Comparative study on vertical deformation based on GPS and leveling data

Qin, Shanlan; Wang, Wenping; Song, Shangwu

doi:10.1016/j.geog.2017.07.005

Cited by 14 publications

(5 citation statements)

References 7 publications

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“…GNSS horizontal displacement rates are more reliably quantified and interpret compared to vertical estimates. The vertical displacement values are generally corrected with the help of precise levelling operations (Ching et al, 2011;Qin et al, 2017).…”

Section: Landslide Detection and Analysismentioning

confidence: 99%

“…For GNSS, such surveys can be time intensive and infeasible. Such areas can be surveyed from a distance of 10-200 m with TLS, resulting in dense point clouds (millions of points/m 2 ) and high resolution DEMs, which can be used for measuring surface movement and volume change (Denora et al, 2011;Barbarella and Fiani, 2013;Syahmi et al, 2011;Wan Aziz et al, 2012;Wang et al, 2017). However, in case of large areas, TLS survey has issues related to occlusion and co-registration errors.…”

Section: Landslide Detection and Analysismentioning

confidence: 99%

See 1 more Smart Citation

Multi-Sensor Geodetic Approach for Landslide Detection and Monitoring

Tiwari

Narayan

Meghanadh

et al. 2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The lesser Himalayan region is mostly affected by landslide events occurring due to rainfall, steep slopes and presence of tectonic activity beneath, causing loss of life and property. Some critical zones in the region have encountered recurring landslides over the past and need careful investigation for better planning and rescue operations. This research work presents a geodetic framework comprising multiple sensors to monitor the Sirobagarh landslide in Uttarakhand, India, which is affected by recurring landslides. Three field visits were made to this site for geodetic data collection using Terrestrial Laser Scanner (TLS), Global Navigation Satellite System (GNSS) and Robotic Total Station (RTS). Co-registration and vegetation removal of the TLS scans corresponding to the three visits resulted in generation of three Digital Elevation Models (DEM), which were differenced to estimate temporal movement of the landslide scarp. DEM differences indicate subsidence of the landslide scarp with vertical displacement values ranging from &minus;0.05 to &minus;5.0m. Rainfall induced debris flow is one of the prominent reason for large displacement magnitude (&sim;5m) in the upper landslide scarp. Horizontal displacement estimates obtained by geodetic network analysis of six GNSS stations installed on the study site show movement towards the Alaknanda river. The maximum horizontal and vertical displacement values for the GNSS stations were 0.1305m and &minus;2.1315m respectively. Similar pattern is observed by displacement measurements of RTS target reflectors installed on a retaining wall constructed to arrest the debris flow approaorching the National Highway. The displacement estimates obtained from the sensors applied in this study indicate subsidence of the landslide scarp and surroundings. More time series observations can provide better understanding of the overall deformation process.

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Section: Landslide Detection and Analysismentioning

confidence: 99%

Section: Landslide Detection and Analysismentioning

confidence: 99%

Multi-Sensor Geodetic Approach for Landslide Detection and Monitoring

Tiwari

Narayan

Meghanadh

et al. 2018

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Various studies have been conducted worldwide which analyzed the relationship between traditional leveling and obtaining heights using satellite positioning techniques (Li & Goldstein, 1990;Zebker et al, 1994;Dawod et al, 2010;Poitevin et al, 2019). Such is the case of the comparison of the vertical deformations of the profile of the geological fault in Shanyin, Shanxi province in China, based on GNSS observations and precise leveling for multiple periods of time (Qin et al, 2018). The results of the study indicated that the speed in vertical deformation determined with sequential GNSS surveys was 20 mm / year.…”

Section: Introductionmentioning

confidence: 98%

Validation of the GPS leveling method through the gradient analysis of the geoidal wave. Case study of Ecuador.

Enríquez¹,

Leiva²,

Cárdenas³

et al. 2021

RGV

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We validated the GPS leveling as an alternative to the traditional geometric leveling method. Validation compares the geometric slopes derived from the GNSS positioning technique, heights resulting from geometric leveling campaigns and geoid undulations extracted from the Global Geopotential Model EGM08. This analysis was performed in the Ecuadorian mainland, where we identified areas in which the gradient of the geoidal undulation is less pronounced. The spatialization of the gradient or variation-based methods allowed to analyze the performance of the GPS leveling method, under the hypothesis that less variability in geoid undulation implies less discrepancies in the GPS unevenness. GNSS observations were determined on the leveling plates belonging to the Basic Vertical Control Network. The results of the study are given based on the relative error resulting from the comparison of the traditional differential leveling method with the corresponding values obtained from the GNSS positioning, considering different distances for the spread of unevenness.

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“…The traditional precision leveling and GNSS were separately used to study the vertical crustal deformation [31][32][33], but their advantages cannot be fully explored. As shown in Figure 1, the leveling route in SYR was generally arranged along the main structural belt, resulting in some observation gaps in the middle part of the secondary blocks.…”

Section: Introductionmentioning

confidence: 99%

The Current Crustal Vertical Deformation Features of the Sichuan–Yunnan Region Constrained by Fusing the Leveling Data with the GNSS Data

Yong

Zheng

et al. 2022

Remote Sensing

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This study uses the least squares collocation method to fuse the leveling vertical deformation velocity in the Sichuan–Yunnan region with the GNSS observations of this region from 320 stations in the China Crustal Movement Observation Network (CMONOC) and the China Continental Tectonic Environment Monitoring Network (CMTEMN) from 1999 to 2017. Such fusion is to improve the accuracy of the vertical deformation rates in large spatial scales. The fused vertical deformation results show that: (1) the fused deformation field has a uniform spatial distribution, and shows detailed change characteristics of key regions; (2) the current vertical crustal motion in this region is featured by the contemporaneous occurrence of crustal compression, shortening and uplift and basin extensional subsidence; (3) most areas in this region experience uplifts, as the lateral push of the Qinghai–Tibet Plateau was blocked by the Sichuan Basin. The areas on the northwest side of the Longmenshan fault and the Lijiang-Xiaojinhe fault are dominated by uplifts, with the velocity of 1.5 mm/a–5.5 mm/a, and the region on the southeast side has slight uplifts, with the velocity of 1.0 mm/a–1.5 mm/a; (4) many areas have high gradient vertical deformation, especially the region close to the Wenshan fault and on the two sides of the Yarlung Zangbo fault that has the value of 3.0–4.0 × 10−8/a, deserving further attention to be paid to the long-term earthquake hazards.

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Comparative study on vertical deformation based on GPS and leveling data

Cited by 14 publications

References 7 publications

Multi-Sensor Geodetic Approach for Landslide Detection and Monitoring

Multi-Sensor Geodetic Approach for Landslide Detection and Monitoring

Validation of the GPS leveling method through the gradient analysis of the geoidal wave. Case study of Ecuador.

The Current Crustal Vertical Deformation Features of the Sichuan–Yunnan Region Constrained by Fusing the Leveling Data with the GNSS Data

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