An interferometric phase noise reduction method based on modified denoising convolutional neural network

Traditional interferometric synthetic aperture radar (InSAR) denoising methods normally try to estimate the phase fringes directly from the noisy interferogram. Since the statistics of phase noise are more stable than the phase corresponding to complex terrain, it could be easier to estimate the phase noise. In this paper, phase noises rather than phase fringes are estimated first, and then they are subtracted from the noisy interferometric phase for denoising. The denoising convolutional neural network (DnCNN) is introduced to estimate phase noise and then a modified network called IPDnCNN is constructed for the problem. Based on the IPDnCNN, a novel interferometric phase noise reduction algorithm is proposed, which can reduce phase noise while protecting fringe edges and avoid the use of filter windows. Experimental results using simulated and real data are provided to demonstrate the effectiveness of the proposed method

The Performance Analysis Based on SAR Sample Covariance Matrix

Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR) context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given

Monitoring land surface deformation using persistent scatterers interferometric synthetic aperture radar technique

Land subsidence is one of the major hazards occurring globally due to several reasons including natural and human activities. The effect of land subsidence depends on the extent and severity. The consequences of this hazard can be seen in many forms including damaged of infrastructures and loss of human lives. Although land subsidence is a global problem, but it is very common in urban and sub urban areas especially in rapidly developing countries. This problem needs to be monitored effectively. Several techniques such as land surveying, aerial photogrammetry and Global Positioning System (GPS) can be used to monitor or detect the subsidence effectively but these techniques are mostly expensive and time consuming especially for large area. In recent decades, Interferometric Synthetic Aperture Radar (InSAR) technique has been used widely for the monitoring of land subsidence successfully although this technique has several limitations due to temporal decorrelation, atmospheric effects and so on. However, the uncertainties related to InSAR technique have been reduced significantly with the recent Persistent Scatterers Interferometric Synthetic Aperture Radar (PSInSAR) technique which utilized a stack of interferograms generated from several radar images to estimate deformation by finding a bunch of stable points. This study investigates the surface deformation focusing on Kuala Lumpur, a rapidly growing city and Selangor using PSInSAR technique with a set of ALOS PALSAR images from 2007 to 2011. The research methodology consists of several steps of image processing that incudes i) generation of Differential Interferometric Synthetic Aperture Radar (DInSAR), ii) selection of Persistent Scatterers (PS) points, iii) removal of noise, iv) optimization of PS point selection, and v) generation of time series deformation map. However, special consideration was given to optimize the PS selection process using two master images. Results indicate a complete variation of mean line-of-sight (LOS) velocities over the study area. Stable areas (mean LOS=1.1 mm/year) were mostly found in the urban center of Kuala Lumpur, while medium rate of LOS (from 20 mm/year to 30 mm/year) was observed in the south west area in Kuala Langat and Sepang districts. The infrastructures in Kuala Lumpur are mostly stable except in Kuala Lumpur International Airport (KLIA) where a significant subsidence was detected (28.7 mm/year). Meanwhile, other parts of the study area such as Hulu Langat, Petaling Jaya and Klang districts show a very low and non-continuous movement (LOS < 20 mm/year), although comparatively higher subsidence rate (28 mm/year) was detected in the mining area. As conclusion, PSInSAR technique has a potential to monitor subsidence in urban and sub urban areas, but optimization of PS selection processing is necessary in order to reduce the noise and get better estimation accuracy

Modelação de processos de rotura sísmica através de dados de observação da deformação superficial

Nesta dissertação foi desenvolvida uma metodologia baseada no cruzamento de diferentes técnicas e de dados geodésicos e sísmicos, para estudar o processo de rotura de sismos. A metodologia consiste, numa primeira fase, em determinar o campo de deslocamento cossísmico produzido por um evento, através da técnica InSAR. Numa fase seguinte o modelo de deslocamentos cossísmicos é determinado através das equações de Okada utilizando o modelo de distribuição de deslizamentos obtido pela inversão das formas de onda registadas em estações de banda larga a distâncias telessísmicas. Para comparar o modelo de deslocamentos cossísmicos com o interferograma é aplicado um algoritmo que projeta os deslocamentos do modelo na direção do satélite e de seguida procura a região homóloga entre esse modelo e o interferograma, pelo cálculo da máxima correlação entre ambas as regiões, que resulta também na relocalização da fonte. O processo de inversão/modelação da deformação/comparação é repetido iterativamente até se conseguirem bons ajustes simultaneamente nos dados sísmicos e geodésicos. Esta metodologia foi aplicada no estudo dos sismos ocorridos a 12 de janeiro de 2010 no Haiti; a 22 de fevereiro de 2006 em Moçambique; e a 21 de maio de 2003 na Argélia. No estudo do sismo ocorrido no Haiti foi utilizado um par interferométrico do sensor ALOSPALSAR, relativo à órbita descendente 447, onde foi medido o deslocamento máximo de ~70 cm na direção do satélite. O conjunto de 32 registos das formas de onda permitiu obter o modelo de rotura e respetivos deslocamentos superficiais, para quatro soluções de parâmetros da geometria da falha. Após a comparação entre os modelos de deslocamentos e o interferograma é concluído que os parâmetros que melhor justificam a deformação observada no interferograma são: a falha orientada segundo um azimute de 262º, com uma inclinação de 42º para norte e um rake médio de 42º. No estudo do sismo de Moçambique foi usado um par interferométrico do satélite ENVISAT e um conjunto de 36 registos telessísmicos. Desta forma foi possível concluir que a rotura ocorreu na direção 165ºN numa falha com inclinação de 76º para oeste e os deslizamentos ocorreram com um rake médio de 90º, sobre uma falha com um comprimento de 40.6 km por 29 km de largura. Neste modelo de rotura foi obtido o momento sísmico de 3.9x1019Nm, com um deslizamento máximo de 4.1 m próximo do hipocentro. A modelação dos deslocamentos cossísmicos representa bem os deslocamentos observados no terreno e medidos no interferograma. Para o estudo do sismo de Zemmouri-Boumedès foram utilizados alguns pares interferométricos do satélite ENVISAT, as medições realizadas ao longo da costa da Argélia e um conjunto de 28 registos das formas de onda. Os interferogramas revelaram uma fraca coerência, mas mesmo assim foi possível observar 19 franjas (~53 cm) a oeste de Boumerdès. Os parâmetros que justificam os deslocamentos cossísmicos são: strike=64º; dip=50º; rake=97º. Este modelo permite gerar a sobre-elevação observada ao longo da costa, como a configuração das franjas interferométricas. O plano desta solução localiza-se no mar, a 9 km da linha de costa e o respetivo epicentro está localizado no mar; Modelling of active internal processes through observation data of surface deformation. ### Abstract: In this dissertation a methodology that consists of the cross of different techniques and geodetic and seismic data, to study the earthquake rupture process was developed. The methodology consists initially in determining the field of co-seismic displacements caused by an event using the InSAR technique. In a next step the co-seismic displacements model is determined by the equations of Okada using the model of rupture obtained from the inversion of waveforms recorded in the broadband stations at teleseismic distances. To compare the co-seismic displacement model with the interferogram is applied an algorithm that project the model of the displacements toward the satellite and is then applied to search the homologous region between the two region, which also results the re-location of the source. The process of inversion/modeling of the deformation/comparison is repeated iteratively until achieving good adjustments in both seismic and geodetic data. This methodology was applied in the study of the earthquakes that occurred on January 12, 2010 in Haiti, on February 22, 2006 in Mozambique, and on May 21, 2003 in Algeria. In the Haiti earthquake study an interferometric pair of the ALOS-PALSAR sensor of the descending orbit 447 was used, where it was measured the maximum co-seismic displacement of ~70 cm in the direction of the satellite. The set of 32 registers of the waveforms allows obtaining the model of the rupture and the displacements on the earth surface, for four solutions with different geometries parameters. After comparing the models of the displacements with the interferogram is concluded that the parameters that better explain the deformation observed in the interferogram is the fault azimuth of 262° with an inclination of 42º north and the rupture occurred with an rake of 42º. In the Mozambique earthquake study was used an interferometric pair of the ENVISAT satellite and a set of 36 teleseismic registration. Thus it was concluded that the rupture occurred with an azimuth of 165º North with an inclination of 76º westward, the slip occurred with a rake of 90°, on a fault with a length of 40.6 km to 29 km wide. The seismic moment obtained was 3.9x1019 Nm, the maximum slip was 4.1m near the hypocenter and the model of the displacements is well fit to the co-seismic displacements observed on the coastline and in the measurements in the interferogram. To study the earthquake Zemmouri-Boumedès were used some interferometric pairs of the ENVISAT satellite, the measurements along the coastline of Algeria and a set of 28 records of waveforms. The interferograms revealed a low coherence, but it was still possible to observe 19 fringes (~53 cm) west of Boumerdès. The parameters that better justify the coseismic displacements are strike=64°, dip=50°, rake=97º. This model allows us to cause the uplift observed along the coastline, such as the configuration of the interferometric fringes. The plan of this solution is located at the sea, 9 km of coastline and also its epicenter is located at the see