Fast Statistically Homogeneous Pixel Selection for Covariance Matrix Estimation for Multitemporal InSAR

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

Zhao

Wang

et al. 2018

ABSTRACT:SAR interferograms are often contaminated by random noises related to temporal decorrelation, geometrical decorrelation and thermal noises, which makes the fringes obscured and greatly decreases the density of the coherent target and the accuracy of InSAR deformation results, especially for the landslide monitoring in vegetated region and in rainy season. Two different SAR interferogram filtering methods, that is Goldstein filter and homogeneous pixels filter, for one specific landslide are compared. The results show that homogeneous pixels filter is better than Goldstein one for small-scale loess landslide monitoring, which can increase the density of monitoring points. Moreover, the precision of InSAR result can reach millimeter by comparing with GPS time series measurements.

Section: Methodsmentioning

confidence: 99%

“…The core of fast statistically homogeneous pixels selection is to construct the confidence interval for each pixel by applying the central limit theorem, and then determines homogeneous pixels using this interval (Jiang et al, 2015;Jiang et al, 2016 …”

Section: Fast Statistically Homogeneous Pixel Selection Algorithmmentioning

confidence: 99%

Mt-Insar Landslide Monitoring With the Aid of Homogeneous Pixels Filter

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

Zhao

Wang

et al. 2018

“…Hence, a multilooking operation is firstly adopted to improve the coregistration accuracy and reduce phase noise. A non-local filter [44] and a robust coherence calculation [45] are adopted to enhance the success rate of phase unwrapping. Next, the phase unwrapping is directly executed by using minimum cost flow (MCF) method [46].…”

Section: Methodsmentioning

confidence: 99%

Recent Landslide Movement in Tsaoling, Taiwan Tracked by TerraSAR-X/TanDEM-X DEM Time Series

Zhang

et al. 2017

Remote Sensing

Abstract:The Tsaoling Landslide in Taiwan has captured attentions of researchers worldwide due to its frequent catastrophic failure and distinctive features. Thanks to the launch of TerraSAR-X/TanDEM-X (TSX/TDX) constellation, retrieval of global DEM with high spatial resolution and accuracy becomes possible, which is extremely useful for the study of natural hazards (e.g., landslides) globally. We attempt here for the first time to track recent landslide movements in Tsaoling Taiwan by analyzing DEM time series reconstructed from TSX/TDX image pairs. Quality improvement of InSAR derived DEM through an iterated differential operation is addressed during the data processing.

“…Currently, there are three basic methods to detect PSs, i.e., the methods based on normalized amplitude dispersion, phase stability, and correlation. Many attempts have been made to improve these methods [20] or design a hybrid strategy to incorporate three basic methods [21]. In the following part, three typical methods are introduced, respectively.…”

Section: Persistent Scatterer Detectionmentioning

confidence: 99%

A technical review on persistent scatterer interferometry

Jia

2016

J. Mod. Transport.

This article focuses on reviewing the technologies of persistent scatterer interferometry (PSI), which has been often used to monitor the deformation of Earth surface. Three critical steps in the implementation of PSI were introduced, i.e., (1) detection of persistent scatterer (PS), (2) construction of PS network, and (3) PSI modeling and solution. Finally, the main problems and outlooks on the PSI technique are discussed and given.