Huanyin Yue

Improved Goldstein SAR Interferogram Filter Based on Adaptive-Neighborhood Technique

The Goldstein filter is one of the most commonly used filters for synthetic aperture radar (SAR) interferograms. The level of noise after filtering is controlled by a filter parameter, “alpha,” the value of which is determined by pixels within the moving window. However, when there exist different features within a single filter window, especially along the border, the value of alpha as estimated from the pixels within the window can be inaccurate and this may result in blurred borders in filtered interferograms. This letter proposes a modified Goldstein filter based on the adaptive-neighborhood technique. The idea of this method is to filter each pixel of the interferogram within an adjusted filter patch. In this adjusted patch, the adaptive-neighborhood pixels retain the original phase values while the “background” pixels are replaced by the mean value of adaptive-neighborhood pixels. Then, the Fourier transform of the complex phase is applied to this adjusted filter patch. The difficulty of estimating the noise level near the borders of different features can be decreased using this new filtering method. The quantitative results from real data show that this newly developed method could reduce the phase noise efficiently while also outperforming the Goldstein, Baran and empirical mode decomposition (EMD) filters by preserving the edges in interferograms.

Coal mining induced land subsidence monitoring using multiband spaceborne differential interferometric synthetic aperture radar data

The differential interferometric synthetic aperture radar (SAR)(DInSAR) technique has been applied to the earth surface deformation monitoring in many areas. In this paper, the DInSAR technique is used to process the spaceborne SAR data including C band ENVISAT ASAR, L band JERS SAR, and ALOS PALSAR data to derive the temporal land subsidence information in the Fengfeng coal mine area, Hebei province in China. Since JERS and ALOS do not have precise orbit, an orbit adjustment must be accomplished before the DInSAR interferogram was formed. Twenty-three differential interferograms are derived to show the temporal change of the land subsidence range and position. At the acquisition time of ENVISAT ASAR, the leveling in the Dashucun coal mine in Fengfeng area was carried, the historical excavation data in 8 coal mines in Fengfeng area from 1992 to 2007 were collected as well. In our analysis, the DInSAR results are compared with leveling data and historical excavation data. The comparison results show the DInSAR subsidence results are consistent with the leveling results and the historical excavation data, and the L band DInSAR shows more advantages than C band in the coal mining induced subsidence monitoring in a rural area. The feasibility and limitations in coal mining induced subsidence monitoring with DInSAR are analyzed, and the possibility of underground mining activity monitoring by spaceborne InSAR data is evaluated. The experimental results show that both C and L band can accomplish monitoring mining area subsidence, but C band has more restricted conditions of its perpendicular baseline. In order to get a satisfactory outcome in mining area subsidence by the DInSAR method, the time series of SAR images of every visit and SAR deformation interferograms should be archived.

Satellite radar reveals land subsidence over coal mines

Extracting coal from underground mines generally leads to subsidence of the overlaying land within a period of days to years. Underground mines are by their nature hidden from casual view. Land subsidence can give important clues as to the extent of a mine and its impact on the land.1, 2 Local governments can use this information to ensure miners are staying within permitted areas and to monitor environmental effects. Regulators and geologists conventionally monitor land subsidence with in situ field techniques that require expensive, time-consuming measurements on the ground that can be difficult or impossible to perform in steep mountain ranges and other inhospitable terrain. Here we show the feasibility of monitoring land subsidence caused by coal mining with multi-band differential synthetic aperture radar interferometry (DInSAR).3 In synthetic aperture radar (SAR) interferometry, airborne or spaceborne detectors scan Earth’s surface with radio waves to create a topographical map of the ground. DInSAR compares SAR interferometry data taken hours, days, or years apart and can show subtle topographical changes. We use DInSAR techniques to compare scans of land over coal mines on different dates to reveal land subsidence on scales as small as a few centimeters.4 We mapped land subsidence that occurred from 1993 to 1997 in the Fengfeng coal mine area in Hebei province in China using spaceborne SAR data. We used C band data from the Advanced Synthetic Aperture Radar (ASAR) on the Environmental Satellite (ENVISAT) and L band data from the Japanese Earth Research Satellite (JERS) and Advanced Land Observing Satellite Phased Array L type Synthetic Aperture Radar (ALOS PALSAR). JERS does not have a precise orbit. We set up a dynamical coordinate system using the radial, cross-track, and along-track directions for JERS SAR interferometric processing5 to adjust the spatial baseline and obtain an accurate DInSAR result. We also Figure 1. Distribution of lithic benchmarks in Dashucun coal mine and a contour map of land subsidence derived from the leveling data.

Modified four-pass differential SAR interferometry for estimating mountain glacier surface velocity fields

ABSTRACT Conventional four-pass differential synthetic aperture radar interferometry (DInSAR) assumes that there are no significant changes in the ground during the period between the acquisition times of SAR images for topographic DInSAR pairs. This assumption can rarely be satisfied for glacial areas due to their continuous movement. This letter proposes a modified four-pass DInSAR method without an external digital elevation model (DEM), taking into account glacier movement between the acquisition times of SAR images used to form topographic DInSAR pairs. An explicit expression of theoretical formulas for a modified four-pass DInSAR technique was derived for the first time, revealing that four-pass DInSAR considering ground movement of topographic pairs was equivalent to that of conventional four-pass DInSAR with a spatially varying nominal wavelength. Then the proposed method was tested with four Advanced Land Observing Satellite (ALOS) SAR images covering Dongkemadi glacier located on the Tibetan Plateau, China. An experiment with real data showed that the proposed method could obtain glacial flow patterns efficiently, and that the difference between two-pass DInSAR and the proposed method is a result of DEM bias and glacial thinning. The approach presented in this letter proved to be appropriate for monitoring glacial motion and provides a valuable tool for glacier studies, without the need of an external DEM.

Filtering SAR interferometric phase noise using a split-window model

ABSTRACT For interferometric synthetic aperture radar (InSAR) processing, the features of interferometric phase obtained in different coherence regions usually differ from each other. This is called region effect and exists in InSAR coherence map. When coherence value is used as a parameter to filter the phase noise, the result will be highly affected by this region effect. In this paper, we propose a new method of filtering InSAR phase noise using a split-window model. The idea of this method is to incorporate several filters into the model. Different filters will be used when dealing with phase noise locates in different coherence regions. The over-filtering or under-filtering caused by the coherence region effect can be eliminated in this method. As an example to demonstrate the superiority of this method, we incorporated an improved Goldstein filter and empirical mode decomposition filter into the current model. They were included to control phase noise level in the low- and high-coherence regions, respectively. The quantitative results obtained using a COnstellation of small Satellites for the Mediterranean basin Observation (COSMO-SkyMed) image pair over Kilauea volcano in Hawaiian demonstrate the advantages of the newly developed split-window model in filtering different types of noise.

Land subsidence monitoring in city area by time series interferometric SAR data

In this paper, the time series multi-image stack processing technique is implemented based on the ERS-1, ERS-2 SAR data set of cities of Las Vegas in America. A single master approach is used in the stack data processing based on the permanent scatterers processing technique invented by Ferretti et al. (1,2). After the differential phase model establishment and stable points selection, linear subsidence velocity and digital elevation model errors are estimated, non-linear subsidence velocity and atmospheric artifacts related to each SAR acquisition are separated, so a land subsidence history covering all the SAR data acquisitions in each city can be achieved. In our research, more test data in cities of China will be implemented in the next step.

Nonlinear Model for InSAR Baseline Error

Synthetic aperture radar (SAR) interferometric baseline parameters form important input for SAR interferometry. In this paper, a nonlinear error model is established for the SAR interferometric baseline and parameterized as a polynomial based on the natural nonlinearity of the orbit of a satellite. Unlike conventional models, the proposed model takes into account the nonlinear part of the baseline error. A theoretical derivation is performed based on the imaging geometry of interferometric SAR, and the results of the analysis show that the parameters of the nonlinear baseline error model can be obtained from the relationship between the orbit, the nominal baseline, the baseline error, and the residual interferogram phase. A sample data set from the Japanese Earth Resources Satellite-1 (JERS-1) L-band SAR is used to validate the proposed model, and the results indicated that the compensation of the residual interferogram phase of the test data is superior to that provided by conventional models.

SAR interferometric phase filtering technique based on bivariate empirical mode decomposition

The empirical mode decomposition (EMD) has been widely applied in filtering synthetic aperture radar interferograms. A noisy interferogram can be adaptively decomposed into different frequency modes by EMD. Then, the noise can be eliminated based on the partial reconstruction of relevant modes. However, most fine detail and noise of an interferogram often locate in the same mode, which will lead to an inaccurate estimation of noise level in a local region. In this paper, we proposed an improved filtering method based on bivariate EMD. The idea of our method is to decompose both the phase image and pseudo-coherence map of an interferogram using EMD. The filter level of an interferogram is then controlled by the parameters calculated from the bivariate EMD components. The quantitative results from both simulated and real data show that the bivariate EMD filtering method outperforms the original univariate EMD-based methods. It could achieve a balance between suppressing noise and preserving fine detail of an interferogram.

Sub-canopy soil moisture inversion using repeat pass Shuttle Imaging Radar C polarimetric synthetic aperture radar interferometric data

The advances in polarimetric synthetic aperture radar (SAR) interferometry techniques provide a promising way to extract sub-canopy surface parameters using processed SAR images. In this paper, we evaluate the fully maximum likelihood decomposition model of polarimetric SAR interferometry for sub-canopy soil moisture estimation. We further propose a methodology for sub-canopy soil estimation using repeat pass space-borne SIR-C (Shuttle Imaging Radar C) L-band polarimetric SAR interferometric data. The comparison of the inversion results with the field measurements and the climate data of Hotan region from 1951 to 2006 suggests good inversion potential of the proposed method.