Effect of Earthquake Intensity to Land Deformation Observed from Space

Razi, Pakhrur; Sumantyo, Josaphat Tetuko Sri; Nishi, Katsunoshin; Widodo, Joko; Munir, Achmad; Febriany, Fajar

doi:10.1109/piers-spring46901.2019.9017495

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…Razi et al 37 employed PSInSAR method for extracting earthquake-induced land deformation in Chiba prefecture utilizing time-series ALOS-2 PALSAR-2 SAR datasets. Later, Kumar et al 38 investigated urban damage and terrain deformation caused by the 2015 earthquake that struck Kathmandu, Nepal used PSInSAR with Sentinel-1 SAR datasets.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

Awasthi,

Jain,

Sahoo

et al. 2024

Sci Rep

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The Himalayas are highly susceptible to various natural disasters, such as the tectonically induced land deformation, earthquakes, landslides, and extreme climatic events. Recently, the Joshimath town witnessed a significantly large land subsidence activity. The phenomenon resulted in the development of large cracks in roads and in over 868 civil structures, posing a significant risk to inhabitants and infrastructure of the area. This study uses a time-series synthetic aperture radar (SAR) interferometry-based PSInSAR approach to monitor land deformation utilizing multi-temporal Sentinel-1 datasets. The line of sight (LOS) land deformation velocity for the Joshimath region, calculated for the year 2022–2023 using a PSInSAR-based approach, varies from − 89.326 to + 94.46 mm/year. The + ve sign indicates the LOS velocity/displacement away from the SAR sensor, whereas − ve sign signifies the earth's movement towards the SAR sensor in the direction of LOS. In addition, the study investigates feature tracking land displacement analysis using multi-temporal high-resolution Planet datasets. The result of this analysis is consistent with the PSInSAR results. The study also estimated the land deformation for the periods 2016–2017, 2018–2019, and 2020–2021 separately. Our results show that the Joshimath region experienced the highest land deformation during the year 2022–2023. During this period, the maximum land subsidence was observed in the north-western part of the town. The maximum LOS land deformation velocity + 60.45 mm/year to + 94.46 mm/year (2022–2023), occurred around Singhdwar, whereas the north and central region of the Joshimath town experienced moderate to high subsidence of the order of + 10.45 mm/year to + 60.45 mm/year (2022–2023), whereas the south-west part experienced an expansion of the order of 84.65 mm/year to − 13.13 mm/year (2022–2023). Towards the south-east, the town experienced rapid land subsidence, − 13.13 mm/year to − 5 mm/year (2022–2023). The study analyzes the causative factors of the observed land deformation in the region. Furthermore, this work assesses the ground conditions of the Joshimath region using UAV datasets acquired in the most critically affected areas such as Singhdhaar, Hotel Mountain View, Malhari Hotel, and Manoharbagh. Finally, the study provides recommendations and future prospects for the development policies that need to be adopted in the critical Himalayan regions susceptible to land deformation. The study suggests that land deformation in the region is primarily attributed to uncontrolled anthropogenic activities, infrastructural development, along with inadequate drainage systems.

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Section: Introductionmentioning

confidence: 99%

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

Awasthi,

Jain,

Sahoo

et al. 2024

Sci Rep

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“…The SLC data format consists of phase and amplitude information that has focused and georeferenced using altitude and orbit data from the satellite [17], [5]. Also, the data in zero Doppler slant-range geometry [18]. From three-part of beam swath mode of Interferometric Wide (IW) of Sentinel-1, IW1 and IW3 were selected for the study area in both ascending and descending orbits, respectively.…”

Section: A Materialsmentioning

confidence: 99%

Potential Landslide Detection in Kelok Sembilan Flyover Using SAR Interferometry

Razi

Sumantyo

Perissin

et al. 2021

Int. J. Adv. Sci. Eng. Inf. Technol.

Self Cite

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Kelok Sembilan flyover is located in West Sumatra-Riau province connection, Indonesia. Landslide occurs along with the connection every year. However, detecting and obtaining scientific information about the potential landslide zone in the area is difficult because it is mountainous, and there is no disaster equipment monitoring installed on it. Here, we identify the area that potential landslide using Satellite Radar SAR Synthetic Aperture Radar) technology with high accuracy until millimeter unit. Also, we showed how to observe the potential landslide with a low penetrate radar signal (C-band) and shifted polarization due to the topography in the vegetation area. The observation data is extracting from satellite Sentinel- 1A/B provided by the European Space Agency (ESA). The satellite is C-band frequency with 5.5 cm wavelength and 5 x 20-meter range-azimuth resolution. The acquisition time of SAR data is starting from October 2014 to August 2018, which is supported by 119 images. Processing the SAR data is using the Quasi-Persistent Scatterer technique to improve the number of scatterers in a non-urban area. Both ascending and descending orbit of the satellite with both VV and VH polarization were selected to confirm potential landslide detection consistency. The result of processing was validated with GPS geodetic by DGPS network configuration. Based on the QPS processing, five areas with significant land movement have been detected; one of them is collapse after ten days since the last data observation. The land movement range in the area is approximately more than 500 millimeters in four years.

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“…In another study, Zhou et al [48] worked on detecting and illustrating the spatiotemporal changes and subsidence in the Beijing Plain by applying PsInSAR based approach utilizing multi-source SAR datasets. Razi et al [49] observed land deformation resulting from the high-intensity earthquakes in Chiba prefecture using time-series ALOS-2 PALSAR-2 SAR datasets applying the PsInSAR approach. Further, a study was conducted by Liu et al [50] to retrieve temporal and spatial variation of ground settlement related to land reclamation in the Xiamen New Airport in China using C-band Sentinel-1 satellite datasets.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Land Deformation and the Associated Causes along a Rapidly Developing Himalayan Foothill Region Using Multi-Temporal Sentinel-1 SAR Datasets

Awasthi

Varade

Bhattacharjee

et al. 2022

Land

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Land deformation has become a crucial threat in recent decades, caused by various natural and anthropogenic activities in the environment. The seismic land dynamics, landslides activities, heavy rainfall resulting in flood events, and subsurface aquifer shrinkage due to the excessive extraction of groundwater are among the major reasons for land deformation, which may cause serious damage to the overall land surface, civil infrastructure, underground tunnels, and pipelines, etc. This study focuses on preparing a framework for estimating land deformation and analyzing the causes associated with land deformation. A time-series SAR Interferometry-based technique called PsInSAR was used to measure land deformation, using Sentinel-1 datasets from 2015 to 2021 by estimating land deformation velocities for this region. The obtained PSInSAR deformation velocity results ranged between −4 mm to +2 mm per year. Further, land use land cover (LULC) changes in the area were analyzed as an essential indicator and probable cause of land deformation. LULC products were first generated using Landsat-8 images for two time periods (2015, 2021), which were then evaluated in accordance with the deformation analysis. The results indicated an increase in the built-up areas and agricultural cover in the region at the cost of shrinkage in the vegetated lands, which are highly correlated with the land subsidence in the region, probably due to the over-extraction of groundwater. Further, the outer region of the study area consisting of undulating terrain and steep slopes also coincides with the estimated high subsidence zones, which could be related to higher instances of landslides identified in those areas from various primary and secondary information collected. One of the causes of landslides and soil erosion in the region is identified to be high-level precipitation events that loosen the surface soil that flows through the steep slopes. Furthermore, the study region lying in a high seismic zone with characteristic unstable slopes are more susceptible to land deformation due to high seismic activities. The approach developed in the study could be an useful tool for constant monitoring and estimation of land deformation and analysis of the associated causes which can be easily applied to any other region.

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Effect of Earthquake Intensity to Land Deformation Observed from Space

Cited by 7 publications

References 8 publications

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

Potential Landslide Detection in Kelok Sembilan Flyover Using SAR Interferometry

Assessment of Land Deformation and the Associated Causes along a Rapidly Developing Himalayan Foothill Region Using Multi-Temporal Sentinel-1 SAR Datasets

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