Nowa metoda wyznaczania tensora odkształceń bazująca na obserwacjach InSAR

Witkowski, Wojciech T.; Hejmanowski, Ryszard

Artykuł - szczegóły

Tytuł artykułu

Nowa metoda wyznaczania tensora odkształceń bazująca na obserwacjach InSAR

Autorzy

Witkowski Wojciech T. , Hejmanowski Ryszard

Treść / Zawartość

Pełne teksty:

Pobierz

Identyfikatory

Warianty tytułu

A new method of determining the strain tensor based on InSAR observations

Języki publikacji

Abstrakty

Odkształcenia poziome towarzyszące deformacjom górniczym mają istotne znaczenie w aspekcie bezpieczeństwa zarówno infrastruktury technicznej, zabudowy powierzchniowej, jak i jakości życia osób żyjących na terenach podlegających przekształceniom. O ile kierunkowe odkształcenia poziome można łatwo wyznaczać wykorzystując klasyczne pomiary geodezyjne, o tyle brak jest metod obserwacji pełnego tensora odkształceń. W prezentowanych badaniach autorzy proponują nową metodę wyzna-czania tensora odkształceń poziomych, w której wykorzystywane są obserwacje satelitarnej interferometrii radarowej (InSAR). W pierwszej kolejności sprawdzono poprawność działania metody na danych teoretycznych, modelowych. Błąd względny wyznaczony dla wartości ekstremalnych odkształceń nie przekroczył 0,02 przy odchyleniu σ = +/-0,003. W dalszej kolejności zastosowano proponowaną metodę na rzeczywistym poligonie badawczym. Przemieszczenia kierunkowe (LOS) wyznaczono metodą Multi-Temporal InSAR, w wariancie małych baz (SBAS), dla danych z misji Sentinel-1. Dla przedstawionego przypadku uzyskano przemieszczenia pionowe powierzchni terenu wynoszące do -167 mm i składową przemieszczeń poziomych w zakresie od -110 mm do +62 mm. Dla tak wykształconego pola przemieszczeń, ekstremalne wartości odkształceń poziomych wahały się od -0,52 mm/m do +0,36 mm/m przy σ = +/-0,050 mm/m. Uzyskane wyniki świadczą o wysokiej i wystarczającej dla celów praktycznych dokładności metody wyznaczania tensora odkształcenia poziomego. Nowa metoda analizy wyników satelitarnych obserwacji radarowych rozszerza istniejące dotychczas możliwości geodezyjnego wyznaczania odkształceń.

Horizontal strain accompanying mining deformations have significant importance in terms of the safety of both technical infrastructure and the quality of life of people living in the areas undergoing transformation. While directional horizontal strain can be easily determined using classical geodetic measurements, there are no methods of observing the full deforma-tion tensor. In the presented research, the authors propose a new method for determining the horizontal strain tensor, which uses satellite radar interferometry (InSAR) observations. First, the correctness of the method was checked on theoretical and model data. The relative error determined for the extreme deformation values did not exceed 0.02 with the deviation σ = +/- 0.003. Subsequently, the proposed method was applied on a real cause study example. Directional displacements (LOS) were determined using the Multi-Temporal InSAR method, in the small baseline variant (SBAS), for the data from the Sentinel-1 mission. For the presented case, vertical displacements of the terrain surface were obtained, amounting to -167 mm, and the component of horizontal displacements ranging from -110 mm to +62 mm. For such a developed displacement field, the extreme values of horizontal deformations ranged from -0.52 mm/m to +0.36 mm/m with σ = +/-0.050 mm/m. The obtained results prove a high and sufficient for practical purposes the accuracy of the method of determining the horizontal strain tensor. The new method of analyzing the results of satellite radar observations extends the existing possibilities of geodetic determination of deformations.

Słowa kluczowe

deformacje górnicze InSAR odkształcenia poziome monitoring

mining deformation InSAR horizontal strain monitoring

Wydawca

Stowarzyszenie Inżynierów i Techników Górnictwa

Czasopismo

Przegląd Górniczy

Rocznik

2022

Tom

T. 78, nr 1

Strony

16--24

Opis fizyczny

Bibliogr. 47 poz., rys., wykr.

Twórcy

autor

Witkowski Wojciech T.

AGH Akademia Górniczo-Hutnicza w Krakowie

autor

Hejmanowski Ryszard

AGH Akademia Górniczo-Hutnicza w Krakowie

Bibliografia

1. AMBROŽIČ T., TURK G. 2003 - Prediction of Subsidence Due to Underground Mining by Artificial Neural Networks. Comput. Geosci., 29 (5), 627–637. https://doi.org/10.1016/S0098-3004(03)00044-X.
2. BARBATO J., HEBBLEWHITE B., MITRA R., MILLS K. 2016 - Prediction of Horizontal Movement and Strain at the Surface Due to Longwall Coal Mining. Int. J. Rock Mech. Min. Sci., 84, 105–118. https://doi.org/10.1016/j.ijrmms. 2016.02.006.
3. CHENG J., LIU F., LI S. 2017 - Model for the Prediction of Subsurface Strata Movement Due to Underground Mining. J. Geophys. Eng., 14 (6), 1608–1623. https://doi.org/10.1088/1742-2140/aa8238.
4. DAITO K., GALLOWAY D. L. 2015 - Preface: Prevention and Mitigation of Natural and Anthropogenic Hazards Due to Land Subsidence. In Proceedings of the International Association of Hydrological Sciences; Copernicus GmbH; Vol. 372, pp 555–557. https://doi.org/10.5194/piahs-372-555-2015.
5. DIA X., BAI Z., WU K., ZHO D., LI Z. 2018 - Assessment of Mining-Induced Damage to Structures Using InSAR Time Series Analysis: A Case Study of Jiulong Mine, China. Environ. Earth Sci., 77 (5), 166. https://doi.org/10.1007/s12665-018-7353-2.
6. DÍAZ-FERNÁNDEZ M.E., ÁLVAREZ-FERNÁNDEZ M.I., ÁLVAREZVIGIL A.E. 2010 - Computation of Influence Functions for Automatic Mining Subsidence Prediction. Comput. Geosci. https://doi.org/10.1007/s10596-009-9134-1.
7. FAN H., WANG L., WEN B., DU S. 2021 - A New Model for ThreeDimensional Deformation Extraction with Single-Track InSAR Based on Mining Subsidence Characteristics. Int. J. Appl. Earth Obs. Geoinf., 94, 102223. https://doi.org/10.1016/j.jag.2020.102223.
8. FAN L., LIU S. 2018 - Numerical Prediction of in Situ Horizontal Stress Evolution in Coalbed Methane Reservoirs by Considering Both Poroelastic and Sorption Induced Strain Effects. Int. J. Rock Mech. Min. Sci. 2018, 104, 156–164. https://doi.org/10.1016/j.ijrmms.2018.02.012.
9. FENG Q. Y., LIU G.J., MENG L., FU E.J., ZHANG H.R.. ZHANG K. 2008 - Land Subsidence Induced by Groundwater Extraction and Building Damage Level Assessment - a Case Study of Datun, China. J. China Univ. Min. Technol., 18 (4), 556–560. https://doi.org/10.1016/S1006-1266(08)60293-X.
10. GALLOWAY D. L. 2013 - Subsidence Induced by Underground Extraction. In Encyclopedia of Earth Sciences Series; Springer Netherlands, ; pp 979–985. https://doi.org/10.1007/978-1-4020-4399-4_336.
11. GALLOWAY D. L., BURBEY T. J. 2011 - Review: Regional Land Subsidence Accompanying Groundwater Extraction. Hydrogeol. J., 19 (8), 1459–1486. https://doi.org/10.1007/s10040-011-0775-5.
12. GUZY A., AHMED A. W., MALINOWSKA A. 2018 - Spatio-Temporal Distribution of Land Subsidence and Water Drop Caused by Underground Exploitation of Mineral Resources. In International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM; https://doi.org/10.5593/ sgem2018v/1.5/s02.058.
13. HANSSEN R. 2001 - Radar Interferometry - Data Interpretation and Error Analysis, 1st ed.; Remote Sensing and Digital Image Processing; Springer Netherlands: Dordrecht, Vol. 2. https://doi.org/10.1007/0-306-47633-9.
14. HEBBLEWHITE B. 2020 - Fracturing, Caving Propagation and Influence of Mining on Groundwater above Longwall Panels–a Review of Predictive Models. Int. J. Min. Sci. Technol. https://doi.org/10.1016/j.ijmst.2019.12.001.
15. HEJMANOWSKI R. 2015 - Modeling of Time-Dependent Subsidence for Coal and Ore Deposits. Int. J. Coal Sci. Technol. https://doi.org/10.1007/s40789-015-0092-z.
16. HEJMANOWSKI R., MALINOWSKA, A., KWINTA A., PATYKOWSKI G. 2016 - Prediction of Land Subsidence and Deformations at Copper Ore Underground Mining Site : Experiences and Verification Based on KGHM Mines in Poland. In 16th International Congress for Mine Surveying; Brisbane, Australia, 2016; pp 183–186.
17. Hooper A., Bekaert D., Spaans K., Arıkan M. 2012 - “Recent advances in SAR interferometry time series analysis for measuring crustal deformation,” Tectonophysics, vol. 514–517, pp. 1–13, Jan. 2012.
18. HU J., LI Z. W., DING X. L., ZHU J. J., ZHANG L., SUN Q. 2014 - Resolving Three-Dimensional Surface Displacements from InSAR Measurements: A Review. Earth-Science Reviews. Elsevier June 1, 2014, pp 1–17. https://doi.org/10.1016/j.earscirev.2014.02.005.
19. Hydrology I. A. of S. Land Subsidence: Proceedings of the Tokyo Symposium September 1969. Affaissement Du Sol; Actes Du Colloque de Tokyo Septembre 1969; Land Subsidence: Proceedings of the Tokyo Symposium September 1969. Affaissement Du Sol; Actes Du Colloque de Tokyo Septembre 1969; IASH/AIHS-Unesco, 1970.
20. JONES C.E., AN K., BLOM R.G., KENT J.D., IVINS E.R., BEKAERT D. 2016 - Anthropogenic and Geologic Influences on Subsidence in the Vicinity of New Orleans, Louisiana. J. Geophys. Res. Solid Earth.https://doi.org/10.1002/2015JB012636.
21. KWINTA A. 2012 - Prediction of Strain in a Shaft Caused by Underground Mining. Int. J. Rock Mech. Min. Sci. 2012, 55, 28–32. https://doi.org/10.1016/j.ijrmms.2012.06.007.
22. LEE S., PARK I. 2013 - Application of Decision Tree Model for the Ground Subsidence Hazard Mapping near Abandoned Underground Coal Mines. J. Environ. Manage., 127, 166–176. https://doi.org/10.1016/j.jenvman.2013.04.010.
23. LIU J.H. HU J. LI Z.W. ZHU J.J. SUN Q. GAN J. 2018 - A Method for Measuring 3-D Surface Deformations with InSAR Based on Strain Model and Variance Component Estimation. IEEE Trans. Geosci. Remote Sens., 56 (1), 239–250. https://doi.org/10.1109/ TGRS.2017.2745576.
24. LIU L., JIANG L., JIANG H., WANG H., MA N., XU H. 2019 - Accelerated Glacier Mass Loss (2011–2016) over the Puruogangri Ice Field in the Inner Tibetan Plateau Revealed by Bistatic InSAR Measurements Remote Sens. Environ., 231, 111241. https://doi.org/10.1016/j.rse.2019.111241.
25. MALINOWSKA A., HEJMANOWSKI R. 2010 - Building Damage Risk Assessment on Mining Terrains in Poland with GIS Application. Int. J. Rock Mech. Min. Sci., 47 (2), 238–245. https://doi.org/10.1016/j.ijrmms.2009.09.009.
26. MINH D.H.T., HANSSEN R., ROCCA F. 2020 - Radar Interferometry: 20 Years of Development in Time Series Techniques and Future Perspectives. Remote Sens., 12 (9), 1364. https://doi.org/10.3390/RS12091364.
27. OH H. J., LEE S. 2010 - Assessment of Ground Subsidence Using GIS and the Weights-of-Evidence Model. Eng. Geol. https://doi.org/10.1016/j.enggeo.2010.06.015.
28. PACHECO-MARTÍNEZ J., HERNANDEZ-MARÍN M., BURBEY T.J., GONZÁLEZ-CERVANTES N., ORTÍZ-LOZANO J.Á., ZERMEÑODE-LEON M.E., SOLÍS-PINTO A. 2013 - Land Subsidence and Ground Failure Associated to Groundwater Exploitation in the Aguascalientes Valley, México. Eng. Geol., 164, 172–186. https://doi.org/10.1016/j.enggeo.2013.06.015.
29. PARKER A.L., BIGGS J., LU Z. 2016 - Time-Scale and Mechanism of Subsidence at Lassen Volcanic Center, CA, from InSAR. J. Volcanol. Geotherm. Res., 320, 117–127. https://doi.org/10.1016/j.jvolgeores.2016.04.013.
30. RATEB A., ABOTALIB A. Z. 2020 - Inferencing the Land Subsidence in the Nile Delta Using Sentinel-1 Satellites and GPS between 2015 and 2019. Sci. Total Environ. 2020, 729, 138868. https://doi.org/10.1016/j.scitotenv.2020.138868.
31. REN H., FENG X. 2020 - Calculating Vertical Deformation Using a Single InSAR Pair Based on Singular Value Decomposition in Mining Areas. Int. J. Appl. Earth Obs. Geoinf., 92, 102115. https://doi.org/10.1016/j.jag.2020.102115.
32. RIESGO FERNÁNDEZ P., RODRÍGUEZ GRANDA G., KRZEMIEŃ A., GARCÍA CORTÉS S., FIDALGO VALVERDE G. 2020 - Subsidence versus Natural Landslides When Dealing with Property Damage Liabilities in Underground Coal Mines. Int. J. Rock Mech. Min. Sci., 126. https://doi.org/10.1016/j.ijrmms.2019.104175.
33. SAMIEIE-ESFAHANY S., HANSSEN R.F., VAN THIENEN-VISSER K., MUNTENDAM-BOS A. 2009 - “On the effect of horizontal deformation on InSAR subsidence estimates, Proc. ‘Fringe Workshop’, Frascati, Italy, 30 November – 4 December 2009 (ESA SP-677), 2009.
34. SHI X., FANG R., WU J., XU H., SUN Y.Y., YU J. 2012 - Sustainable Development and Utilization of Groundwater Resources Considering Land Subsidence in Suzhou, China. Eng. Geol., 124 (1), 77–89. https://doi.org/10.1016/j.enggeo.2011.10.005.
35. SINGH R.P., YADAV R. N. 1995 - Prediction of Subsidence Due to Coal Mining in Raniganj Coalfield, West Bengal, India. Eng. Geol. https://doi.org/10.1016/0013-7952(94)00062-7.
36. STEINBERG A., SUDHAUS H., HEIMANN S., KRÜGER F. 2020 - Sensitivity of InSAR and Teleseismic Observations to Earthquake Rupture Segmentation. Geophys. J. Int., 223 (2), 875–907. https://doi. org/10.1093/gji/ggaa351.
37. STOCH T. 2019 - Przemieszczenia poziome w ochronie terenów górniczych – Horizontal displacements in mining areas protection, Monografia, Kraków, Wydawnictwa AGH.
38. STROZZI T., CADUFF R., WEGMÜLLER U., RAETZO H., HAUSER M. 2017 - Widespread Surface Subsidence Measured with Satellite SAR Interferometry in the Swiss Alpine Range Associated with the Construction of the Gotthard Base Tunnel. Remote Sens. Environ., 190, 1–12. https://doi.org/10.1016/j.rse.2016.12.007.
39. SUH J. 2020 - An Overview of GIS-Based Assessment and Mapping of Mining-Induced Subsidence. Appl. Sci., 10 (21), 1–23. https://doi.org/10.3390/app10217845.
40. TRUPLETT T., YURCHAK D. 1996 - Determination of Intensity Functions for Predicting Subsidence from Coal Mining, Potash Mining, and Groundwater Withdrawal Using the Influence Function Technique. In 6. international FIG symposium on deformation measurements: measurement, modelling and prediction; Hannover, Germany, 1996; pp 761–773.
41. WANG B., XU J., XUAN D. 2018 - Time Function Model of Dynamic Surface Subsidence Assessment of Grout-Injected Overburden of a Coal Mine. Int. J. Rock Mech. Min. Sci., 104, 1–8. https://doi.org/10.1016/j.ijrmms.2018.01.044.
42. WASOWSKI J., PISANO L. 2020 - Long-Term InSAR, Borehole Inclinometer, and Rainfall Records Provide Insight into the Mechanism and Activity Patterns of an Extremely Slow Urbanized Landslide. Landslides, 17 (2), 445–457. https://doi.org/10.1007/s10346-019-01276-7.
43. WHITTAKER B.N., REDDISH D. J. 1989 - Subsidence: Occurrence, Prediction, and Control; Elsevier, 1989.
44. YANG Z., LI Z., ZHU J., PREUSSE A., HU J., FENG G., WANG Y., PAPST M. 2018 - An InSAR-Based Temporal Probability Integral Method and Its Application for Predicting Mining-Induced Dynamic Deformations and Assessing Progressive Damage to Surface Buildings. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 11 (2), 472–484. https://doi.org/10.1109/JSTARS.2018.2789341.
45. YANG Z., LI Z., ZHU J., PREUSSE A., YI H., HU J., FEN G., PAPST M. 2017 - Retrieving 3-D Large Displacements of Mining Areas from a Single Amplitude Pair of SAR Using Offset Tracking. Remote Sens., 9 (4), 338. https://doi.org/10.3390/rs9040338.
46. YANG Z., LI Z., ZHU J., WANG Y., WU L. 2020 - Use of SAR/InSAR in Mining Deformation Monitoring, Parameter Inversion, and Forward Predictions: A Review. IEEE Geoscience and Remote Sensing Magazine. Institute of Electrical and Electronics Engineers Inc. March 1, pp 71–90. https://doi.org/10.1109/MGRS.2019.2954824.
47. ZHANG L., CHENG H., YAO Z., WANG X. 2020 - Application of the Improved Knothe Time Function Model in the Prediction of Ground Mining Subsidence: A Case Study from Heze City, Shandong Province, China. Appl. Sci., 10 (9), 3147. https://doi.org/10.3390/app10093147.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu „Społeczna odpowiedzialność nauki” - moduł: Popularyzacja nauki i promocja sportu (2022-2023)

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-28b42dd0-5dd2-4a16-b843-bed8d88e4204