Table1_v1_Automated Processing of Declassified KH-9 Hexagon Satellite Images for Global Elevation Change Analysis Since the 1970s.XLSX

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.

观测地球表面地形变化对于诸多地球科学学科而言均具有至关重要的意义。然而，由于2000年之前适用的卫星数据资源有限，在区域乃至全球尺度上记录数十年间的此类地形变化仍是一项挑战。美国侦察计划“六角”（Hexagon, KH-9）解密的模拟卫星图像，于1972年至1986年间以米级乃至亚米级分辨率对几乎全部陆地表面进行了测绘，为填补观测数据空白提供了独一无二的契机。但大规模处理模拟影像仍面临诸多难题。我们开发了一套自动化工作流，可从经扫描的KH-9测绘相机立体影像中生成数字高程模型（Digital Elevation Models, DEM）与正射影像。该工作流包含两个核心步骤：一是预处理步骤，用于校正胶片与扫描畸变并裁剪扫描影像；二是立体重建步骤，采用开源的NASA艾姆斯立体管线（NASA Ames Stereo Pipeline）完成。通过处理数百幅影像对，我们得以为每一次KH-9任务估算可靠的相机参数，进而校正数十米量级的高程偏差。所生成的DEM已通过多种参考高程数据进行了验证，其中包括图像纹理有限的积雪覆盖冰川。在68%置信水平下，像素尺度的高程不确定性约为5米；在95%置信水平下，该不确定性则小于15米。我们分别通过经验方法与解析方法，对空间平均高程变化与体积变化的不确定性进行了评估，并特别指出了可能影响此类DEM体积变化估算结果的大规模相关偏差问题。最后，我们以欧洲阿尔卑斯山区的长期冰川高程变化为例开展了案例研究。研究结果表明，这类历史影像可用于定量分析过去40至50年间的全球地表变化。