Land Subsidence Monitoring in Nanning Based on Sentinel-1A data and SBAS-InSAR

Author(s):  
Chao Ren ◽  
Zilin Zhu ◽  
Lv Zhou ◽  
Xianjian Shi ◽  
Xianguang Li ◽  
...  
Author(s):  
G. Huang ◽  
H. Chen ◽  
X. Li ◽  
G. Cheng ◽  
Z. Yu ◽  
...  

<p><strong>Abstract.</strong> The Sentinel-1 data is currently the latest free SAR data and is well suited for land subsidence monitoring based on InSAR technology due to its 6-day revisit cycle. In this paper, the urban area and surrounding areas of Handan City are used as research areas, and 29 scences of S1A data (December 2017 &amp;ndash; December 2018) was used for time series SBAS processing. The results shows that the surface cumulative deformation ranged from -42 to 30&amp;thinsp;mm in most regions of Handan City. The maximum settlement is 69&amp;thinsp;mm, which is near the Hankuang Group Julong Company. The areas where the settlement is obvious include Wu'an City, Daishan Village, Dashe Town, Zhangxibao Town, Baijia Street, Dongxingtai Village, Gaonan Village and Hankuang Group Julong Company. Slightly elevated in the southeast of Handan City.</p>


Author(s):  
M. L. Gao ◽  
H. L. Gong ◽  
B. B. Chen ◽  
C. F. Zhou ◽  
K. S. Liu ◽  
...  

Abstract. InSAR time series analysis is widely used for detection and monitoring of slow surface deformation. In this paper, 15 TerraSAR-X radar images acquired in stripmap mode between 2012 and 2013 are processed for land subsidence monitoring with the Small Baseline Subset (SBAS) approach in Beijing Plain in China. Mapping results produced by SBAS show that the subsidence rates in the area of Beijing Plain range from −97.5 (subsidence) and to +23.8 mm yr−1 (uplift), relative to a presumably stable benchmark. The mapping result also reveals that there are the five subsidence centers formed by surface deformation spreading north to south east of the downtown. An uneven subsidence patten was detected near the Beijing Capital International Airpor, which may be related to loading of buildings and the aircraft.


Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4751 ◽  
Author(s):  
Sadra Karimzadeh ◽  
Masashi Matsuoka

In this study, we monitor pavement and land subsidence in Tabriz city in NW Iran using X-band synthetic aperture radar (SAR) sensor of Cosmo-SkyMed (CSK) satellites (2017–2018). Fifteen CSK images with a revisit interval of ~30 days have been used. Because of traffic jams, usually cars on streets do not allow pure backscattering measurements of pavements. Thus, the major paved areas (e.g., streets, etc.) of the city are extracted from a minimum-based stacking model of high resolution (HR) SAR images. The technique can be used profitably to reduce the negative impacts of the presence of traffic jams and estimate the possible quality of pavement in the HR SAR images in which the results can be compared by in-situ road roughness measurements. In addition, a time series small baseline subset (SBAS) interferometric SAR (InSAR) analysis is applied for the acquired HR CSK images. The SBAS InSAR results show land subsidence in some parts of the city. The mean rate of line-of-sight (LOS) subsidence is 20 mm/year in district two of the city, which was confirmed by field surveying and mean vertical velocity of Sentinel-1 dataset. The SBAS InSAR results also show that 1.4 km2 of buildings and 65 km of pavement are at an immediate risk of land subsidence.


2018 ◽  
Vol 10 (1) ◽  
pp. 678-687 ◽  
Author(s):  
Deliang Chen ◽  
Yanyan Lu ◽  
Dongzhen Jia

Abstract The Urban Agglomeration in Yangtze River Delta is one of the most important economic and industrial regions in China. The City of Changzhou is one of the most important industrial citys in Yangtze River Delta Urban Agglomeration. Activities here include groundwater exploration. Groundwater overexploitation has contributed to the major land deformation in this city. The severity and magnitude of land deformation over time were investigated in Changzhou City. A Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology, provides a useful tool in measuring urban land deformation. In this study, a time series of COSMO-SkyMed and Sentinel-1A SAR images covering Changzhou City were acquired. SBAS-InSAR imaging technique was used to survey the extent and severity of land deformation associated with the exploitation of groundwater in Changzhou City. Leveling data was used to validate the SBAR-InSAR productions, the error of SBAR-InSAR annual subsidence results was within 2 mm. The results showed that three main land subsidence zones were detected at Xinbei, Tianning and Wujin District. Four subsidence points were selected to analyze the temporal and spatial evolution characteristics of land subsidence. The subsidence rate of P1 to P4 was −2.48 mm/year, −12.78 mm/year, −18.09 mm/year, and −12.69 mm/year respectively. Land subsidence over Changzhou showed a trend of slowing down from 2011 to 2017, especially in Wujin District. SBAR-InSAR derived land deformation that correlates with the water level change in six groundwater stations. Indicated that with groundwater rebound, the land rebound obviously, and the maximum rebound vale reached 9.13 mm.


2021 ◽  
Author(s):  
Femi Emmanuel Ikuemonisan ◽  
Vitalis Chidi Ozebo ◽  
Olawale Babatunde Olatinsu

Abstract Lagos has a history of long-term groundwater abstraction that is often compounded by the rising indiscriminate private borehole and water well proliferation. This has resulted in various forms of environmental degradation, including land subsidence. Prediction of the temporal evolution of land subsidence is central to successful land subsidence management. In this study, a triple exponential smoothing algorithm was applied to predict the future trend of land subsidence in Lagos. Land subsidence time series is computed with SBAS-InSAR technique with Sentinel-1 acquisitions from 2015 to 2019. Besides, Matlab wavelet tool was implemented to investigate the periodicity within land displacement signal components and to understand the relationship between the observed land subsidence, and groundwater level change and that of soil moisture. Results show that land subsidence in the LOS direction varied approximately between –94 and 15 mm/year. According to the wavelet-based analysis result, land subsidence in Lagos is partly influenced by both groundwater level fluctuations and soil moisture variability. Evaluation of the proposed model indicates good accuracy, with the highest residual of approximately 8%. We then used the model to predict land subsidence between the years 2020 and 2023. The result showed that by the end of 2023 the maximum subsidence would reach 958 mm which is approximately 23% increase.


Sign in / Sign up

Export Citation Format

Share Document