Advertisement

Comprehensive evaluation of Pléiades-1A bundle images for geospatial applications

  • Hüseyin TopanEmail author
  • Karsten Jacobsen
  • Ali Cam
  • Mustafa Ozendi
  • Murat Oruç
  • Oya Burcu Bakioğlu
  • Çağlar Bayık
  • Talha Taşkanat
Original Paper

Abstract

This paper presents the results of comprehensive evaluation of Pléiades 1A which is the first civilian satellite of Europe with sub-meter resolution. The analyses consist of radiometric evaluation, georeferencing accuracy assessment, pan-sharpening performance, digital surface/terrain model quality and vector map production. The effective resolution is estimated with a factor slightly below 1.0 for triplet panchromatic images, and signal to noise ratio is in the range of other comparable space borne images. The georeferencing accuracy was estimated with a standard deviation in X and Y directions in the range of 0.45 m by bias-corrected and sensor-dependent rational functional model. 3D standard deviation of ± 0.44 m in X direction, ± 0.51 m in Y direction and ± 1.82 m in the Z direction were reached in spite of the very narrow angle of convergence by the same mathematical model. The generated digital surface/terrain models were achieved with ± 1.6 m standard deviation in Z direction in relation to a reference digital terrain model. The pan-sharpened images were generated by various methods, and were validated by quantitative and qualitative analyses. Moreover, a vector map was generated in the level of detail 0 to analyse information content.

Keywords

Accuracy Digital elevation models Geospatial analysis Image fusion Image quality Optical imaging Pléiades 1A 

References

  1. Abduelmola AEA (2016) High resolution satellite image analysis and rapid 3D model extraction for urban change detection. University of Porto, PortoGoogle Scholar
  2. Airbus (2012) Pléiades imagery user guide. V 2.0 edn.Google Scholar
  3. Alobeid A, Jacobsen K, Heipke C (2009) Building height estimation in urban areas from very high resolution satellite stereo images. In: ISPRS Hannover Workshop. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. pp 2–5Google Scholar
  4. Bagnardi M, González PJ, Hooper A (2016) High-resolution digital elevation model from tri-stereo Pleiades-1 satellite imagery for lava flow volume estimates at Fogo Volcano. Geophys Res Lett 43:6267–6275CrossRefGoogle Scholar
  5. Baillarin S, Panem C, Lebegue L, Bignalet-Cazalet F (2010) Pleiades HR imaging system: ground processing and products performance, few months before launch. In: Wagner W, Székely B (eds.): ISPRS TC VII Symposium – 100 Years ISPRS, Vienna, Austria, July 5–7, 2010. vol Part 7B. pp 51–55Google Scholar
  6. Baudoin A (2004) Beyond SPOT 5: Pléiades, Part of the French-Italian Program ORFEO. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Istanbul, Turkey, July 12–23, 2004. vol Part B1. pp 260–267Google Scholar
  7. Bayık Ç, Topan H, Özendi M, Oruç M, Cam A, Abdikan S (2016) Geospatial analysis using remote sensing images: case studies of Zonguldak test field. Paper presented at the International Archives of Photogrammetry Remote Sensing and Spatial Informaton Sciences, Prague (Czech Republic),Google Scholar
  8. Bernard M, Decluseau D, L. Gabet, Nonin P (2012) 3D capabilities of Pleiades satellite. Paper presented at the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Melbourne, Australia, 25 August – 01 September 2012Google Scholar
  9. Blanchet G, Lebegue L, Fourest S, Latry C, Porez-Nadal F, Lacherade S, Thıebaut C (2012) Pleiades-HR innovative techniques for radiometric image quality commissioning. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Melbourne, Australia, 25 August – 01 September 2012. vol B1. pp 513–518CrossRefGoogle Scholar
  10. Boissin MB, Gleyzes A, Tinel C (2012) The Pléiades system and data distribution. In: IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany. pp 7098–7101.  https://doi.org/10.1109/IGARSS.2012.6352027
  11. Cam A, Topan H, Özendi M Oruç M (2014) Pléiades-1 A Görüntülerinin Gerçek Geometrik Çözünürlüğünün ve Radyometrik Kalitesinin Belirlenmesi. In: 5. Uzaktan Algılama ve Coğrafi Bilgi Sistemleri Sempozyumu, İstanbulGoogle Scholar
  12. Crete F, Dolmiere T, Ladret P, Nicolas M (2007) The blur effect: perception and estimation with a new no-reference perceptual blur metric. In: SPIE Human Vision and Electronic Imaging XII, San Jose, USA, 12 February 2007. p 64920I.  https://doi.org/10.1117/12.702790
  13. de Franchis C, Meinhardt-Llopis E, Michel J, Morel JM, Facciolo G (2014) Automatic sensor orientation refinement of Pléiades stereo images. In: Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International, 13-18 July 2014 2014. pp 1639–1642.  https://doi.org/10.1109/IGARSS.2014.6946762
  14. de Lussy F, Kubik P, Greslou D, Pascal V, Gigord P, Cantou JP, (2005) Pleiades-HR image system products and quality, Pleiades-HR image system products and geometric accuracy. In: ISPRS Hannover Workshop, Hannover, Germany. p 6 pagesGoogle Scholar
  15. Delvit JM et al (2012) Attitude assessment using Pleiades-HR capabilities. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B1:525–530.  https://doi.org/10.5194/isprsarchives-XXXIX-B1-525-2012 CrossRefGoogle Scholar
  16. Doyle FJ (1978) Digital terrain models: an overview. Photogramm Eng Remote Sens 44:1481–1485Google Scholar
  17. Flamanc D, Maillet G (2005) Evaluation of 3D city model production from Pleiades-HR satellite images and 2D ground maps International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVI-8/W27Google Scholar
  18. Fourest S, Kubik P, Lebègue L, Déchoz C, Lacherade S, Blanchet G (2012) Star-based methods for Pleiades HR commissioning. Int Arch Photogramm Remote Sens SpatInf Sci XXXIX-B1:531–536.  https://doi.org/10.5194/isprsarchives-XXXIX-B1-531-2012 CrossRefGoogle Scholar
  19. Greslou D, de Lussy F (2006) Geometric calibration of Pleiades location model. In: ISPRS Commission I Symposium “From Sensors to Imagery”, Paris, France, 4-6.5.2006. p 6 pagesGoogle Scholar
  20. Greslou D, deLussy F, Delvit JM, Dechoz C, Amberg V (2012) Pleiades-HR innovative techniques for geometric image quality commissioning. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B1Google Scholar
  21. Gruen A (1985) Adaptive least squares correlation: a powerful image matching technique. S Afr J Photogramm Remote Sens Cartogr 14:175–187Google Scholar
  22. Jacobsen K (2009) Effective resolution of digital frame images. In: ISPRS Hannover Workshop, Hannover. International Archieves of Photogrammetry, Remote Sensing and Spatial Information SystemsGoogle Scholar
  23. Jacobsen K, Topan H (2015) DEM generation with short base length Pléiades triplet. Int Arch Photogramm Remote Sens Spat Inf Sci XL-3/W2:81–86.  https://doi.org/10.5194/isprsarchives-XL-3-W2-81-2015 CrossRefGoogle Scholar
  24. Jacobsen K, Topan H, Cam A, Özendi M, Oruc M (2014) Radiometric and geometric characteristics of Pleiades images. Int Arch Photogramm Remote Sens Spatial Inf Sci XL-1:173–177.  https://doi.org/10.5194/isprsarchives-XL-1-173-2014 CrossRefGoogle Scholar
  25. Jacobsen K, Topan H, Cam A, Özendi M, Oruc M (2016) Image quality assessment of Pléiades-1A triplet bundle and pan-sharpened images. Photogramm Fernerkun 2016:141–152.  https://doi.org/10.1127/pfg/2016/0291 CrossRefGoogle Scholar
  26. Javan F, Samadzadegan F, Reinartz P (2013) Spatial quality assessment of pan-sharpened high resolution satellite imagery based on an automatically estimated edge based metric. Remote Sens 5:6539–6559.  https://doi.org/10.3390/rs5126539 CrossRefGoogle Scholar
  27. Kapnias D, Milenov P, Kay S (2008) Guidelines for best practice and quality checking of ortho imagery. European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen.  https://doi.org/10.2788/36028
  28. Kubik P, Pascal V (2004) Amethist: a method for equalization thanks to histograms. In: Meynart R, Neeck SP, Shimoda H (eds) SPIE 5570, sensors, systems, and next-generation satellites VIII, Maspalomas, Canary Islands, pp 256–267.  https://doi.org/10.1117/12.565091 CrossRefGoogle Scholar
  29. Kubik P, Pascal V, Latry C, Baillarin S (2005) Pleiades image quality: from users’ needs to products definition. 5978:59780L-59780L-59711.  https://doi.org/10.1117/12.627570
  30. Lachérade S, Fourest S, Gamet P, Lebègue L (2012) Pleiades absolute calibration: inflight calibration sites and methodology. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B1:549–554.  https://doi.org/10.5194/isprsarchives-XXXIX-B1-549-2012 CrossRefGoogle Scholar
  31. Lebegue L, Greslou D, deLussy F, Fourest S, Latry C, Kubik P, Delvit J-M (2010) Pleiades-HR image quality commissioning foreseen methods. In: International Geoscience and Remote Sensing Symposium 2010, Hawaii. pp 1675–1678Google Scholar
  32. Lebègue L, Greslou D, de Lussy F, Fourest S, Blanchet G, Latry C, Lachérade L, Delvit JM, Kubik P, Déchoz C, Amberg V, Porez-Nadal F (2012) Pleiades-HR image quality commissioning. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX-B1:561–566CrossRefGoogle Scholar
  33. Nasir S, Iqbal IA, Ali Z, Shahzad A (2015) Accuracy assessment of digital elevation model generated from Pleiades tri stereo-pair. In: 7th International Conference on Recent Advances in Space Technologies (RAST). IEEE, pp 193–197Google Scholar
  34. OGC (1999) The OpenGIS® Abstract Specification Topic 6: The Coverage Type and its Subtypes Version 4Google Scholar
  35. Özendi M, Topan H, Oruç M, Cam A (2016) Pan-sharpening quality investigation of PLÉIADES-1A images. Geocarto Int 31:881–890.  https://doi.org/10.1080/10106049.2015.1094520 CrossRefGoogle Scholar
  36. Panem C, Bignalet-Cazalet F, Baillarin S (2012) Pleiades-HR system products performance after in-orbit commissioning phase. Int Arch Photogramm Remote Sens Spat Inf Sci XXXIX:567–572.  https://doi.org/10.5194/isprsarchives-XXXIX-B1-567-2012 CrossRefGoogle Scholar
  37. Perko R, Raggam H, Gutjahr K, Schardt M (2014) Assessment of the mapping potential of Pléiades stereo and triplet data. ISPRS Ann Photogramm Remote Sens Spatial Inf Sci II-3:103–109.  https://doi.org/10.5194/isprsannals-II-3-103-2014 CrossRefGoogle Scholar
  38. Poli D, Remondino F, Angiuli E, Agugiaro G (2015) Radiometric and geometric evaluation of GeoEye-1, WorldView-2 and Pléiades-1A stereo images for 3D information extraction. ISPRS J Photogramm Remote Sens 100:35–47.  https://doi.org/10.1016/j.isprsjprs.2014.04.007 CrossRefGoogle Scholar
  39. Qayyum A, Malik AS, Nuafal M, Iqbal M, Abdullah MF (2015a) Design of digital elevation model based on orthorectified satellite stereo images. In: Signal Processing and Communication Systems (ICSPCS), 9th International Conference on, 2015a. IEEE, pp 1–6Google Scholar
  40. Qayyum A, Malik AS, Saad MNBM (2015b) Comparison of digital elevation models based on high resolution satellite stereo imagery. In: Space Science and Communication (IconSpace), International Conference on, 2015b. IEEE, pp 203–208Google Scholar
  41. Qayyum A, Malik AS, Saad MNBM (2015c) Evaluation of digital elevation model using rational polynomial coefficient based on HR Pleiades satellite stereo imagery. In: Signal and Image Processing Applications (ICSIPA), IEEE International Conference on, 2015c. IEEE, pp 32–37Google Scholar
  42. Schowengerdt RA (1997) Remote sensing, models and methods for image processing, 2nd edn. Academic Press, CambridgeGoogle Scholar
  43. Sefercik UG, Alkan M, Buyuksalih G, Jacobsen K (2013) Generation and validation of high-resolution DEMs from Worldview-2 stereo data. Photogramm Rec 28:362–374.  https://doi.org/10.1111/phor.12038 CrossRefGoogle Scholar
  44. Sofia G, Bailly JS, Chehata N, Tarolli P, Levavasseur F (2016) Comparison of Pleiades and LiDAR digital elevation models for terraces detection in farmlands. IEEE J Sel Top Appl Earth Observ Remote Sens 9:1567–1576.  https://doi.org/10.1109/JSTARS.2016.2516900 CrossRefGoogle Scholar
  45. Stumpf A, Malet JP, Allemand P, Ulrich P (2014) Surface reconstruction and landslide displacement measurements with Pléiades satellite images. ISPRS J Photogramm Remote Sens 95:1–12.  https://doi.org/10.1016/j.isprsjprs.2014.05.008 CrossRefGoogle Scholar
  46. Suliman A, Zhang Y (2015) Development of line-of-sight digital surface model for co-registering off-nadir VHR satellite imagery with elevation data. IEEE J Sel Top Appl Earth Observ Remote Sens 8:1913–1923CrossRefGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  1. 1.Engineering Faculty, Department of Geomatics EngineeringZonguldak Bülent Ecevit UniversityZonguldakTurkey
  2. 2.Institute of Photogrammetry and GeoInformationGottfried Wilhelm Leibniz University HannoverHannoverGermany
  3. 3.Engineering Faculty, Department of Geomatics EngineeringErciyes UniversityKayseriTurkey

Personalised recommendations