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Tectonic Deformation Estimation using Stream Gradients: Nonparametric Function Estimation from Difference Data using Splines and Conjugate Gradients

机译:使用流梯度的构造变形估计:使用样条和共轭梯度从差异数据进行非参数函数估计

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In 1811-1812 three great (8.0+) earthquakes occurred near New Madrid, Missouri. We estimate coseismic deformation in this area using stream elevation data from topographic maps. Streams have a natural profile, the gradient of which depends on the resistance of underlying sediment and the volume of stream flow. If tectonic processes elevate the upstream end of a segment a different amount than the downstream end, the stream will attempt to return to its natural gradient by incising, aggrading, or altering its sinuousity. This adjustment takes time, so deviations from the natural gradient may indicate geologically recent deformation.We use penalized regression splines to estimate the natural stream profile and the deformation of the ground surface Estimation of the natural profile and deformation is based on nonparametric regression of the form y_2 - y_1 = f(x_2) - f(x_1). This may be formulated as a linear regression problem, potentially with millions of parameters when estimating large-scale surfaces; the system may be solved using conjugate gradient methods.
机译:在1811-1812年,密苏里州新马德里附近发生了三场大地震(8.0级以上)。我们使用地形图上的河流标高数据估算该地区的同震变形。溪流具有自然剖面,其梯度取决于下层沉积物的阻力和溪流流量。如果构造过程将分段的上游端抬高的量与下游端的抬高量不同,则河流将试图通过切开,渐进或改变其曲折度而返回其自然梯度。这种调整需要时间,因此与自然坡度的偏差可能表示地质上最近的变形。 我们使用罚分回归样条来估计自然流剖面和地表变形。自然剖面和变形的估计基于形式为y_2-y_1 = f(x_2)-f(x_1)的非参数回归。这可以表述为线性回归问题,在估计大型曲面时可能具有数百万个参数。该系统可以使用共轭梯度法求解。

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