The integration of Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) data with Optical Photogrammetric Satellite Stereo Imagery (OPSSI) for Block Adjustment (BA) has emerged as a novel approach for generating large-area, high-accuracy Digital Elevation Models (DEMs). However, owing to the discrepancies between these two data platforms and the systematic errors of their sensors, errors arise in the BA fusion outcomes during the matching process of the two datasets. To tackle this issue, this paper proposes a method aimed at enhancing the accuracy of the BA process. Initially, the multi-characteristic constraint is used to filter the ICESat-2 ATL08 product to obtain control points and check points. Subsequently, the Terrain Matching Correction is applied to control points, and then integrated with the GF-7 OPSSI for BA to generate DEM. Ultimately, the check points are employed to assess the accuracy of the established DEM. Experiments in a 2,000 km2 test area in the Wuding River Basin show that: (1) The inclusion of ICESat-2 data has remarkably enhanced the accuracy of DEM modeling utilizing GF-7 OPSSI, and the Root Mean Square Error (RMSE) has been reduced from the range of 5–10 m to 2–6 m. (2) Multi-characteristic constraint filtering is crucial for the identification of high quality ICESat-2 control points in flat and low relief areas. When implementing this filtering method, the established criteria should comprehensively consider both the quantity and the spatial distribution of control points to ensure optimal results. (3) Terrain Matching Correction on ICESat-2 data has effectively elevated the vertical accuracy of DEM modeling, particularly in regions with flat terrain. The RMSE of the vertical accuracy in such areas can be decreased by 1–3 m. In summary, the integration of spaceborne laser altimeter data with OPSSI holds immense significance for the production of large-scale and high-accuracy DEMs, offering a promising solution for terrain modeling and analysis on regional scales.

中文翻译：

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增强 GF-7 立体影像的大面积 DEM 建模：将 ICESat-2 数据与多特征约束过滤和地形匹配校正集成


将冰、云和陆地高程卫星 2 （ICESat-2） 数据与光学摄影测量卫星立体影像 （OPSSI） 集成以进行区域网平差 （BA） 已成为生成大面积、高精度数字高程模型 （DEM） 的新方法。然而，由于这两个数据平台之间的差异以及它们传感器的系统误差，在两个数据集的匹配过程中，BA 融合结果会出现误差。为了解决这个问题，本文提出了一种旨在提高 BA 过程准确性的方法。最初，使用多特征约束对 ICESat-2 ATL08 产品进行过滤，以获得控制点和检查点。随后，将地形匹配校正应用于控制点，然后与 BA 的 GF-7 OPSSI 集成以生成 DEM。最终，这些检查点用于评估已建立的 DEM 的准确性。在武定河流域 2,000 km2 测试区的实验表明：（1） ICESat-2 数据的纳入显著提高了使用 GF-7 OPSSI 进行 DEM 建模的准确性， 均方根误差 （RMSE） 已从 5-10 m 的范围降低到 2-6 m。（2） 多特征约束滤波对于在平坦和低浮场区域中识别高质量的 ICESat-2 控制点至关重要。在实施这种过滤方法时，建立的标准应综合考虑控制点的数量和空间分布，以确保最佳结果。（3） ICESat-2 数据的地形匹配校正有效地提高了 DEM 建模的垂直精度，尤其是在地形平坦的地区。这些区域的垂直精度的 RMSE 可以减少 1-3 m。 综上所述，星载激光高度计数据与 OPSSI 的集成对于大规模和高精度 DEM 的生成具有重要意义，为区域尺度的地形建模和分析提供了有前途的解决方案。