Studying subsidence in urban areas and its effect on transportation infrastructure using the method based on Persistent Scatterer.

Arjmandrad, Mohammad Reza; Voosoghi, Behzad; Ghorbani, Zahra

doi:10.52547/jgst.12.3.113

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Volume 12, Issue 3 (3-2023)

JGST 2023, 12(3): 113-123

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Studying subsidence in urban areas and its effect on transportation infrastructure using the method based on Persistent Scatterer.

Mohammad Reza Arjmandrad

, Behzad Voosoghi

, Zahra Ghorbani ^*

Abstract: (571 Views)

In urban areas, deformation of transport and road infrastructure may lead to serious safety incidents. Therefore, management and monitoring are vital to ensure the quality of constructions and prevent transportation accidents, especially in areas with land subsidence such as Qom province. Low annual rainfall statistics, successive droughts and the type of soil in the region have caused this province, especially Qom city, to be among areas prone to land subsidence. The absence of a permanent geodynamic station in Qom's urban area, as well as the costly and time-consuming leveling operation, made radar interferometric technology to be chosen as one of the best methods for monitoring land deformation. In this study, the permanent scatterer interferometric synthetic aperture radar (PS-InSAR) technique has been used for infrastructure monitoring and inspection because it allows obtaining reliable results in the detection and prevention of infrastructure instabilities during time provides. For estimating land subsidence rate in the city of Qom, 29 descending radar images of the Sentinel-1 sensor were used during the period of January 2019 to November 2020. GMTSAR2StaMPS (G2S) software was used to process radar images and time series analysis. The results showed that southeastern area of Qom city has a subsidence rate of -54.5 mm/yr along the line of sight (LOS) of the satellite. The worrisome issue is the extension of land subsidence to the central area of the city and damage to important urban infrastructures, which should be taken into account in order to prevent this problem. The investigation of regional piezometers and Qom-Kahak hydrograph shows a drop of 1.8 meters in the water level between October 2017 and October 2021, which has caused subsidence of about -7.5 cm per year in the vertical direction in the southeast of Qom. Also, due to the good agreement of the results of radar interferometry and the drop of the underground level in the region, the excessive exploitation of underground water resources for agricultural purposes can be considered as the main reason for the subsidence in this area.

Article number: 8

Keywords: Subsidence, Qom, Interferometric radar, Sentinel-1, Underground water, Piezometers

Full-Text [PDF 1586 kb] (216 Downloads)

Type of Study: Research | Subject: Geo&Hydro
Received: 2022/10/29

References

1. Gao, M.; Gong, H.; Li, X.; Chen, B.; Zhou, C.; Shi, M.; Guo, L.; Chen, Z.; Ni, Z.; Duan, G. Land Subsidence and

2. Ground Fissures in Beijing Capital International Airport (BCIA): Evidence from Quasi-PS InSAR Analysis.

3. Remote Sens. 2019, 11, 1466.

4. Hu, S.; Zhang, H.; Zhang, L. Influence analysis of ground seam on urban overpass and disease prevention.

5. J. China Foreign Highw. 2018, 38, 167-172.

6. Bugajska, N. J., & Milczarek, W. J. (2021, March). Remote sensing monitoring of influence of underground mining in the area of the S3 Express Road. In IOP Conference Series: Earth and Environmental Science (Vol. 684, No. 1, p. 012028). IOP Publishing. [DOI:10.1088/1755-1315/684/1/012028]

7. Thapa, S., Chatterjee, R. S., Singh, K. B., & Kumar, D. (2016). LAND SUBSIDENCE MONITORING USING PS-InSAR TECHNIQUE FOR L-BAND SAR DATA. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 40. [DOI:10.5194/isprs-archives-XLI-B7-995-2016]

8. Tarighat, F., Foroughnia, F., & Perissin, D. (2021). Monitoring of power towers' movement using persistent scatterer SAR interferometry in south west of Tehran. Remote Sensing, 13(3), 407. [DOI:10.3390/rs13030407]

9. Lyu, M., Ke, Y., Li, X., Zhu, L., Guo, L., & Gong, H. (2020). Detection of seasonal deformation of highway overpasses using the PS-InSAR technique: A case study in Beijing urban area. Remote Sensing, 12(18), 3071. [DOI:10.3390/rs12183071]

10. Soodmand Afshar, R., & Ahmadi, S. (2020). Monitoring of land subsidence due to overexploitation of groundwater using PS-InSAR in the region in hamadan proviance, Iran. Engineering Journal of Geospatial Information Technology, 8(1), 79-99. [DOI:10.29252/jgit.8.1.79]

11. Deng, Z., Ke, Y., Gong, H., Li, X., & Li, Z. (2017). Land subsidence prediction in Beijing based on PS-InSAR technique and improved Grey-Markov model. GIScience & Remote Sensing, 54(6), 797-818. [DOI:10.1080/15481603.2017.1331511]

12. Maghsoudi, Y., van der Meer, F., Hecker, C., Perissin, D., & Saepuloh, A. (2018). Using PS-InSAR to detect surface deformation in geothermal areas of West Java in Indonesia. International journal of applied earth observation and geoinformation, 64, 386-396. [DOI:10.1016/j.jag.2017.04.001]

13. Hussain, S., Hongxing, S., Ali, M., & Ali, M. (2021). PS-InSAR based validated landslide susceptibility modelling: a case study of Ghizer valley, Northern Pakistan. Geocarto International, 1-22. [DOI:10.1080/10106049.2020.1870165]

14. Dwivedi, R., Varshney, P., Tiwari, A., Narayan, A. B., Singh, A. K., Dikshit, O., & Pallav, K. (2015, March). Monitoring of landslides in Nainital, Uttarakhand, India: validation of PS-InSAR results. In 2015 Joint Urban Remote Sensing Event (JURSE) (pp. 1-4). IEEE. [DOI:10.1109/JURSE.2015.7120538]

15. Galve, J.P.; Castañeda, C.; Gutiérrez, F. Railway deformation detected by DInSAR over active sinkholes in

16. the Ebro Valley evaporite karst, Spain. Hazards Earth Syst. Sci. 2015, 15, 2439-2448. [DOI:10.5194/nhess-15-2439-2015]

17. Galve, J.P.; Castañeda, C.; Gutiérrez, F.; Herrera, G. Assessing sinkhole activity in the Ebro Valley mantled

18. evaporite karst using advanced DInSAR. Geomorphology 2015, 229, 30-44. [DOI:10.1016/j.geomorph.2014.07.035]

19. Villarroel, C.D.; Beliveau, G.T.; Forte, A.P.; Monserrat, O.; Morvillo, M. DInSAR for a regional inventory of

20. active rock glaciers in the Dry Andes Mountains of Argentina and Chile with سنتینل-1 data. Remote Sens.

21. 2018, 10, 1588.

22. Solari, L.; Ciampalini, A.; Raspini, F.; Bianchini, S.; Moretti, S. PSInSAR analysis in the pisa urban area (Italy):

23. A case study of subsidence related to stratigraphical factors and urbanization. Remote Sens. 2016, 8, 120. [DOI:10.3390/rs8020120]

24. Ferretti, A.; Prati, C.; Rocca, F. Permanent scatterers in SAR interferometry. IEEE Trans. Geosci. Remote Sens.

25. 2001, 39, 8-20.

26. Babaee, S.S., S. Khazai, and F. Ghasser Mobarake, Interferometric Processing Time Series COSMO-SkyMed Pictures to Calculate Subsidence Rate of the Ground and Underground Structures. ISSGE, 2017. 7(1): p. 55-67.

27. Sandwell, D., Mellors, R., Tong, X., Xu, X., Wei, M., & Wessel, P. http://topex. ucsd. edu/gmtsar/tar/GMTSAR_2ND_TEX. pdf.

28. Hooper, A., Bekaert, D., Hussain, E., & Spaans, K. (2018). StaMPS/MTI manual: Version 4.1 b. School of Earth and Environment, University of Leeds. Retrieved October, 15, 2019.

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Arjmandrad M R, Voosoghi B, Ghorbani Z. Studying subsidence in urban areas and its effect on transportation infrastructure using the method based on Persistent Scatterer.. JGST 2023; 12 (3) : 8
URL: http://jgst.issgeac.ir/article-1-1119-en.html

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Volume 12, Issue 3 (3-2023)

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