[
Ansari, H., De Zan, F., and Bamler, R. (2017). Sequential Estimator: Toward Efficient InSAR Time Series Analysis. IEEE Transactions on Geoscience and Remote Sensing, 55(10):5637–5652, doi:10.1109/tgrs.2017.2711037.
]Search in Google Scholar
[
Ansari, H., De Zan, F., and Bamler, R. (2018). Efficient Phase Estimation for Interferogram Stacks. IEEE Transactions on Geoscience and Remote Sensing, 56(7):4109–4125, doi:10.1109/tgrs.2018.2826045.
]Search in Google Scholar
[
Bateson, L., Cigna, F., Boon, D., and Sowter, A. (2015). The application of the Intermittent SBAS (ISBAS) InSAR method to the South Wales Coalfield, UK. International Journal of Applied Earth Observation and Geoinformation, 34:249–257, doi:10.1016/j.jag.2014.08.018.
]Search in Google Scholar
[
Berardino, P., Fornaro, G., Lanari, R., and Sansosti, 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.
]Search in Google Scholar
[
Dai, K., Deng, J., Xu, Q., Li, Z., Shi, X., Hancock, C., Wen, N., Zhang, L., and Zhuo, G. (2022). Interpretation and sensitivity analysis of the InSAR line of sight displacements in landslide measurements. GIScience and Remote Sensing, 59(1):1226–1242, doi:10.1080/15481603.2022.2100054.
]Search in Google Scholar
[
Deledalle, C.-A., Denis, L., Tupin, F., Reigber, A., and Jager, M. (2015). NL-SAR: A Unified Nonlocal Framework for Resolution-Preserving (Pol)(In)SAR Denoising. IEEE Transactions on Geoscience and Remote Sensing, 53(4):2021–2038, doi:10.1109/tgrs.2014.2352555.
]Search in Google Scholar
[
Dong, J., Qiu, M., Zhao, J., Li, H., and Wu, Q. (2022). Deformation instability mechanism of slope in Fa’er Town,
]Search in Google Scholar
[
Shuicheng County, Guizhou, China. Alexandria Engineering Journal, 61(10):8289–8295, doi:10.1016/j.aej.2022.01.042.
]Search in Google Scholar
[
Ferretti, A., Fumagalli, A., Novali, F., Prati, C., Rocca, F., and Rucci, A. (2011). A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR. IEEE Transactions on Geoscience and Remote Sensing, 49(9):3460–3470, doi:10.1109/tgrs.2011.2124465.
]Search in Google Scholar
[
Ferretti, A., Prati, C., and Rocca, F. (2001). Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1):8–20, doi:10.1109/36.898661.
]Search in Google Scholar
[
Fobert, M.-A., Singhroy, V., and Spray, J. G. (2021). InSAR Monitoring of Landslide Activity in Dominica. Remote Sensing, 13(4):815, doi:10.3390/rs13040815.
]Search in Google Scholar
[
Fornaro, G., Verde, S., Reale, D., and Pauciullo, A. (2015). CAESAR: An Approach Based on Covariance Matrix Decomposition to Improve Multibaseline–Multitemporal Interferometric SAR Processing. IEEE Transactions on Geoscience and Remote Sensing, 53(4):2050–2065, doi:10.1109/tgrs.2014.2352853.
]Search in Google Scholar
[
Guo, J., Cui, Y., Xu, W., Yin, Y., Li, Y., and Jin, W. (2022). Numerical investigation of the landslide-debris flow transformation process considering topographic and entrainment effects: a case study. Landslides, 19(4):773–788, doi:10.1007/s10346-021-01791-6.
]Search in Google Scholar
[
He, L., Pei, P., Zhang, X., Qi, J., Cai, J., Cao, W., Ding, R., and Mao, Y. (2023a). Sensitivity Evaluation of Time Series InSAR Monitoring Results for Landslide Detection. Remote Sensing, 15(15):3906, doi:10.3390/rs15153906.
]Search in Google Scholar
[
He, Y., Wang, W., Zhang, L., Chen, Y., Chen, Y., Chen, B., He, X., and Zhao, Z. (2023b). An identification method of potential landslide zones using InSAR data and landslide susceptibility. Geomatics,NaturalHazardsandRisk, 14(1), doi:10.1080/19475705.2023.2185120.
]Search in Google Scholar
[
Hetland, E. A., Musé, P., Simons, M., Lin, Y. N., Agram, P. S., and DiCaprio, C. J. (2012). Multiscale InSAR Time Series (MInTS) analysis of surface deformation. JournalofGeophysical Research: Solid Earth, 117(B2), doi:10.1029/2011jb008731.
]Search in Google Scholar
[
Hooper, A. (2008). A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches. Geophysical Research Letters, 35(16), doi:10.1029/2008gl034654.
]Search in Google Scholar
[
Hu, K., Wu, C., Tang, J., Pasuto, A., Li, Y., and Yan, S. (2018). New understandings of the June 24th 2017 Xinmo Landslide, Maoxian, Sichuan, China. Landslides, 15(12):2465–2474, doi:10.1007/s10346-018-1073-2.
]Search in Google Scholar
[
Jia, H., Wang, Y., Ge, D., Deng, Y., and Wang, R. (2022). InSAR Study of Landslides: Early Detection, Three-Dimensional, and Long-Term Surface Displacement Estimation—A Case of Xiaojiang River Basin, China. Remote Sensing, 14(7):1759, doi:10.3390/rs14071759.
]Search in Google Scholar
[
Jiao, Y.-Y., Wang, Z.-H., Wang, X.-Z., Adoko, A. C., and Yang, Z.-X. (2013). Stability assessment of an ancient landslide crossed by two coal mine tunnels. Engineering Geology, 159:36–44, doi:10.1016/j.enggeo.2013.03.021.
]Search in Google Scholar
[
Li, W., Zhan, W., Lu, H., Xu, Q., Pei, X., Wang, D., Huang, R., and Ge, D. (2022). Precursors to large rockslides visible on optical remote-sensing images and their implications for landslide early detection. Landslides, 20(1):1–12, doi:10.1007/s10346-022-01960-1.
]Search in Google Scholar
[
Li, X., Zhou, L., Su, F., and Wu, W. (2021). Application of InSAR technology in landslide hazard: Progress and prospects. National Remote Sensing Bulletin, 25(2):614–629, doi:10.11834/jrs.20209297.
]Search in Google Scholar
[
Ma, Z.-F., Jiang, M., and Huang, T. (2020). A sequential approach for Sentinel-1 TOPS time-series coregistration over low coherence scenarios. IEEE Transactions on Geoscience and Remote Sensing, 59(6):4818–4826, doi:10.1109/TGRS.2020.3009996.
]Search in Google Scholar
[
Ma, Z.-F., Jiang, M., Khoshmanesh, M., and Cheng, X. (2021). Time series phase unwrapping based on graph theory and compressed sensing. IEEE Transactions on Geoscience and Remote Sensing, 60:1–12, doi:10.1109/TGRS.2021.3066784.
]Search in Google Scholar
[
Ma, Z.-F., Jiang, M., Zhao, Y., Malhotra, R., and Yong, B. (2019). Minimum spanning tree co-registration approach for time-series Sentinel-1 TOPS data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(8):3004–3013, doi:10.1109/JSTARS.2019.2920717.
]Search in Google Scholar
[
Moretto, S., Bozzano, F., and Mazzanti, P. (2021). The Role of Satellite InSAR for Landslide Forecasting: Limitations and Openings. Remote Sensing, 13(18):3735, doi:10.3390/rs13183735.
]Search in Google Scholar
[
Perissin, D. and Wang, T. (2011). Time-Series InSAR Applications Over Urban Areas in China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4(1):92–100, doi:10.1109/jstars.2010.2046883.
]Search in Google Scholar
[
Schmitt, M., Schonberger, J. L., and Stilla, U. (2014). Adaptive Covariance Matrix Estimation for Multi-Baseline InSAR Data Stacks. IEEE Transactions on Geoscience and Remote Sensing, 52(11):6807–6817, doi:10.1109/tgrs.2014.2303516.
]Search in Google Scholar
[
van Natijne, A., Bogaard, T., van Leijen, F., Hanssen, R., and Lindenbergh, R. (2022). World-wide InSAR sensitivity index for landslide deformation tracking. International Journal of Applied Earth Observation and Geoinformation, 111:102829, doi:10.1016/j.jag.2022.102829.
]Search in Google Scholar
[
Vu, P. V. H., Breloy, A., Brigui, F., Yan, Y., and Ginolhac, G. (2023). Robust Phase Linking in InSAR. IEEE Transactions on Geoscience and Remote Sensing, 61:1–11, doi:10.1109/tgrs.2023.3289338.
]Search in Google Scholar
[
Wang, Y. and Zhu, X. X. (2016). Robust Estimators for Multipass SAR Interferometry. IEEE Transactions on Geoscience and Remote Sensing, 54(2):968–980, doi:10.1109/tgrs.2015.2471303.
]Search in Google Scholar
[
Werner, C., Wegmuller, U., Wiesmann, A., and Strozzi, T. (2003). Interferometric Point Target Analysis with JERS-1 Lband SAR data. In IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477), volume 7 of IGARSS-03, pages 4359–4361. IEEE, doi:10.1109/igarss.2003.1295515.
]Search in Google Scholar
[
Wu, J. J., Zhi, Q. Q., and Li, X. (2023). Loop source semiairborne TEM system and its application in landslide detection (in Chinese). Chinese Journal of Geophysics, 66(4):1758–1770, doi:10.6038/cjg2022P0960.
]Search in Google Scholar
[
Yunjun, Z., Fattahi, H., and Amelung, F. (2019). Small baseline InSAR time series analysis: Unwrapping error correction and noise reduction. Computers and Geosciences, 133:104331, doi:10.1016/j.cageo.2019.104331.
]Search in Google Scholar
[
Zhang, L., Dai, K., Deng, J., Ge, D., Liang, R., Li, W., and Xu, Q. (2021). Identifying Potential Landslides by Stacking- InSAR in Southwestern China and Its Performance Comparison with SBAS-InSAR. Remote Sensing, 13(18):3662, doi:10.3390/rs13183662.
]Search in Google Scholar
[
Zhao, C., Dong, Y., Wu, W., Tian, B., Zhou, J., Zhang, P., Gao, S., Yu, Y., and Huang, L. (2023). A Modification to Phase Estimation for Distributed Scatterers in InSAR Data Stacks. Remote Sensing, 15(3):613, doi:10.3390/rs15030613.
]Search in Google Scholar
[
Zhou, C., Cao, Y., Yin, K., Wang, Y., Shi, X., Catani, F., and Ahmed, B. (2020). Landslide Characterization Applying Sentinel-1 Images and InSAR Technique: The Muyubao Landslide in the Three Gorges Reservoir Area, China. Remote Sensing, 12(20):3385, doi:10.3390/rs12203385.
]Search in Google Scholar
Profil Orcid