters 3 D 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 CONCLUSIONS BACK Kyoto, Japan. 10 August 2010

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

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

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability INTRODUCTION Pre-oriented model by means of automatic relative orientation. Preliminary course-orientation. NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Average Error = 16. 12 m Maximum Error = 63. 29 m Minimum Error = -35. 03 m Standard deviation = 22. 15 m Kyoto, Japan. 10 August 2010 9

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability 135º solar azimuth and 45º solar elevation INTRODUCTION NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS 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 Kyoto, Japan. 10 August 2010 10

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability INTRODUCTION Shaded-relief image matching. Results from 3 D Helmert adjustment NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS Estimated parameters Parameter RESULTS & DISCUSSION Solar azimuth 270º Solar elevation 45º Solar azimuth 135º Solar elevation 45º Value Accuracy ΔX -36. 15 m 0. 74 m -38. 81 m 0. 99 m -8. 35 m 0. 77 m -7. 65 m 1. 01 m ΔZ -10. 97 m 0. 74 m -9. 42 m 1. 00 m ΔΩ 0. 0081º 0, 00377º 0. 0141º 0, 00418º ΔΦ 0. 0174º 0, 00172º 0. 0162º 0, 00372º ΔΚ -0. 0116º 0, 00489º -0. 0123º 0, 00503º λ Kyoto, Japan. 10 August 2010 Accuracy ΔY CONCLUSIONS Value 1. 0006 0, 00077 0. 9954 0, 00253 11

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability INTRODUCTION Surface Matching Results between 1977 and 2001 (270º solar azimuth and 45º solar elevation shaded-relief) NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Average Error = -1. 03 m Maximum Error = 11. 45 m Minimum Error = -20. 92 m Standard deviation = 2. 70 m Kyoto, Japan. 10 August 2010 12

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability INTRODUCTION Surface Matching Results between 1977 and 2001 (135º solar azimuth and 45º solar elevation shaded-relief) NEW APPROACH FUNDAMENTALS STUDY SITE & DATASETS RESULTS & DISCUSSION CONCLUSIONS Average Error = -0. 31 m Maximum Error = 7. 79 m Minimum Error = -15. 18 m Standard deviation = 1. 89 m Kyoto, Japan. 10 August 2010 13

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

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability INTRODUCTION Comparison between the 1977 Photogrammetrically Oriented DSM and the Shaded-relief Matching Oriented DSM NEW APPROACH FUNDAMENTALS CONCLUSIONS Kyoto, Japan. 10 August 2010 Maximum (m) Minimum (m) Standard deviation (m) DSM (135º/45º) – Photo. DSM (1977) 6. 40 -6. 05 1. 57 5. 28 -6. 76 2. 56 2001 DTM – 1977 Photo. DSM RESULTS & DISCUSSION DSM/DTM comparison DSM (240º/45º) – Photo. DSM (1977) STUDY SITE & DATASETS 8. 34 -7. 28 1. 60 14

Research Project RNM 3575: Multisource Geospatial Data Integration and Mining for the Monitoring and Modelling of Coastal Areas Evolution and Vulnerability 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 3 D 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 3 D 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 Kyoto, Japan. 10 August 2010 15

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

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