Automated Processing of Declassified KH-9 Hexagon Satellite Images for Global Elevation Change Analysis Since the 1970s

Frontiers in Earth Science

卷:8

David Shean¹  Alex S. Gardner²  Romain Hugonnet³  Oleg Alexandrov⁵  Scott McMichael⁵  Mauro Marty⁶  Amaury Dehecq⁶ 

[1] Civil and Environmental Engineering, University of Washington, Seattle, WA, United States;

[2] Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States;

[3] Laboratoire d'Etudes en Géophysique et Océanographie Spatiales, Université de Toulouse, Centre National de la Recherche Scientifique, Centre National de la Recherche Scientifique, IRD, UPS, Toulouse, France;

[4] Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zürich, Zürich, Switzerland;

[5] NASA Ames Research Center, Moffet Field, CA, United States;

[6] Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), Birmensdorf, Switzerland;

关键词: stereo;    digital elevation model;    photogrammetry;    historical satellite imagery;    glacier changes;    uncertainty propagation;   

DOI  :  10.3389/feart.2020.566802

来源: DOAJ

【 摘 要 】

Observing changes in Earth surface topography is crucial for many Earth science disciplines. Documenting these changes over several decades at regional to global scale remains a challenge due to the limited availability of suitable satellite data before the year 2000. Declassified analog satellite images from the American reconnaissance program Hexagon (KH-9), which surveyed nearly all land surfaces from 1972 to 1986 at meter to sub-meter resolutions, provide a unique opportunity to fill the gap in observations. However, large-scale processing of analog imagery remains challenging. We developed an automated workflow to generate Digital Elevation Models and orthophotos from scanned KH-9 mapping camera stereo images. The workflow includes a preprocessing step to correct for film and scanning distortions and crop the scanned images, and a stereo reconstruction step using the open-source NASA Ames Stereo Pipeline. The processing of several hundreds of image pairs enabled us to estimate reliable camera parameters for each KH-9 mission, thereby correcting elevation biases of several tens of meters. The resulting DEMs were validated against various reference elevation data, including snow-covered glaciers with limited image texture. Pixel-scale elevation uncertainty was estimated as 5 m at the 68% confidence level, and less than 15 m at the 95% level. We evaluated the uncertainty of spatially averaged elevation change and volume change, both from an empirical and analytical approach, and we raise particular attention to large-scale correlated biases that may impact volume change estimates from such DEMs. Finally, we present a case study of long-term glacier elevation change in the European Alps. Our results show the suitability of these historical images to quantitatively study global surface change over the past 40–50 years.

【 授权许可】

Unknown