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Estimating statistical errors in retrievals of ice velocity and deformation parameters from satellite images and buoy arrays

机译:从卫星图像和浮标阵列检索冰速度和变形参数中的统计误差

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The objective of this note is to provide the background and basic tools to estimate the statistical error of deformation parameters that are calculated from displacement fields retrieved from synthetic aperture radar (SAR) imagery or from location changes of position sensors in an array. We focus here specifically on sea ice drift and deformation. In the most general case, the uncertainties of divergence/convergence, shear, vorticity, and total deformation are dependent on errors in coordinate measurements, the size of the area and the time interval over which these parameters are determined, as well as the velocity gradients within the boundary of the area. If displacements are calculated from sequences of SAR images, a tracking error also has to be considered. Timing errors in position readings are usually very small and can be neglected. We give examples for magnitudes of position and timing errors typical for buoys and SAR sensors, in the latter case supplemented by magnitudes of the tracking error, and apply the derived equations on geometric shapes frequently used for deriving deformation from SAR images and buoy arrays. Our case studies show that the size of the area and the time interval for calculating deformation parameters have to be chosen within certain limits to make sure that the uncertainties are smaller than the magnitude of deformation parameters.
机译:本说明的目的是提供背景和基本工具来估计从合成孔径雷达(SAR)图像检出的位移场或从阵列中位置传感器的位置变化来估计从位移场计算的变形参数的统计误差。我们专注于海冰漂移和变形。在最常规的情况下,发散/收敛,剪切,涡度和总变形的不确定性取决于坐标测量中的误差,区域的尺寸和确定这些参数的时间间隔以及速度梯度在该地区的边界内。如果从SAR图像的序列计算位移,则还必须考虑跟踪误差。位置读数中的定时错误通常很小,可以忽略。我们为浮标和SAR传感器典型的位置和定时误差提供了典型的示例,在后一种情况下补充了跟踪误差的大小,并在经常用于从SAR图像和浮标阵列中导出变形的几何形状上的衍生方程。我们的案例研究表明,面积和计算变形参数的时间间隔必须在某些限度内选择,以确保不确定性小于变形参数的大小。

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