相對門檻優化永久散射體干涉雷達技術於地表變形偵測之應用;Using Relative Thresholds to Investigate Surface Deformation by Persistent Scatterer InSAR

NCUIR > Engineering College > Graduate Institute of Civil Engineering > Electronic Thesis & Dissertation > Item 987654321/66739

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/66739

Title:	相對門檻優化永久散射體干涉雷達技術於地表變形偵測之應用;Using Relative Thresholds to Investigate Surface Deformation by Persistent Scatterer InSAR
Authors:	蔡長興;Tsai,Chang-Xing
Contributors:	土木工程學系
Keywords:	相對門檻;永久散射體;干涉合成孔徑雷達;Relative Threshold;Persistent Scatterer;InSAR
Date:	2015-01-27
Issue Date:	2015-03-16 15:08:10 (UTC+8)
Publisher:	國立中央大學
Abstract:	永久散射體干涉合成孔徑雷達 (PSInSAR)是一種提供長期觀測地表變形的方法。它解決了差分干涉合成孔徑雷達技術用於長時間觀測時導致同調性降低，進而使誤差上升的問題。此方法是藉由尋找影像中訊號穩定的點，利用該點特性計算地表變形率將會使準確性上升。然而在此方法中，是使用一固定值當作門檻值，而門檻值之設置相當依靠經驗。因此，影像中若有同調性較低之影像將會影響所有的圖像，使影像處理者難以選擇。而經過分析合成孔徑雷達圖像，影像同調性分布近似於常態分布。經過一系列的統計檢驗，確認特性後，使用該特性及能排除影像中相對不穩定的點來獲得永久散射體。使用此方法可以自動化獲得門檻和該門檻的信心水準，跟原方法比較可以獲得較為客觀及可信之結果。另一方面，所計算出的門檻值不受各影像間差異（如季節）影響，使得成果有一定程度的提升。另外該門檻值可通過調整相關門檻中使用者所需之信心水準，以滿足不同區域的研究。;Permanent scatterers (PS) InSAR is a method providing long-term observation radar surface deformation. It resolved the problem that InSAR technique is used for a long time observing. This method is looking for stable points. After finding the PS points and calculating the phase of PS points, the information can be calculated to the deformation speed. However, in this method, the threshold setting is dependent on experience and for a given value. Therefore, the uneven quality of particular image will impact all the images and make users hard to choose. With analyzing synthetic aperture radar images, we find that the image coherence distribution is similar to normal distribution. After the distribution identified, the threshold could be set by the statistical property through excluding the points within the confidence interval, and the remaining points are what we need. This method can give an objective and credible result without manual adjusting. We don’t need to get involved through the experience of setting and other processing experience. On the other hand, the calculated threshold individual with each image will not be affected by other images (like seasons), but also effectively solve the problem that image quality is uneven. By the way, the threshold can be regulated by changing the confidence level to satisfy the different research area.
Appears in Collections:	[Graduate Institute of Civil Engineering] Electronic Thesis & Dissertation

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