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Optimizing the Achievable Information Content Extraction from WorldView-4 Stereo Imagery

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Abstract

In 2016, DigitalGlobe’s third-generation commercial Earth observation satellite WorldView-4 (WV-4), which offered 31 cm spatial resolution for panchromatic imagery, was launched and was active up to January 2019. Together with WorldView-3, this is the highest ground resolution of civilian optical space-borne missions. In this study, the information content of WV-4′s pan-sharpened stereo imagery is comprehensively investigated by manual and automatic object extraction approaches in a study area with rolling urban topography. The potential of automatic extraction was maximised by a group of refinement methods supported by the normalised digital surface model (NDSM) generated from WV-4 stereo pair. The NDSM was used as an additional band in the segmentation for revealing the object height heterogeneity. The results demonstrated that our method increased the precision, completeness and overall quality of WV-4 automatic extraction up to 8.4% for the number of buildings and up to 3.4% for the road length.

Zusammenfassung

Optimierung des erreichbaren Informationsinhalts von WorldView-4 Stereomodellen. Im Jahr 2016 startete DigitalGlobe WorldView-4 (WV-4), einen kommerziellen Erdbeobachtungssatelliten der dritten Generation. Er lieferte eine Bodenauflösung von 31 cm und war bis Januar 2019 in Betrieb. Gemeinsam mit WorldView-3 hatte er die höchste Bodenauflösung eines nicht-militärischen optischen Fernerkundungssatelliten. In dieser Arbeit wird der Informationsgehalt der pan-geschärften Stereomodelle des WV-4 umfassend durch manuelle und automatische Datenerfassung in einem Gebiet untersucht, das durch Verstädterung und bewegte Topographie geprägt ist. Das Potenzial der automatischen Datenerfassung wurde durch eine Reihe von verfeinerten Methoden maximiert, unterstützt durch das aus dem WV-4 Stereomodell erzeugte normalisierte digitale Oberflächenmodell (NDSM). Der NDSM wurde als zusätzliche Ebene in der Segmentierung verwendet, um die Heterogenität der Objekthöhen zu ermitteln. Die Ergebnisse zeigten, dass unsere Methode die Genauigkeit, Vollständigkeit und Gesamtqualität der automatischen Datenerfassung bei WV-4-Szenen bis zu 8,4% bezüglich der Anzahl der Gebäude und bis zu 3,4% bezüglich der Straßenlänge gesteigert hat.

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Acknowledgements

We would like to thank Yıldız Technical University for supporting the acquisition of WV-4 stereo imagery in the scope of Scientific Research Project with ID: 3075. Finally, many thanks to Zonguldak Bulent Ecevit University for supporting the used software.

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Authors and Affiliations

  1. Department of Geomatics Engineering, Gebze Technical University, 41400, Kocaeli, Turkey

    Umut G. Sefercik

  2. Department of Geomatics Engineering, Yıldız Technical University, 34220, İstanbul, Turkey

    Mehmet Alkan

  3. Department of Geomatics Engineering, Zonguldak Bülent Ecevit University, 67100, Zonguldak, Turkey

    Can Atalay

  4. Institute of Photogrammetry and Geoinformation, Leibniz University Hannover, Nienburger Str. 1, 30167, Hannover, Germany

    Karsten Jacobsen

  5. İMP- BİMTAŞ, İstanbul Metropolitan Municipality, 34430, Beyoğlu, İstanbul, Turkey

    Gürcan Büyüksalih

  6. Department of Geomatics Engineering, İzmir Katip Çelebi University, 35620, İzmir, Turkey

    Serkan Karakış

Authors
  1. Umut G. Sefercik
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  2. Mehmet Alkan
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  3. Can Atalay
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  4. Karsten Jacobsen
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  5. Gürcan Büyüksalih
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Correspondence to Umut G. Sefercik.

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Sefercik, U.G., Alkan, M., Atalay, C. et al. Optimizing the Achievable Information Content Extraction from WorldView-4 Stereo Imagery. PFG 88, 449–461 (2020). https://doi.org/10.1007/s41064-020-00127-8

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  • DOI: https://doi.org/10.1007/s41064-020-00127-8

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