Loess Slope Instability Assessment Based on PS-InSAR Detected and Spatial Analysis in Lanzhou Region, China

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Abstract:

Lanzhou is a mountainous city in which serious disasters have occurred due to several slope hazards. We used PS-InSAR technique to detect surface deformation: an indicator of potential hazards. In the period extending from 2003 to 2010, 41 Envisat ASAR images were captured and analyzed using PS-InSAR. We identified 27186 PS points. The deformation velocity in this area is found to being 3.5 mm/year ~ -5.4 mm/year. The results were inserted into a GIS to derive spatial interpolations and map zones with different magnitudes of surface displacement. Then, we used the analytical hierarchic process (AHP) to statistically assess the susceptibility of loess slope hazards with lithology, slope, altitude, distance to road, Ndvi, land use and aspect. According to the result of the model, the study area could be classified into three categories: stable, less unstable and unstable. Causal mechanisms include human interactions in the landscape (construction, waste water discharge, etc.) and slope instability processes (landslide, subsidence, etc.).

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Advanced Materials Research (Volumes 1065-1069)

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2342-2352

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December 2014

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© 2015 Trans Tech Publications Ltd. All Rights Reserved

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[1] Z.Q. Ding, Z.H. Li: Lanzhou city geological disaster and Prevention. Gansu Science and Technology Publisher, (2009).

Google Scholar

[2] F. Bovenga, J. Wasowski, D.O. Nitti, R. Nutricato, M.T. Chiaradia: Remote Sensing of Environment Vol. 119, (2012), p.272.

DOI: 10.1016/j.rse.2011.12.013

Google Scholar

[3] Y.H. Zhang, J.X. Zhang, H.A. Wu, Z.W. Wu, G.T. Sun: International Journal of Applied Earth Observation and Geoinformation Vol. 13, (2011), p.812.

Google Scholar

[4] A. Hooper, H. Zebker, P. Segall, B. Kampes: Geophysical Research Letters Vol. 31(23), (2004), p.611.

Google Scholar

[5] A. Hooper, H. Zebker: Optical Society of America Vol. 24(9), (2007), p.2737.

Google Scholar

[6] M. Morelli, F. Piana, L. Mallen, G. Nicolo, G. Fioraso: Remote Sensing of Environment Vol. 115, (2011), p.1188.

Google Scholar

[7] A. Ferretti, C. Prati, F. Rocca: Proceedings of IEEE International Geoscience and Remote Sensing Symposium, June 28–July 2, (1999), p.1528.

Google Scholar

[8] A. Ferretti, C. Prati, F. Rocca: IEEE Transactions on Geoscience and Remote Sensing, Vol. 38 (5), (2000), p. (2002).

Google Scholar

[9] S.I.N. Heloeno, L.G.S. Oliveira, M.J. Henriques, A.P. Falcao, J.N.P. Lima: Remote Sensing of Environment Vol. 115, (2011), p.2152.

Google Scholar

[10] J.J. Sousa, A. Ruiz, R. Hassen, L. Bastos, A. Gill, J. Galindo-Zaldivar, C. Galdeano: Journal of Geodynamics Vol. 49, (2010), p.181.

Google Scholar

[11] C. Colesanti, A. Ferretti, C. Prati, F. Rocca: Eng. Geol Vol. 68, (2003), p.3.

Google Scholar

[12] F. Ocakoglu, C. Gokoeoglu, M. Ercanoglu: Geomorphology Vole. 42(3), (2002), p.329.

Google Scholar

[13] S. Lee, K. Min: Environmental Geology Vol. 40, (2001), p.1095.

Google Scholar

[14] A. Yalcin: PhD Thesis, Karadeniz Technical University, Trabzon, Turkey, (2005).

Google Scholar

[15] J. Malczewski: GIS and Multi-criteria Decision Analysis. John Wiley and Sons, New York, (1999).

Google Scholar

[16] E. Derbyshire, X.M. Meng, T.A. Dijkstra: Landslides in the thick loess terrain of northwest China: mechanisms and mitigation. John Wiley and Sons, Ltd, Chichester, (2000).

Google Scholar

[17] P. Mu, L.F. Dong, W.J. Wu: Northwestern Seismological Journal Vol 30, (2008), p.332.

Google Scholar

[18] Y.P. Yin, Z.C. Zhang, Z.H. Li, S.Q. Zhang, J. Yu: Quaternary Sciences Vol. 24, (2004), p.302.

Google Scholar

[19] H. Gao, Y.J. Zhang, X.G. Zhang: Gansu Geogloy Vol. 21, (2012), p.30.

Google Scholar

[20] H. Wu, L. Shao, D.R. Lu: Arid Meteorology Vol. 23, (2005), p.63.

Google Scholar