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Automated Coregistration of Repeat Digital Elevation Models for Surface Elevation Change Measurement Using Geometric Constraints

机译:使用几何约束进行曲面高程变化测量的重复数字高程模型的自动配准

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A large archive of digital elevation model (DEM) data spanning more than a decade is now available for a wide range of earth surface process studies. Precise coregistration is a critical step for obtaining accurate elevation change measurements from repeat DEMs. We present an algorithm for coregistering stereoscopic gridded DEMs that includes an automatic detection of control surfaces, a reliable estimation technique for defining a geometric relationship between DEMs through a 3-D conformal transformation, and a quality check (QC) for the confidence of the coregistration. For the control surface detection, we use a geometric constraint approach that uses similarities in slope, aspect, and height undulation as observation weights in an iterative transformation model solution. The QC is possible through the evaluation of the geometric similarities and the amount of detected relatively unchanged surfaces. We test our algorithm using a sample of repeat stereoscopic gridded DEMs from multiple sources over a rapidly changing glacier in Greenland. The algorithm results, on average, in a 24% decrease in the standard error, as obtained from elevation over stationary surfaces. The result is not sensitive to the distribution of the control surface. The QC metric provides a simple and effective criterion for parsing result quality in large data sets. Surface height decreases of ~ 110 and 200 m at the up-glacier and down-glacier ends of Kangerdlugssuaq Glacier in Greenland are observed between April 2001 and June 2010, respectively.
机译:现在,已有超过十年的大型数字高程模型(DEM)数据档案可用于各种地球表面过程研究。精确的配准是从重复DEM获得准确的高程变化测量值的关键步骤。我们提出了一种用于共配准立体网格化DEM的算法,该算法包括控制面的自动检测,用于通过3-D保形变换定义DEM之间的几何关系的可靠估计技术,以及用于质量保证的置信度的质量检查(QC) 。对于控制面检测,我们使用了几何约束方法,该方法在迭代变换模型解决方案中将坡度,坡度和高度波动的相似性用作观察权重。通过评估几何相似性和检测到的相对不变的表面的数量,可以进行质量控制。我们使用格陵兰快速变化的冰川上来自多个来源的重复立体网格化DEM样本来测试我们的算法。从固定表面的高程来看,该算法平均可使标准误差降低24%。结果对控制表面的分布不敏感。质量控制指标为解析大型数据集中的结果质量提供了一种简单有效的标准。在2001年4月至2010年6月之间,格陵兰Kangerdlugssuaq冰川的上冰川末端和下冰川末端的表面高度分别下降了约110 m和200 m。

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