[1] Li S, Yang X. Sentinel-1 InSAR-derived land subsidence assessment along the Texas Gulf Coast. Geomat Nat Hazards Risk. 2023;14(1):1245-63. doi: 10.1016/j.jngse.2023.105209
[2] Crosetto M, Monserrat O, Cuevas-González M, Devanthéry N, Crippa B. Interferometric SAR monitoring of land subsidence: Persistent scatterer vs distributed scatterer techniques. Remote Sens. 2016;8(6):1-22.
doi: 10.5194/isprsarchives-XLI-B7-835-2016
[3] Ferretti A, Prati C, Rocca F. Permanent scatterers in SAR interferometry. IEEE Trans Geosci Remote Sens. 2001;39(1):8-20. doi: 10.1109/36.898661
[4] Li Z, Elliott JR, Hooper A. Integration of GPS and InSAR data for resolving 3D crustal deformation. Earth Space Sci. 2019;6(5):856-75. doi: 10.1029/2019EA001036
[5] Wang HM, Wang Y, Jiao X, Qian GR. Risk management of land subsidence in Shanghai. Desalination Water Treat. 2014;52(4-6):1122-9. doi: 10.1080/19443994.2013.826337
[6] Bamler R, Hartl P. Synthetic aperture radar interferometry. Inverse Probl. 1998;14(4):R1-54.
doi: 10.1088/0266-5611/14/4/001
[7] Liu Y, Ma T, Du Y. Compaction of muddy sediment and its significance to groundwater chemistry. Procedia Earth Planet Sci. 2017;17:392-5. doi: 10.1016/j.proeps.2016.12.099
[8] Gambolati G, Teatini P. Geomechanics of subsurface water withdrawal and injection. Water Resour Res. 2015;51(6):3922-55. doi: 10.1002/2014WR016841
[9] Solari L, Rosi A, Bianchini S, Casagli N, Raspini F. SAR interferometry for monitoring ground displacements in mountain regions. Earth Surf Process Landf. 2019;44(1):58-76. doi: 10.1002/esp.4470
[10] Jin YF, Yin ZY, Wu ZX, Zhou WH. Identifying parameters of easily crushable sand and application to offshore pile driving. Ocean Eng. 2018;154:416-29.
doi: 10.1016/j.oceaneng.2018.01.023
[11] Jin YF, Yin ZY, Shen SL, Hicher PY. Selection of sand models and identification of parameters using an enhanced genetic algorithm. Int J Numer Anal Methods Geomech. 2016; 40(8):1219-40. doi: 10.1002/nag.2487
[12] Bendarzsevszkij A, Eszterhai V, Gere L, Klemensits P, Polyák E. World Economic Forum. Environ Sci Pollut Res. 2017.
doi: 10.1007/s11356-024-32075-w
[13] Goudarzi M, Farahpour M, Mousavi SA. Use of Landsat TM digital data in land cover mapping and rangeland condition classification: A case study of Namrood watershed. Iran J Range Desert Res. 2006;13(3):265-77. [In Persian]
[14] Hooper A, Bekaert D, Spaans K, Arıkan M. Recent advances in SAR interferometry time series analysis for measuring crustal deformation. Tectonophysics. 2012;514-517:1-13.
doi: 10.1016/j.tecto.2011.10.013
[15] Raspini F, Bianchini S, Moretti S. Exploitation of satellite SAR data for the detection and monitoring of slow-moving landslides. Remote Sens. 2018;10(7):1121.
doi: 10.3390/rs10071121
[16] Zhang L, Wang S, Wei Y. Integration of differential InSAR and optical data for land surface deformation analysis in Enshi City, China. Front Earth Sci. 2023; 11:1101848.
doi: 10.3389/feart.2023.1101848
[17] Bonforte A, et al. Present-day surface deformation of Sicily derived from Sentinel-1 InSAR time-series. arXiv. 2022. doi: 10.48550/arXiv.2208.08183
[18] Chen C, et al. Deep learning framework for detecting ground deformation in the built environment using satellite InSAR data. arXiv. 2020. doi: 10.48550/arXiv.2005.03221
[19] Cao X, He K, Hu X, Luo G, Zhou Y, Zhou R, et al. Combined InSAR and optical dataset unravelling the characteristics of hillslope erosion in burned areas in Xichang, China. Catena. 2024; 244:108123. doi: 10.1016/j.catena.2024.108123
[20] Yu W, Li W, Wu Z, Lu H, Xu Z, Wang D, et al. Integrated remote sensing investigation of suspected landslides: A case study of the Genie Slope on the Tibetan Plateau, China. Remote Sens. 2024;16(13):2412. doi: 10.3390/rs16132412
[21] Chen H, Zhao C, Tomás R, Reyes-Carmona C, Kang Y. Integrating InSAR and non-rigid optical pixel offsets to explore the kinematic behaviors of the Lanuza complex landslide. Remote Sens Environ. 2025; 320:114651.
doi: 10.1016/j.rse.2025.114651
[22] Handwerger AL, Lacroix P, Bell AF, Booth AM, Huang MH, Mudd SM, et al. Multi-sensor remote sensing captures geometry and slow-to-fast sliding transition of the 2017 Mud Creek landslide. Sci Rep. 2025; 15:29831.
doi: 10.1038/s41598-025-11399-8
[23] Hanssen RF. Radar interferometry: Data interpretation and error analysis. Dordrecht: Springer; 2001.
doi: 10.1007/0-306-47633-9
[24] Liang D, Guo H, Zhang L, Cheng Y, Zhu Q, Liu XT. Time-series snowmelt detection over the Antarctic using Sentinel-1 SAR images on Google Earth Engine. Remote Sens Environ. 2021; 264:112318. doi: 10.1016/j.rse.2021.112318
[25] Li J, Li ZW, Ding XL, Wang QJ, Zhu JJ, Wang CC. Investigating mountain glacier motion with the method of SAR intensity-tracking: Removal of topographic effects and analysis of the dynamic patterns. Earth-Sci Rev. 2014;138(1):179-95.
doi: 10.1016/j.earscirev.2014.08.016
[26] Zhang Y, Handwerger AL, Fielding EJ, Huang M. Integrating InSAR and non-rigid optical pixel offsets to explore the Lanuza landslide. Remote Sens Environ. 2025; 305:113689.
doi: 10.1016/j.rse.2024.113689
[27] Liu Y, Ma T, Du Y. Compaction of muddy sediment and its significance to groundwater chemistry. Procedia Earth Planet Sci. 2017; 17:392-5. doi: 10.1016/j.proeps.2016.12.099
[28] Mousavi Z, Dehghani M, Sahebi MR. Monitoring land subsidence in the arid region of Mashhad, northeast Iran, using SBAS InSAR technique. J Arid Environ. 2020; 174:104045. [In Persian] doi: 10.1016/j.jaridenv.2019.104045
[29] Karimi N, Namdari S. Estimation of severity and extent of desertification in Iran using Landsat satellite images and spectral mixture analyses methods during 1984 and 2015. Iran J Range Desert Res. 2019;26(2):500-15. [In Persian]
doi: 10.22092/ijrdr.2019.119369
[30] Raspini F, Bianchini S, Moretti S. Exploitation of satellite SAR data for the detection and monitoring of slow-moving landslides. Remote Sens. 2018;10(7):1121.
doi: 10.3390/rs10071121
[31] Wang H, Li T, Chen Q, Zhao Z. Monitoring land subsidence in the Yangtze River Delta using Sentinel-1 data: Implications for urban infrastructure. GISci Remote Sens. 2025;62(1):101-19. doi: 10.1080/15481603.2025.2465349
[32] Ye S, Xue Y, Wu J, Yan X, Yu J. Progression and mitigation of land subsidence in China. Hydrogeol J. 2016;24(3):685-93.
doi: 10.1007/s10040-015-1356-9
[33] Jin YF, Yin ZY, Wu ZX, Zhou WH. Identifying parameters of easily crushable sand and application to offshore pile driving. Ocean Eng. 2018; 154:416-29.
doi: 10.1016/j.oceaneng.2018.01.023
[34] Pereira MA, Silva J, Santos FD. Integration of optical and SAR data for burned area mapping in Portugal. Remote Sens. 2015;7(2):1320-42. doi: 10.3390/rs70201320
[35] Massonnet D, Feigl KL. Radar interferometry and its application to changes in the Earth's surface. Rev Geophys. 1998;36(4):441-500. doi: 10.1029/97RG03139
[36] Zhang L, Wang S, Wei Y. Integration of differential InSAR and optical data for land surface deformation analysis in Enshi City, China. Front Earth Sci. 2023; 11:1101848.
doi: 10.3389/feart.2023.1101848
[37] Schmidt DA, Bürgmann R. Time-dependent land subsidence and uplift near the California-Nevada border observed by GPS and InSAR. J Geophys Res Solid Earth. 2019;124(8):8707-23.
doi: 10.1029/2019JB017354
[38] Shirzaei M, et al. Land subsidence risk to infrastructure in US metropolises. Nat Cities. 2025. [In Persian]
doi: 10.1038/s44284-025-00240-y
[39] Figueroa-Miranda S, Tuxpan-Vargas J, Ramos-Leal JA, Hernández-Madrigal VM, Villaseñor-Reyes CI. Land subsidence by groundwater over-exploitation from aquifers in tectonic valleys of Central Mexico: A review. Eng Geol. 2018;246:91-106. doi: 10.1016/j.enggeo.2018.09.023
[40] Duo L, Hu Z. Soil quality change after reclaiming subsidence land with Yellow River sediments. Sustainability. 2018;10(11):4310. doi: 10.3390/su10114310
[41] Wang Y, Zhang H, Wang Z. Integration of optical, SAR and DEM data for automated detection of debris-covered glaciers. ISPRS J Photogramm Remote Sens. 2021; 180:149-62.
doi: 10.1016/j.isprsjprs.2021.08.005
[42] Ganas A, Elias P, Bozionelos G, Papathanassiou G, Avallone A, Papastergios A, et al. Sentinel-1 reveals ground deformation patterns associated with the August 2016 earthquake sequence in Central Italy. Remote Sens. 2018;10(6):894.
doi: 10.3390/app12052630
[43] Hooper A, Bekaert D, Spaans K, Arıkan M. Recent advances in SAR interferometry time series analysis for measuring crustal deformation. Tectonophysics. 2012;514-517:1-13.
doi: 10.1016/j.tecto.2011.10.013
[44] Zhao P, Lu D, Wang G, Wu C, Huang Y, Yu S. Examining spectral reflectance saturation in Landsat imagery and corresponding solutions to improve forest aboveground biomass estimation. Remote Sens. 2016;8(6):469.
doi: 10.3390/rs8060469a