Comparison Between PS and SBAS InSAR Techniques in Monitoring Shallow Landslides

Chen, Xue; Tessari, Giulia; Fabris, Massimo; Achilli, Vladimiro; Floris, Mario

doi:10.1007/978-3-030-60311-3_17

Cited by 12 publications

(7 citation statements)

References 13 publications

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“…In addition, this technique provides low-noise time series of displacements which allow to estimate the temporal evolution of the movements and explore the triggering factors. For these reasons, despite SBAS technique is time-consuming from the computational viewpoint and for the operator intervention, it should be preferred to PS-InSAR based techniques [14] which allow to estimate deformations affecting limited areas [53]. PS techniques can be effectively used for analyzing highly urbanized unstable slopes, as shown in previous studies [21][22][23][24].…”

Section: Discussionmentioning

confidence: 99%

Combining Sentinel-1 Interferometry and Ground-Based Geomatics Techniques for Monitoring Buildings Affected by Mass Movements

et al. 2021

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Mass movements represent a serious threat to the stability of human structures and infrastructures, and cause loss of lives and severe damages to human properties every year worldwide. Built structures located on potentially unstable slopes are susceptible to deformations due to the displacement of the ground that at worst can lead to total destruction. Synthetic aperture radar (SAR) data acquired by Sentinel-1 satellites and processed by multi-temporal interferometric SAR (MT-InSAR) techniques can measure centimeter to millimeter-level displacement with weekly to monthly updates, characterizing long-term large-scale behavior of the buildings and slopes. However, the spatial resolution and short wavelength weaken the performance of Sentinel-1 in recognizing features (i.e., single buildings) inside image pixels and maintaining the coherence in mountainous vegetated areas. We have proposed and applied a methodology that combines Sentinel-1 interferometry with ground-based geomatics techniques, i.e., global navigation satellite system (GNSS), terrestrial laser scanning (TLS) and terrestrial structure from motion photogrammetry (SfM), for fully assessing building deformations on a slope located in the north-eastern Italian pre-Alps. GNSS allows verifying the ground deformation estimated by MT-InSAR and provides a reference system for the TLS and SfM measurements, while TLS and SfM allow the behavior of buildings located in the investigated slope to be monitored in great detail. The obtained results show that damaged buildings are located in the most unstable sectors of the slope, but there is no direct relationship between the rate of ground deformation of these sectors and the temporal evolution of damages to a single building, indicating that mass movements cause the displacement of blocks of buildings and each of them reacts differently according to its structural properties. This work shows the capability of MT-InSAR, GNSS, TLS and SfM in monitoring both buildings and geological processes that affect their stability, which plays a key role in geohazard analysis and assessment.

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Section: Discussionmentioning

confidence: 99%

Combining Sentinel-1 Interferometry and Ground-Based Geomatics Techniques for Monitoring Buildings Affected by Mass Movements

et al. 2021

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“…To conduct this, the use of multi-temporal interferometry SAR techniques (MTInSAR) [29][30][31][32] can be advantageous for mapping landslide phenomena as well as for determining their state of activity in the long run [33,34]. Data acquired by space-borne SAR sensors and processed using differential SAR interferometry (DInSAR) techniques are now important technological tools in landslide investigations and studies [35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

Landslide Mapping in Calitri (Southern Italy) Using New Multi-Temporal InSAR Algorithms Based on Permanent and Distributed Scatterers

Famiglietti,

Miele,

Defilippi

et al. 2024

Remote Sensing

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Landslides play a significant role in the morpho-evolutional processes of slopes, affecting them globally under various geological conditions. Often unnoticed due to low velocities, they cause diffuse damage and loss of economic resources to the infrastructure or villages built on them. Recognizing and mapping mass movements is crucial for mitigating economic and social impacts. Conventional monitoring techniques prove challenging for large areas, necessitating resource-intensive ground-based networks. Leveraging abundant synthetic aperture radar (SAR) sensors, satellite techniques offer cost-effective solutions. Among the various methods based on SAR products for detecting landslides, multi-temporal differential interferometry SAR techniques (MTInSAR) stand out for their precise measurement capabilities and spatiotemporal evolution analysis. They have been widely used in several works in the last decades. Using information from the official Italian landslide database (IFFI), this study employs Sentinel-1 imagery and two new processing chains, E-PS and E-SBAS algorithms, to detect deformation areas on the slopes of Calitri, a small town in Southern Italy; these algorithms assess the cumulated displacements and their state of activity. Taking into account the non-linear trends of the scatterers, these innovative algorithms have helped to identify a dozen clusters of points that correspond well with IFFI polygons.

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“…Zhang et al proposed an InSAR analysis method for identifying and extracting the temporary coherence point (TCP) between two SAR values [20]. Chen aimed to compare the two commonly used multi-temporal InSAR techniques, that is, PS-InSAR and SBAS-InSAR, in monitoring shallow landslides [21]. Dong validated the DS-InSAR algorithm to monitor the Xishan Landslide in the western mountainous region of Sichuan province with a qualitative and quantitative simulation analysis [22].…”

Section: Introductionmentioning

confidence: 99%

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

Zheng

Xie

He³

et al. 2022

Remote Sensing

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In recent years, the number of geological disasters in Sichuan Province has significantly increased due to the influence of earthquakes and extreme climate, as well as the disturbance to the geological environment by human activities. Thus, geological disaster monitoring is particularly important, which can provide some scientific basis for disaster prevention and reduction. In this paper, the interferometric synthetic aperture radar (InSAR) technology was introduced to monitor potential geological hazards, taking parts of Dujiangyan City, Wenchuan County, and Mao County in Sichuan Province, China as examples. Firstly, the data such as Sentinel-1A Terrain Observation with Progressive Scans (TOPS) Synthetic Aperture Radar (SAR) images and Precision Orbit Determination (POD) precise orbit ephemerides from 2018 to 2020, high-resolution optical satellite images and Digital Elevation Model (DEM) were collected. Secondly, the Differential InSAR (D-InSAR), Persistent Scatterer InSAR (PS-InSAR), Small Baseline Subset InSAR (SBAS-InSAR), Offset-Tracking, and Distributed Scatterer InSAR (DS-InSAR) algorithms were used to invert the surface deformation of the study area. Thirdly, according to the deformation results obtained by experiments, we used GF-1 and GF-2 optical images as a reference and combine the experimental results of InSAR algorithms to delineate the areas affected by geological disasters. A total of 49 geological disaster areas were obtained, mainly including landslides, collapses, and debris flow. Through field verification, the overall accuracy rate of InSAR deformation monitoring achieved 69.23%, and the accuracy rate of new potential hazards monitoring reached 63.64%. Among all InSAR methods, the DS-InSAR method outperformed and monitored the geological disaster areas well. Finally, the study area was divided into three elevation intervals and the applicability of different InSAR algorithms in different elevation intervals was discussed.

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Comparison Between PS and SBAS InSAR Techniques in Monitoring Shallow Landslides

Cited by 12 publications

References 13 publications

Combining Sentinel-1 Interferometry and Ground-Based Geomatics Techniques for Monitoring Buildings Affected by Mass Movements

Combining Sentinel-1 Interferometry and Ground-Based Geomatics Techniques for Monitoring Buildings Affected by Mass Movements

Landslide Mapping in Calitri (Southern Italy) Using New Multi-Temporal InSAR Algorithms Based on Permanent and Distributed Scatterers

Monitoring Potential Geological Hazards with Different InSAR Algorithms: The Case of Western Sichuan

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