參考文獻 |
Abolmasov, B., Milenković, S., Jelisavac, B., Pejić, M., andRadić, Z. (2015). The Analysis of Landslide Dynamics Based on Automated GNSS Monitoring—A Case Study. In Engineering Geology for Society and Territory - Volume 2 (pp. 143-146).
Antonielli, Mazzanti, Rocca, Bozzano, andDei, C. (2019). A-DInSAR Performance for Updating Landslide Inventory in Mountain Areas: An Example from Lombardy Region (Italy). Geosciences, 9(9), 364. doi:10.3390/geosciences9090364
Aslan, G., Foumelis, M., Raucoules, D., De Michele, M., Bernardie, S., andCakir, Z. (2020). Landslide Mapping and Monitoring Using Persistent Scatterer Interferometry (PSI) Technique in the French Alps. Remote Sensing, 12(8), 1305. doi:10.3390/rs12081305
Barla, G., Antolini, F., Barla, M., Mensi, E., andPiovano, G. (2010). Monitoring of the Beauregard landslide (Aosta Valley, Italy) using advanced and conventional techniques. Engineering Geology, 116(3-4), 218-235. doi:10.1016/j.enggeo.2010.09.004
Berardino, P., Fornaro, G., Lanari, R., andSansosti, E. (2002). A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11), 2375-2383. doi:10.1109/tgrs.2002.803792
Bobrowsky, P., Sladen, W., Huntley, D., Qing, Z., Bunce, C., Edwards, T., Hendry, M., Martin, D., andChoi, E. (2015). Multi-parameter Monitoring of a Slow Moving Landslide: Ripley Slide, British Columbia, Canada. In Engineering Geology for Society and Territory - Volume 2 (pp. 155-158).
133
Booysen, R., Gloaguen, R., Lorenz, S., Zimmermann, R., andNex, P. A. M. (2021). Geological Remote Sensing. 301-314. doi:10.1016/b978-0-12-409548-9.12127-x
Bovenga, F., Pasquariello, G., Pellicani, R., Refice, A., andSpilotro, G. (2017). Landslide monitoring for risk mitigation by using corner reflector and satellite SAR interferometry: The large landslide of Carlantino (Italy). Catena, 151, 49-62. doi:10.1016/j.catena.2016.12.006
Brückl, E., Brunner, F. K., andKraus, K. (2006). Kinematics of a deep‐seated landslide derived from photogrammetric, GPS and geophysical data. Engineering Geology, 88(3-4), 149-159. doi:10.1016/j.enggeo.2006.09.004
Calamita, G., Serlenga, V., Stabile, T. A., Gallipoli, M. R., Bellanova, J., Bonano, M., Casu, F., Vignola, L., Piscitelli, S., andPerrone, A. (2018). An integrated geophysical approach for urban underground characterization: the Avigliano town (southern Italy) case study. Geomatics, Natural Hazards and Risk, 10(1), 412-432. doi:10.1080/19475705.2018.1526220
Campbell, J. B., andWynne, R. H. (2011). Introduction to Remote Sensing, Fifth Edition. New York: The Guilford Press.
Carlà, T., Tofani, V., Lombardi, L., Raspini, F., Bianchini, S., Bertolo, D., Thuegaz, P., andCasagli, N. (2019). Combination of GNSS, satellite InSAR, and GBInSAR remote sensing monitoring to improve the understanding of a large landslide in high alpine environment. Geomorphology, 335, 62-75. doi:10.1016/j.geomorph.2019.03.014
Cascini, L., Fornaro, G., andPeduto, D. (2010). Advanced low- and full-resolution DInSAR map generation for slow-moving landslide analysis at different scales. Engineering Geology, 112(1-4), 29-42. doi:10.1016/j.enggeo.2010.01.003
134
Casu, F., Elefante, S., Imperatore, P., Zinno, I., Manunta, M., De Luca, C., andLanari, R. (2014). SBAS-DInSAR Parallel Processing for Deformation Time-Series Computation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(8), 3285-3296. doi:10.1109/jstars.2014.2322671
Casu, F., Manzo, M., andLanari, R. (2006). A quantitative assessment of the SBAS algorithm performance for surface deformation retrieval from DInSAR data. Remote Sensing of Environment, 102(3-4), 195-210. doi:10.1016/j.rse.2006.01.023
Chaabani, A., andDeffontaines, B. (2020). Application of the SBAS-DInSAR technique for deformation monitoring in Tunis City and Mornag plain. Geomatics, Natural Hazards and Risk, 11(1), 1346-1377. doi:10.1080/19475705.2020.1788654
Chen, R.-F., Lee, C.-Y., Yin, H.-Y., Huang, H.-Y., Cheng, K.-P., andLin, C.-W. (2017). Monitoring the Deep-Seated Landslides by Using ALOS/PALSAR Satellite Imagery in the Disaster Area of 2009 Typhoon Morakot, Taiwan. 239-247. doi:10.1007/978-3-319-53487-9_27
Colesanti, C., andWasowski, J. (2006). Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry. Engineering Geology, 88(3-4), 173-199. doi:10.1016/j.enggeo.2006.09.013
Corominas, J., van Westen, C., Frattini, P., Cascini, L., Malet, J. P., Fotopoulou, S., Catani, F., Van Den Eeckhaut, M., Mavrouli, O., Agliardi, F., Pitilakis, K., Winter, M. G., Pastor, M., Ferlisi, S., Tofani, V., Hervás, J., andSmith, J. T. (2014). Recommendations for the quantitative analysis of landslide risk. Bulletin of Engineering Geology and the Environment. doi:10.1007/s10064-013-0538-8
Cruden, D. M., andVarnes, D. J. (1996). Landslide Types and Processes (Special Report ed. Vol. 247). Washington, DC: U.S. National Academy of Sciences.
135
Du, Y., Feng, G., Liu, L., Fu, H., Peng, X., andWen, D. (2020). Understanding Land Subsidence Along the Coastal Areas of Guangdong, China, by Analyzing Multi-Track MTInSAR Data. Remote Sensing, 12(2). doi:10.3390/rs12020299
Dumka, R. K., SuriBabu, D., Malik, K., Prajapati, S., andNarain, P. (2020). PS-InSAR derived deformation study in the Kachchh, Western India. Applied Computing and Geosciences, 8. doi:10.1016/j.acags.2020.100041
Dwivedi, R., Narayan, A. B., Tiwari, A., Dikshit, O., andSingh, A. K. (2016). Multi-Temporal Sar Interferometry for Landslide Monitoring. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLI-B8, 55-58. doi:10.5194/isprsarchives-XLI-B8-55-2016
Fárová, K., Jelének, J., Kopačková-Strnadová, V., andKycl, P. (2019). Comparing DInSAR and PSI Techniques Employed to Sentinel-1 Data to Monitor Highway Stability: A Case Study of a Massive Dobkovičky Landslide, Czech Republic. Remote Sensing, 11(22). doi:10.3390/rs11222670
Ferretti, A., Guarnieri, A. M., Prati, C., andRocca, F. (2007). InSAR Principles: Guidelines for SAR Interferometry Processing and Interpretation. The Netherlands: ESA Publications.
Ferretti, A., Prati, C., andRocca, F. (1999). Permanent Scatterers in SAR Interferometry. IEEE Geoscience and Remote Sensing Magazine.
Ferretti, A., Prati, C., andRocca, F. (2001). Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1), 8-20. doi:10.1109/36.898661
Florinsky, I. (2016). Digital Terrain Analysis in Soil Science and Geology. London Wall, London, UK: Academic Press.
136
Foroughnia, F., Nemati, S., Maghsoudi, Y., andPerissin, D. (2019). An iterative PS-InSAR method for the analysis of large spatio-temporal baseline data stacks for land subsidence estimation. International Journal of Applied Earth Observation and Geoinformation, 74, 248-258. doi:10.1016/j.jag.2018.09.018
Gabriel, A. K., Goldstein, R. M., andZebker, H. A. (1989). Mapping small elevation changes over large areas: Differential radar interferometry. Journal of Geophysical Research, 94(B7). doi:10.1029/JB094iB07p09183
Goorabi, A. (2020). Detection of landslide induced by large earthquake using InSAR coherence techniques – Northwest Zagros, Iran. The Egyptian Journal of Remote Sensing and Space Science, 23(2), 195-205. doi:10.1016/j.ejrs.2019.04.002
Hanssen, R. F. (2001). Radar Interferometry: Data Interpretation and Error Analysis. London: Kluwer Academic Publishers.
Hanssen, R. F., andFerretti, A. (2002). Deformation Monitoring by Satellite Interferometry. GIM International.
Hein, A. (2004). Processing of SAR Data_ Fundamentals, Signal Processing, Interferometry. Heidelberg: Springer-Verlag Berlin Heidelberg.
Hoek, E., andBray, J. W. (1981). Rock slope engineering (3rd edition). London: The Institution of Mining and Metallurgy.
Hooper, A., Segall, P., andZebker, H. (2007). Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcán Alcedo, Galápagos. Journal of Geophysical Research, 112(B7). doi:10.1029/2006jb004763
Hooper, A., Zebker, H., Segall, P., andKampes, B. (2004). A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers. Geophysical Research Letters, 31(23). doi:10.1029/2004gl021737
137
Höser, T. (2018). Analysing the Capabilities and Limitations of InSAR using Sentinel-1 data for Landslide Detection and Monitoring. (Master of Science), University of Bonn,
Hu, J., Li, Z. W., Ding, X. L., Zhu, J. J., Zhang, L., andSun, Q. (2014). Resolving three-dimensional surface displacements from InSAR measurements: A review. Earth-Science Reviews, 133, 1-17. doi:10.1016/j.earscirev.2014.02.005
Intrieri, E., Raspini, F., Fumagalli, A., Lu, P., Del Conte, S., Farina, P., Allievi, J., Ferretti, A., andCasagli, N. (2017). The Maoxian landslide as seen from space: detecting precursors of failure with Sentinel-1 data. Landslides, 15(1), 123-133. doi:10.1007/s10346-017-0915-7
Jennifer, J. J., Saravanan, S., andPradhan, B. (2020). Persistent Scatterer Interferometry in the post-event monitoring of the Idukki Landslides. Geocarto International, 1-15. doi:10.1080/10106049.2020.1778101
Kampes, B. M. (2006). Radar Interferometry Persistent Scatterer Technique. The Netherland: Springer.
Lanari, R., Casu, F., Manzo, M., Zeni, G., Berardino, P., Manunta, M., andPepe, A. (2007). An Overview of the Small BAseline Subset Algorithm: a DInSAR Technique for Surface Deformation Analysis. Pure and Applied Geophysics, 164(4), 637-661. doi:10.1007/s00024-007-0192-9
Li, Z., Cao, Y., Wei, J., Duan, M., Wu, L., Hou, J., andZhu, J. (2019). Time-series InSAR ground deformation monitoring: Atmospheric delay modeling and estimating. Earth-Science Reviews, 192, 258-284. doi:10.1016/j.earscirev.2019.03.008
Lillesand, T. M., Kiefer, R. W., andChipman, J. (2015). Remote Sensing and Image Interpretation. The United States of America: Wiley.
138
McCormack, H., Thomas, A., andSolomon, I. The capabilities and limitations of satellite InSAR and terrestrial radar interferometry.pdf>. Fugro NPA Limited.
Moreira, A., Prats-Iraola, P., Younis, M., Krieger, G., Hajnsek, I., andPapathanassiou, K. P. (2013). A tutorial on synthetic aperture radar. IEEE Geoscience and Remote Sensing Magazine, 1(1), 6-43. doi:10.1109/mgrs.2013.2248301
Oštir, K., andKomac, M. (2007). PSInSAR and DInSAR methodology comparison and their applicability in the field of surface deformations–A case of NW Slovenia. Geologija, 50(1), 77-96. doi:10.5474/geologija.2007.007
Ottinger, M., andKuenzer, C. (2020). Spaceborne L-Band Synthetic Aperture Radar Data for Geoscientific Analyses in Coastal Land Applications: A Review. Remote Sensing, 12(14). doi:10.3390/rs12142228
Pawluszek-Filipiak, K., andBorkowski, A. (2020). Integration of DInSAR and SBAS Techniques to Determine Mining-Related Deformations Using Sentinel-1 Data: The Case Study of Rydułtowy Mine in Poland. Remote Sensing, 12(2). doi:10.3390/rs12020242
Pepe, A., Solaro, G., Calo, F., andDema, C. (2016). A Minimum Acceleration Approach for the Retrieval of Multiplatform InSAR Deformation Time Series. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(8), 3883-3898. doi:10.1109/jstars.2016.2577878
Purkis, S., andKlemas, V. (2011). Remote Sensing and Global Environmental Change. John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK: Wiley-Blackwell.
Shanker, P., Casu, F., Zebker, H. A., andLanari, R. (2011). Comparison of Persistent Scatterers and Small Baseline Time-Series InSAR Results: A Case Study of the San
139
Francisco Bay Area. IEEE Geoscience and Remote Sensing Letters, 8(4), 592-596. doi:10.1109/lgrs.2010.2095829
Sousa, J. J., Hooper, A. J., Hanssen, R. F., Bastos, L. C., andRuiz, A. M. (2011). Persistent Scatterer InSAR: A comparison of methodologies based on a model of temporal deformation vs. spatial correlation selection criteria. Remote Sensing of Environment, 115(10), 2652-2663. doi:10.1016/j.rse.2011.05.021
Sun, Q., Zhang, L., Ding, X. L., Hu, J., Li, Z. W., andZhu, J. J. (2015). Slope deformation prior to Zhouqu, China landslide from InSAR time series analysis. Remote Sensing of Environment, 156, 45-57. doi:10.1016/j.rse.2014.09.029
Townsend, P. A. (2002). Estimating forest structure in wetlands using multitemporal SAR. Remote Sensing of Environment, 79, 288-304.
U-Blox. (2020). ZED-F9P IntegrationManual_(UBX-18010802): u-blox AG.
Varnes, D. J. (1978). Slope Movement Types and Processes. In Special Report 176: Landslides: Analysis and Control (Eds: Schuster, R.L and Krizek, R.J) (pp. 11-33). Washington D.C: Transportation and Road research board, National Academy of Science.
Vicari, A., Famiglietti, N. A., Colangelo, G., andCecere, G. (2019). A comparison of multi temporal interferometry techniques for landslide susceptibility assessment in urban area: an example on stigliano (MT), a town of Southern of Italy. Geomatics, Natural Hazards and Risk, 10(1), 836-852. doi:10.1080/19475705.2018.1549113
Wasowski, J., andBovenga, F. (2014). Investigating landslides and unstable slopes with satellite Multi Temporal Interferometry: Current issues and future perspectives. Engineering Geology, 174, 103-138. doi:10.1016/j.enggeo.2014.03.003
Wempen, J. M. (2020). Application of DInSAR for short period monitoring of initial subsidence due to longwall mining in the mountain west United States. International
140
Journal of Mining Science and Technology, 30(1), 33-37. doi:10.1016/j.ijmst.2019.12.011
Xiao, R., andHe, X. (2013). GPS and InSAR Time Series Analysis: Deformation Monitoring Application in a Hydraulic Engineering Resettlement Zone, Southwest China. Mathematical Problems in Engineering, 2013, 1-11. doi:10.1155/2013/601209
Zebker, H., andVillasenor, J. (1992). Decorrelation in Interferometric Radar Echoes. IEEE Transactions on Geoscience and Remote Sensing, 30, 950-959.
Zhang, L., Sun, Q., andHu, J. (2018). Potential of TCPInSAR in Monitoring Linear Infrastructure with a Small Dataset of SAR Images: Application of the Donghai Bridge, China. Applied Sciences, 8(3), 425. doi:10.3390/app8030425
Zhang, Y., Meng, X. M., Dijkstra, T. A., Jordan, C. J., Chen, G., Zeng, R. Q., andNovellino, A. (2020). Forecasting the magnitude of potential landslides based on InSAR techniques. Remote Sensing of Environment, 241, 111738. doi:10.1016/j.rse.2020.111738
Zhao, C.-y., Zhang, Q., Yang, C., andZou, W. (2011). Integration of MODIS data and Short Baseline Subset (SBAS) technique for land subsidence monitoring in Datong, China. Journal of Geodynamics, 52(1), 16-23. doi:10.1016/j.jog.2010.11.004 |