Multi-temporal InSAR Techniques Research Articles

Landslide susceptibility mapping by remote sensing and geomorphological data: case studies on the Sorrentina Peninsula (Southern Italy)

The Sorrentina Peninsula is a densely populated area with high touristic impact. It is located in a morphologically complex zone of Southern Italy frequently affected by dangerous and calamitous landslides. This work contributes to the prevention of such natural disasters by applying a GIS-based interdisciplinary approach aimed to map the areas more potentially prone to trigger slope instability phenomena. We have developed the Landslide Susceptibility Index (LSI) combining five weighted and ranked susceptibility parameters on a GIS platform. These parameters are recognized in the literature as the main predisposing factors for triggering landslides. This work combines analyses conducted on Remote Sensing, Geo-Lithology and Morphometry data and it is organized in the following logical steps: i) Multi-temporal InSAR technique was applied to Envisat-ASAR (2003–2010) and COSMO-SkyMed (2013–2015) datasets to obtain the ground displacement time series and the relative mean ground velocity maps. InSAR allowed the detection of the areas that are subjected to ground deformation and the main affected municipalities; ii) Such deformation areas were investigated through airborne photo interpretation to identify the presence of geomorphological peculiarities connected to potential slope instability. Subsequently, some of these peculiarities were checked on the field; iii) In these deformation areas the susceptibility parameters were mapped in the entire territory of Amalfi and Conca dei Marini and then investigated with a multivariate analysis to derive the classes and the respective weights used in the LSI calculation. The resulting LSI map classifies the two municipalities with high spatial resolution (2m) according to five classes of instability. The map highlights that the high/very high susceptibility zones cover 6% of the investigated territory and correspond to potential landslide source areas characterized by 25°-70° slope angles. A spatial analysis between the map of the historical landslides and the areas classified according to susceptibility allowed testing of the reliability of the LSI Index, resulting in 85% prediction accuracy.

Geocoding Error Correction for InSAR Point Clouds

Persistent Scatterer Interferometry (PSI) is an advanced multitemporal InSAR technique that is capable of retrieving the 3D coordinates and the underlying deformation of time-coherent scatterers. Various factors degrade the localization accuracy of PSI point clouds in the geocoding process, which causes problems for interpretation of deformation results and also making it difficult for the point clouds to be compared with or integrated into data from other sensors. In this study, we employ the SAR imaging geodesy method to perform geodetic corrections on SAR timing observations and thus improve the positioning accuracy in the horizontal components. We further utilize geodetic stereo SAR to extract large number of highly precise ground control points (GCP) from SAR images, in order to compensate for the unknown height offset of the PSI point cloud. We demonstrate the applicability of the approach using TerraSAR-X high resolution spotlight images over the city of Berlin, Germany. The corrected results are compared with a reference LiDAR point cloud of Berlin, which confirms the improvement in the geocoding accuracy.

Regional Land Subsidence Analysis in Eastern Beijing Plain by InSAR Time Series and Wavelet Transforms

Land subsidence is the disaster phenomenon of environmental geology with regionally surface altitude lowering caused by the natural or man-made factors. Beijing, the capital city of China, has suffered from land subsidence since the 1950s, and extreme groundwater extraction has led to subsidence rates of more than 100 mm/year. In this study, we employ two SAR datasets acquired by Envisat and TerraSAR-X satellites to investigate the surface deformation in Beijing Plain from 2003 to 2013 based on the multi-temporal InSAR technique. Furthermore, we also use observation wells to provide in situ hydraulic head levels to perform the evolution of land subsidence and spatial-temporal changes of groundwater level. Then, we analyze the accumulated displacement and hydraulic head level time series using continuous wavelet transform to separate periodic signal components. Finally, cross wavelet transform (XWT) and wavelet transform coherence (WTC) are implemented to analyze the relationship between the accumulated displacement and hydraulic head level time series. The results show that the subsidence centers in the northern Beijing Plain is spatially consistent with the groundwater drop funnels. According to the analysis of well based results located in different areas, the long-term groundwater exploitation in the northern subsidence area has led to the continuous decline of the water level, resulting in the inelastic and permanent compaction, while for the monitoring wells located outside the subsidence area, the subsidence time series show obvious elastic deformation characteristics (seasonal characteristics) as the groundwater level changes. Moreover, according to the wavelet transformation, the land subsidence time series at monitoring well site lags several months behind the groundwater level change.

Advanced MT-InSAR Landslide Monitoring: Methods and Trends

MT-InSAR (Multi-temporal Interferometric Synthetic Aperture Radar) is a powerful remote sensing technique used to measure earth surface displacements and monitor their trend throughout the years over different times. It employs multiple time series of SAR images and extracts spatial height information over large scales of illuminated areas. It is a proficient technique to acquire all season day and night data with high accuracy and wide spatial coverage. Although conventional InSAR technique have vast successful applications but several limitations like decorrelation of phase, error in phase unwrapping and atmospheric artifacts hinders its use, which, in fact, have resulted in the development of more innovative multi-temporal InSAR (MTInSAR) techniques which has proved an enhancement in accuracy and consistency of extracted deformation time series. This paper provides a review of development of MTInSAR techniques, basic principles behind them, their strengths and limitations and a review of the applications of the advanced algorithms proposed in the literature and deformation measurement trends being followed. The paper accomplishes discussions on the main strengths, limitations, cross-comparison among approaches and the associated research trends.

Deformation monitoring of dam infrastructures via spaceborne MT-InSAR. The case of La Viñuela (Málaga, southern Spain)

Dams require continuous security and monitoring programs, integrated with visual inspection and testing in dam surveillance programs. New approaches for dam monitoring focus on multi-sensor integration, taking into account emerging technologies such as GNSS, optic fiber, TLS, InSAR techniques, GBInSAR, GPR, that can be used as complementary data in dam monitoring, eliciting causes of dam deformation that cannot be assessed with traditional techniques. This paper presents a Multi-temporal InSAR (MT-InSAR) monitoring of La Viñuela dam (Málaga, Spain), a 96 m height earth-fill dam built from 1982 to 1989. The presented MT-InSAR monitoring system comprises three C-band radar (~5,7 cm wavelength) datasets from the European satellites ERS-1/2 (1992-2000), Envisat (2003-2008), and Sentinel-1A/B (2014-2018). ERS-1/2 and Envisat datasets were processed using StaMPS. In the case of Sentinel-1A/B, two different algorithms were applied, SARPROZ and ISCE-SALSIT, allowing the comparison of the estimated LOS velocity pattern. The obtained results confirm that LaViñuela dam is deforming since its construction, as an earth-fill dam. Maximum deformation rates were measured in the initial period (1992-2000), being around -7 mm/yr (LOS direction) on the coronation of the dam. In the period covered by the Envisat dataset (2003-2008), the average deforming pattern was lower, of the order of -4 mm/yr. Sentinel-1A/B monitoring confirms that the deformation is still active in the period 2014-2018 in the central-upper part of the dam, with maximums of velocity reaching -6 mm/yr. SARPROZ and ISCE-SALSIT algorithms provide similar results. It was concluded that MT-InSAR techniques can support the development of new and more effective means of monitoring and analyzing the health of dams complementing actual dam surveillance systems.

DEFORMATION EFFECTS OF DAMS ON COASTAL REGIONS USING SENTINEL-1 IW TOPS TIME SERIES: THE WEST LESVOS, GREECE CASE

Abstract. Coastal zones are vulnerable to erosion and loss by level sea rise. Subsidence caused by the reduction of fluvial sediments in coastal zones found close to dams, is another important deformation factor. Quantification of the deformation rate of coastal region is essential for natural and anthropogenic activities. The study utilizes Interferometric SAR (Synthetic Aperture Radar) techniques and exploits the archive of Sentinel-1 TOPS data for the period 2014–2016. The freely available, wide ground coverage (250 × 170 km) and small temporal resolution Sentinel-1 TOPS datasets are promising for coastal applications. Persistent Scatterer Interferometry (PSI) methodologies are considered state-of-the-art remote sensing approaches for land deformation monitoring. The selected PSI method is the Small Baseline Subset (SBAS) multitemporal InSAR technique. The study area of this study is the coastal zone of west region of Lesvos Island, Greece. The main characteristic of the area is the reduction of the fluvial sediment supply from the coastal drainage basins due to construction of dams and the abstraction of riverine sediments. The study demonstrates the potentials of the SBAS method for measuring and mapping the dynamic changes in coastal topography in terms of subsidence rates and discusses its advantages and limitations. The results show that natural and rural environments appear to have diverse ground deformation patterns.

Deriving time-series three-dimensional displacements of mining areas from a single-geometry InSAR dataset

This paper presents a method for deriving time-series three-dimensional (3-D) displacements of mining areas from a single-geometry interferometric synthetic aperture radar (InSAR) dataset (hereafter referred to as the SGI-based method). This is mainly aimed at overcoming the limitation of the traditional multi-temporal InSAR techniques that require SAR data from at least three significantly different imaging geometries to fully retrieve time-series 3-D displacements of mining areas. The SGI-based method first generates the multi-temporal observations of the mining-induced vertical subsidence from the single-geometry InSAR data, using a previously developed method for retrieving 3-D mining-related displacements from a single InSAR pair (SIP). The weighted least-squares solutions of the time series of vertical subsidence are estimated from these generated multi-temporal observations of vertical subsidence. Finally, the time series of horizontal motions in the east and north directions are estimated using the proportional relationship between the horizontal motion and the subsidence gradient of the mining area, on the basis of the SGI-derived time series of vertical subsidence. Seven ascending ALOS PALSAR images from the Datong mining area of China were used to test the proposed SGI-based method. The results suggest that the SGI-based method is effective. The SGI-based method not only extends the SIP-based method to time-series 3-D displacement retrieval from a single-geometry InSAR dataset, but also limits the uncertainty propagation from InSAR-derived deformation to the estimated 3-D displacements.

New insights into earthquake precursors from InSAR

We measured ground displacements before and after the 2009 L’Aquila earthquake using multi-temporal InSAR techniques to identify seismic precursor signals. We estimated the ground deformation and its temporal evolution by exploiting a large dataset of SAR imagery that spans seventy-two months before and sixteen months after the mainshock. These satellite data show that up to 15 mm of subsidence occurred beginning three years before the mainshock. This deformation occurred within two Quaternary basins that are located close to the epicentral area and are filled with sediments hosting multi-layer aquifers. After the earthquake, the same basins experienced up to 12 mm of uplift over approximately nine months. Before the earthquake, the rocks at depth dilated, and fractures opened. Consequently, fluids migrated into the dilated volume, thereby lowering the groundwater table in the carbonate hydrostructures and in the hydrologically connected multi-layer aquifers within the basins. This process caused the elastic consolidation of the fine-grained sediments within the basins, resulting in the detected subsidence. After the earthquake, the fractures closed, and the deep fluids were squeezed out. The pre-seismic ground displacements were then recovered because the groundwater table rose and natural recharge of the shallow multi-layer aquifers occurred, which caused the observed uplift.

Estimation of north Tabriz fault parameters using neural networks and 3D tropospherically corrected surface displacement field

ABSTRACTIn this paper, parameters of north Tabriz fault are studied using 3D displacement field and artificial neural networks (ANNs). We provide the 3D surface displacement along the north Tabriz fault using an integration of tropospherically corrected InSAR, GPS and precise levelling data. To perform the InSAR analysis, we use the 17 ENVISAT radar acquisitions. The line of sight (LOS) displacement field was corrected using the ERA-Interim global meteorological reanalysis models. In order to calculate the 3D displacement, we use a Simultaneous and Integrated Strain Tensor Estimation from Geodetic and Satellite Deformation Measurements approach. ANNs used to estimate the parameters. 3D displacement field and ANN algorithm yields an average slip rate of 6.1 ± 0.01 mm/year with a locking depth of 13.4 ± 0.01 km. This rate is consistent with previous geodetic estimates based on recent global positioning system measurements and InSAR analysis. In addition, the length, width and dip angle of fault are about 101.2 ± 0.01 km, 25.06 ± 0.03 km and 63 ± 0.05 deg. This study demonstrates that interseismic displacement with a sub-centimetre rate can be successfully detected by integration of multi temporal InSAR techniques, GPS and precise leveling data and shows that ANN algorithm is suitable for estimating the parameters of north Tabriz fault.

Landslide monitoring for risk mitigation by using corner reflector and satellite SAR interferometry: The large landslide of Carlantino (Italy)

The use of satellite Synthetic Aperture Radar Interferometry (InSAR) for monitoring ground instability due to landslide events, although advantageous over large spatial scales, still poses challenges related to the recurrently complex kinematics of the phenomena or to the unfavorable settings of the examined areas with respect to steep topography and vegetated land cover.This paper presents results obtained by using Multi-temporal InSAR techniques with high resolution TerraSARX (TSX) data for monitoring the Carlantino landslide, located in the Daunian Subapennine (Apulia region, southern Italy) on a slope overlooking a water reservoir, and subjected to several investigations and consolidation works. The targets detected by using Persistent Scatterer Interferometry (PSI) correspond to urban structures or peri-urban walls and guard rails, while the landslide body is almost completely devoid of stable targets, due to the widespread vegetation and variable land cover. To allow stability monitoring, a network of six Corner Reflectors (CR) was designed and deployed over the landslide test site. The TSX images were analyzed by using both the PSI processing and a procedure, based on the double difference analysis of InSAR phase values on the CR pixels. Despite residual noise and the loss of 2 CRs due to vandalism, the processing allowed verifying the stability of the upper and central part of the landslide body, and relating indirectly the movements at the toe of the landslide to the water level fluctuations of the reservoir. Finally, this experiment suggests some recommendations and guidelines in planning CR deployment in complex landslide sites.

Potential loess landslide deformation monitoring using L-band SAR interferometry

Multi-temporal InSAR technique can implement continuous earth surface deformation detection with long time scale and wide geographical coverage. In this paper, we first employ the Small Baseline Subset method to survey potential landslides in Guide County, Qinghai Province, which is identified as a loess landslide prone area for geological and climate conditions. Two anomalous deformation regions are detected by L-band Phased Array and L-band Synthetic Aperture Radar stacks. Then, qualitative and quantitative evaluations of the measuring points are given for understanding the distribution regularity of deformation. Finally, preliminary correlation between the time-series deformation and triggering factors is analyzed to explore the driving mechanism for landslide movement. The results demonstrate that L-band SAR has high potential in landslide monitoring applications and can be used as the basis for landslide recognizing, precursory information extracting, and early warning.

POTENTIAL OF SENTINEL-1A FOR NATION-WIDE ROUTINE UPDATES OF ACTIVE LANDSLIDE MAPS

Slope deformation is one of the typical geohazards that causes an extensive economic damage in mountainous regions. As such, they are usually intensively monitored by means of modern expertise commonly by national geological or emergency services. Resulting landslide susceptibility maps, or landslide inventories, offer an overview of areas affected by previously activated landslides as well as slopes known to be unstable currently. Current slope instabilities easily transform into a landslide after various triggering factors, such as an intensive rainfall or a melting snow cover. In these inventories, the majority of the existing landslide-affected slopes are marked as either stable or active, after a continuous investigative work of the experts in geology. In this paper we demonstrate the applicability of Sentinel-1A satellite SAR interferometry (InSAR) to assist by identifying slope movement activity and use the information to update national landslide inventories. This can be done reliably in cases of semi-arid regions or low vegetated slopes. We perform several analyses based on multitemporal InSAR techniques of Sentinel-1A data over selected areas prone to landslides.

POTENTIAL OF SENTINEL-1A FOR NATION-WIDE ROUTINE UPDATES OF ACTIVE LANDSLIDE MAPS

Abstract. Slope deformation is one of the typical geohazards that causes an extensive economic damage in mountainous regions. As such, they are usually intensively monitored by means of modern expertise commonly by national geological or emergency services. Resulting landslide susceptibility maps, or landslide inventories, offer an overview of areas affected by previously activated landslides as well as slopes known to be unstable currently. Current slope instabilities easily transform into a landslide after various triggering factors, such as an intensive rainfall or a melting snow cover. In these inventories, the majority of the existing landslide-affected slopes are marked as either stable or active, after a continuous investigative work of the experts in geology. In this paper we demonstrate the applicability of Sentinel-1A satellite SAR interferometry (InSAR) to assist by identifying slope movement activity and use the information to update national landslide inventories. This can be done reliably in cases of semi-arid regions or low vegetated slopes. We perform several analyses based on multitemporal InSAR techniques of Sentinel-1A data over selected areas prone to landslides.

Reconstructing the Vertical Component of Ground Deformation from Ascending ALOS and Descending ENVISAT Datasets—A Case Study in the Cangzhou Area of China

. Due to the regular revisit periods of SAR platforms and the decorrelation of SAR images, the estimation of ground deformation retrieved from a particular SAR dataset may be of low resolution in both spatial and temporal dimensions. To enhance the spatial and temporal sampling rates in ground deformation estimation, a multiplatform SAR dataset combination strategy is proposed, based on the Multi-Temporal InSAR (MTInSAR) technique and the Same Name target point Pairs (SNPs) combination approach. The combination strategy has been tested and applied in the Cangzhou area, which has suffered from ground subsidence due mainly to groundwater extraction. The derived results show that the deformation monitoring sampling rates can be improved in the space and time dimensions when compared to the results obtained from a single-platform SAR dataset, which makes the multiplatform SAR dataset combination strategy useful for uneven (spatially variable) and nonlinear (temporally variable) deformation detection. Moreover, the results derived from the combination strategy tend to be more reliable and have fewer noise points.

Post-Eruptive Inflation of Okmok Volcano, Alaska, from InSAR, 2008–2014

Okmok, a ~10-km wide caldera that occupies most of the northeastern end of Umnak Island, is one of the most active volcanoes in the Aleutian arc. The most recent eruption at Okmok during July–August 2008 was by far its largest and most explosive since at least the early 19th century. We investigate post-eruptive magma supply and storage at the volcano during 2008–2014 by analyzing all available synthetic aperture radar (SAR) images of Okmok acquired during that time period using the multi-temporal InSAR technique. Data from the C-band Envisat and X-band TerraSAR-X satellites indicate that Okmok started inflating very soon after the end of 2008 eruption at a time-variable rate of 48–130 mm/y, consistent with GPS measurements. The “model-assisted” phase unwrapping method is applied to improve the phase unwrapping operation for long temporal baseline pairs. The InSAR time-series is used as input for deformation source modeling, which suggests magma accumulating at variable rates in a shallow storage zone at ~3.9 km below sea level beneath the summit caldera, consistent with previous studies. The modeled volume accumulation in the six years following the 2008 eruption is ~75% of the 1997 eruption volume and ~25% of the 2008 eruption volume.

InSAR Time Series Analysis of Natural and Anthropogenic Coastal Plain Subsidence: The Case of Sibari (Southern Italy)

We applied the Small Baseline Subset multi-temporal InSAR technique (SBAS) to two SAR datasets acquired from 2003 up to 2013 by Envisat (ESA, European Space Agency) and COSMO-SkyMed (ASI, Italian Space Agency) satellites to investigate spatial and temporal patterns of land subsidence in the Sibari Plain (Southern Italy). Subsidence processes (up to ~20 mm/yr) were investigated comparing geological, hydrogeological, and land use information with interferometric results. We suppose a correlation between subsidence and thickness of the Plio-Quaternary succession suggesting an active role of the isostatic compensation. Furthermore, the active back thrusting in the Corigliano Gulf could trigger a flexural subsidence mechanism even if fault activity and earthquakes do not seem play a role in the present subsidence. In this context, the compaction of Holocene deposits contributes to ground deformation. Despite the rapid urbanization of the area in the last 50 years, we do not consider the intensive groundwater pumping and related water table drop as the main triggering cause of subsidence phenomena, in disagreement with some previous publications. Our interpretation for the deformation fields related to natural and anthropogenic factors would be a comprehensive and exhaustive justification to the complexity of subsidence processes in the Sibari Plain.

Mapping ground deformation over Houston–Galveston, Texas using multi-temporal InSAR

Abstract Houston–Galveston (HG) region in Texas has been subsiding due to the combined effects of groundwater withdrawal, hydrocarbon extraction, salt dome movement, and faulting. This human- and partially nature-induced ground deformation has gradually threatened the stability of urban infrastructure and caused the loss of wetland habitat along the Gulf of Mexico. Interferometric synthetic aperture radar (InSAR) techniques can measure ground motions in high spatial resolution over large coverage. The purpose of this study is to map the spatial and temporal variations in surface deformation around the HG region using a Multi-Temporal InSAR (MTI) technique and to assess the role of fluid withdrawal (groundwater withdrawal and hydrocarbon extraction), salt tectonics, and fault activity in land surface deformation. MTI-derived land surface deformation measurements are then compared to GPS and extensometer observations, geologic and hydrologic data, and information about hydrocarbon extraction to address the causes of the observed deformation. The MTI measurements based on ERS-1/2 datasets have mapped regional subsidence up to 53 mm/yr in the northwestern HG as well as a slight uplift at 20 mm/yr in the southeastern HG from 1993 to 2000. InSAR measurements obtained from Envisat and ALOS data reveal subsidence rate of up to 30 mm/yr over the northwestern HG between 2004 and 2011. Our results indicate that the pattern of ground deformation was nearly concentric around locations of intense groundwater withdrawal and the spatial extent of the subsiding area has been shrinking and migrating toward the northeast after 2000. We have resolved localized ground subsidence cones over hydrocarbon exploration fields, which were likely caused by reservoir compaction. We have differentiated ground surface deformation over salt domes, which was due to ongoing differential movement of individual salt spines. We have identified 5–40 mm/yr differential subsidence across a number of faults in the region. These faults functioned as water barriers disrupting the integrity of ground water flow and aggravating localized surface displacements.

Study of the ground subsidences in the Sibari Plain (Southern Italy) detected by InSAR data analysis

We investigated surface ground deformations in the Sibari Plain (SP - Calabria, Southern Italy) by means of Small Baseline Subset multi-temporal InSAR technique (SBAS), applied to two SAR datasets acquired from 2003 up to 2013 by Envisat (ESA, European Space Agency) and COSMO-SkyMed (ASI, Italian Space Agency) satellites. The retrieved InSAR data show the existence of ground subsidence phenomena up to ~ -20 mm/yr. Our investigation is based on integration between InSAR data and geological, well-logs, land use and hydrogeological information. The results show a direct correlation among subsidence, the thickness of Plio-Pleistocene succession and thickness and lithology of the late Holocene deposits. We identified the fast urbanization of the coastal area during the last ~50 yr and the water table drop as incremental factors of subsidence phenomena. The second factor, due to intensive use of ground water for agriculture, is not the triggering cause of subsidence processes on contrary to the assumption of some previous publications. No evidence of tectonic contribution in the ground deformation pattern is observed.

Investigation of Slow-Moving Landslides from ALOS/PALSAR Images with TCPInSAR: A Case Study of Oso, USA

Monitoring slope instability is of great significance for understanding landslide kinematics and, therefore, reducing the related geological hazards. In recent years, interferometric synthetic aperture radar (InSAR) has been widely applied to this end, especially thanks to the prompt evolution of multi-temporal InSAR (MTInSAR) algorithms. In this paper, temporarily-coherent point InSAR (TCPInSAR), a recently-developed MTInSAR technique, is employed to investigate the slow-moving landslides in Oso, U.S., with 13 ALOS/PALSAR images. Compared to other MTInSAR techniques, TCPInSAR can work well with a small amount of data and is immune to unwrapping errors. Furthermore, the severe orbital ramps emanated from the inaccurate determination of the ALOS satellite’s state vector can be jointly estimated by TCPInSAR, resulting in an exhaustive separation between the orbital errors and displacement signals. The TCPInSAR-derived deformation map indicates that the riverside slopes adjacent to the North Fork of the Stillaguamish River, where the 2014 mudslide occurred, were active during 2007 and 2011. Besides, Coal Mountain has been found to be experiencing slow-moving landslides with clear boundaries and considerable magnitudes. The Deer Creek River is also threatened by a potential landslide dam due to the creeps detected in a nearby slope. The slope instability information revealed in this study is helpful to deal with the landslide hazards in Oso.

Investigation of Slow-Moving Landslides from ALOS/PALSAR Images with TCPInSAR: A Case Study of Oso, USA

Monitoring slope instability is of great significance for understanding landslide kinematics and, therefore, reducing the related geological hazards. In recent years, interferometric synthetic aperture radar (InSAR) has been widely applied to this end, especially thanks to the prompt evolution of multi-temporal InSAR (MTInSAR) algorithms. In this paper, temporarily-coherent point InSAR (TCPInSAR), a recently-developed MTInSAR technique, is employed to investigate the slow-moving landslides in Oso, U.S., with 13 ALOS/PALSAR images. Compared to other MTInSAR techniques, TCPInSAR can work well with a small amount of data and is immune to unwrapping errors. Furthermore, the severe orbital ramps emanated from the inaccurate determination of the ALOS satellite’s state vector can be jointly estimated by TCPInSAR, resulting in an exhaustive separation between the orbital errors and displacement signals. The TCPInSAR-derived deformation map indicates that the riverside slopes adjacent to the North Fork of the Stillaguamish River, where the 2014 mudslide occurred, were active during 2007 and 2011. Besides, Coal Mountain has been found to be experiencing slow-moving landslides with clear boundaries and considerable magnitudes. The Deer Creek River is also threatened by a potential landslide dam due to the creeps detected in a nearby slope. The slope instability information revealed in this study is helpful to deal with the landslide hazards in Oso.