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1.昆明理工大学国土资源工程学院,云南 昆明,650093
2.云南省定量遥感重点实验室(筹),云南 昆明,650093
3.云南省山地灾害天空地一体化智慧监测国际联合实验室,云南 昆明,650093
4.云南大学地球科学学院,云南 昆明,650500
Received:24 September 2024,
Published:05 August 2025
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尹谢兵,李梦华,俸彬,等.NCC堆叠的SAR POT方法参数优化及雅弄冰川流速提取[J].武汉大学学报(信息科学版),2025,50(8):1705-1718.
YIN Xiebing,LI Menghua,FENG Bin,et al.Parameter Optimization of the SAR POT Method for NCC Stacking and the Yanong Glacier Velocity Extraction[J].Geomatics and Information Science of Wuhan University,2025,50(8):1705-1718.
尹谢兵,李梦华,俸彬,等.NCC堆叠的SAR POT方法参数优化及雅弄冰川流速提取[J].武汉大学学报(信息科学版),2025,50(8):1705-1718. DOI:10.13203/j.whugis20240303
YIN Xiebing,LI Menghua,FENG Bin,et al.Parameter Optimization of the SAR POT Method for NCC Stacking and the Yanong Glacier Velocity Extraction[J].Geomatics and Information Science of Wuhan University,2025,50(8):1705-1718. DOI:10.13203/j.whugis20240303
山地冰川表面运动特征对于识别冰川链式灾害和研究全球气候变化具有重要意义。基于影像匹配的像素偏移量追踪(pixel offset tracking,POT)方法是提取冰川表面大梯度形变的有效手段,然而POT方法的测量精度与影像分辨率密切相关,周期性获取的Sentinel-1分辨率较低(约5×20 m),在狭长形态的山地冰川上使用小窗口匹配时噪声的影响大,归一化互相关系数(normalized cross-correlation,NCC)峰值低,难以获取可靠的冰川位移。利用时序影像对的NCC堆叠提高NCC峰值,降低噪声的影响,牺牲了一定的时间分辨率来提高POT方法小窗口匹配的精度。通过对比堆叠数、搜索距离、匹配窗口大小等不同参数设置对实验结果的影响,提供POT方法计算位移的最佳参数组合策略。将该方法应用于雅弄冰川表面流速提取,使用2017年10月—12月间Sentinel-1升轨数据集,提取了该时段冰川表面的形变。进行NCC堆叠后,非冰川区域的噪声被很好的抑制,冰川区域显示出了更强的空间覆盖和空间连续。稳定区域速度残差的平均值和方差都得到了不同程度的减小,堆叠NCC计算的速度残差均值比单像对NCC减小到1/2以下,速度残差的标准差减小到原来的1/3,大多数区域都表现出了强信噪比增益。
Objective
2
The surface movement characteristics of mountain glaciers are crucial for identifying potential glacial chain disasters and studying global climate change. The pixel offset tracking (POT) method based on image matching is an effective method of detecting large-gradient deformations on glacier surfaces. However
the accuracy of the POT method is closely related to image resolution. The Sentinel-1 imagery
acquired at regular intervals
has a relatively low resolution (approximately 5×20 m). In the case of small window matching on narrow mountain glaciers
the method is highly susceptible to noise
which reduces normalized cross-correlation (NCC) peak values and hinder the acquisition of reliable glacier displacement measurements.
Method
2
To improve NCC peak values and reduce noise interference
this study utilizes NCC stacking from time-series image pairs
which enhances the accuracy of the POT method with small window matching
albeit at the expense of some temporal resolution. By comparing the effects of different parameter settings
such as the number of stackings
search distance
and matching window size on the experimental results
the study offers an optimal strategy for parameter selection when calculating displacement using the POT method.
Results
2
The settings of parameters like search distance and matching window size in POT calculations significantly influence experimental outcomes. Compared to single-image pair calculations with the same parameter settings
NCC stacking significantly improves the spatial continuity and coverage of the velocity field of the Yanong Glacier. Additionally
the mean and variance of velocity residuals in stable regions are reduced to varying degrees
with most areas exhibiting a strong signal-to-noise ratio gain.
Conclusion
2
The settings for the search window and matching window are crucial for ensuring accurate displacement tracking. Larger windows tend to produce better displacement field results but may smooth out the edges and local details of the glacier. Using NCC stacking allows for robust tracking of glacier velocity on smaller windows
achieving coverage comparable to large-template pairwise NCC. This makes NCC stacking the preferred method
especially when the template size is constrained by the area of small-scale glaciers.
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