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All issues Volume 600 (2024) E3S Web Conf., 600 (2024) 02003 References
Open Access
Issue
E3S Web Conf.
Volume 600, 2024
The 6th International Geography Seminar (IGEOS 2023)
Article Number 02003
Number of page(s) 12
Section Geography and Disaster Mitigation Education
DOI https://doi.org/10.1051/e3sconf/202460002003
Published online 29 November 2024
  1. H. Sun, W. Li, M. Scaioni, J. Fu, X. Guo, and J. Gao, “Influence of spatial heterogeneity on landslide susceptibility in the transboundary area of the Himalayas,” Geomorphology, vol. 433, no. May, p. 108723, (2023), doi: 10.1016/j.geomorph.2023.108723. [CrossRef] [Google Scholar]
  2. A. Arrasyid, R., Ihsan, H. M., Darsiharjo., Ruhimat, M., Pratama, “Suitability Evaluation of Land Use / Land Cover ( LULC ) Towards Landslide Prone Areas in Structural and Volcano Landform,” vol. 19, no. 6, pp. 61–75, (2023). [Google Scholar]
  3. K. Dai et al., “Monitoring activity at the Daguangbao mega-landslide (China) using Sentinel-1 TOPS time series interferometry,” Remote Sens. Environ., vol. 186, pp. 501–513, 2016, doi: 10.1016/j.rse.2016.09.009. [CrossRef] [Google Scholar]
  4. X. Liu et al., “Integration of Sentinel-1 and ALOS/PALSAR-2 SAR datasets for mapping active landslides along the Jinsha River corridor, China,” Eng. Geol., vol. 284, no. February, p. 106033, (2021), doi: 10.1016/j.enggeo.2021.106033. [CrossRef] [Google Scholar]
  5. H. Shankar, D. Singh, and P. Chauhan, “Landslide deformation and temporal prediction of slope failure in Himalayan terrain using PSInSAR and Sentinel-1 data,” Adv. Sp. Res., vol. 70, no. 12, pp. 3917–3931, (2022), doi: 10.1016/j.asr.2022.04.062. [CrossRef] [Google Scholar]
  6. M. Santangelo, M. Cardinali, F. Bucci, F. Fiorucci, and A. C. Mondini, “Exploring event landslide mapping using Sentinel-1 SAR backscatter products,” Geomorphology, vol. 397, p. 108021, (2022), doi: 10.1016/j.geomorph.2021.108021. [CrossRef] [Google Scholar]
  7. T. Zhang et al., “Detection of active landslides in southwest China using sentinel-1 and ALOS-2 data,” Procedia Comput. Sci., vol. 181, no. (2019), pp. 1138–1145, 2021, doi: 10.1016/j.procs.2021.01.311. [CrossRef] [Google Scholar]
  8. K. C. Niraj, S. K. Gupta, and D. P. Shukla, “Kotrupi landslide deformation study in non-urban area using DInSAR and MTInSAR techniques on Sentinel-1 SAR data,” Adv. Sp. Res., vol. 70, no. 12, pp. 3878–3891, (2022), doi: 10.1016/j.asr.2021.11.042. [CrossRef] [Google Scholar]
  9. Q. Xu et al., “Remote sensing for landslide investigations: A progress report from China,” Eng. Geol., vol. 321, no. August 2022, p. 107156, (2023), doi: 10.1016/j.enggeo.2023.107156. [CrossRef] [Google Scholar]
  10. D. K. Dwivedi, A. K. Saraf, and J. D. Das, “Geoinformatics-based investigation of slope failure and landslide damming of chenab river, lahaul-spiti, Himachal Pradesh, India,” Nat. Hazards Res., vol. 3, no. 2, pp. 186–195, (2023), doi: 10.1016/j.nhres.2023.02.008. [CrossRef] [Google Scholar]
  11. B. Li, W. Jiang, Y. Li, Y. Luo, Q. Jiao, and Q. Zhang, “ScienceDirect Monitoring and analysis of Woda landslide ( China ) using InSAR and Sentinel-1 data,” Adv. Sp. Res., no. xxxx, pp. 1–14, (2023), doi: 10.1016/j.asr.2023.04.055. [Google Scholar]
  12. H. M. Ihsan and S. S. Sahid, “Vertikal Accuracy Assessment On Sentinel-1, Alos Palsar, And Demnas In The Ciater Basin,” J. Geogr. Gea, vol. 21, no. 1, pp. 16–25, 2021, doi: 10.17509/gea.v21i1.29931. [Google Scholar]
  13. J. Das, P. Saha, R. Mitra, A. Alam, and M. Kamruzzaman, “GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India,” Heliyon, vol. 9, no. 5, p. e16186, (2023), doi: 10.1016/j.heliyon.2023.e16186. [CrossRef] [PubMed] [Google Scholar]
  14. A. A. A. Rahman, N. Abd Majid, N. Adhalysha Ahli, A. Sharifuddin Ab Latip, and A. Mohd Taib, “The capability of SNAP software application to identify landslide using InSAR technique,” Phys. Chem. Earth, vol. 131, no. (August 2022), p. 103427, 2023, doi: 10.1016/j.pce.2023.103427. [CrossRef] [Google Scholar]
  15. L. Bragagnolo, R. V. da Silva, and J. M. V. Grzybowski, “Landslide susceptibility mapping with r.landslide: A free open-source GIS-integrated tool based on Artificial Neural Networks,” Environ. Model. Softw., vol. 123, no. (October 2019), p. 104565, 2020, doi: 10.1016/j.envsoft.2019.104565. [CrossRef] [Google Scholar]
  16. Y. Wang et al., “Automatic detection and update of landslide inventory before and after impoundments at the Lianghekou reservoir using Sentinel-1 InSAR,” Int. J. Appl. Earth Obs. Geoinf., vol. 118, no. February, p. 103224, (2023), doi: 10.1016/j.jag.2023.103224. [Google Scholar]
  17. V. E. Nwazelibe, C. O. Unigwe, and J. C. Egbueri, “Testing the performances of different fuzzy overlay methods in GIS-based landslide susceptibility mapping of Udi Province, SE Nigeria,” Catena, vol. 220, no. PA, p. 106654, (2023), doi: 10.1016/j.catena.2022.106654. [CrossRef] [Google Scholar]
  18. N. Abbas, S. Afsar, B. Jan, E. A. Sayla, and F. Nawaz, “GIS based model for the landslides risk assessment. A case study in Hunza-Nagar settlements, Gilgit-Baltistan, Pakistan,” Environ. Challenges, vol. 7, no. February, p. 100487, (2022), doi: 10.1016/j.envc.2022.100487. [CrossRef] [Google Scholar]
  19. P. K. Rawat and D. B. Pant, “Geo-Ecological GIS Development to Investigate Landslides and Slope Instability Along Frontal Zone of Central Himalaya,” SSRN Electron. J., vol. 3, no. 2, pp. 196–204, (2022), doi: 10.2139/ssrn.4251397. [Google Scholar]
  20. D. Asmare, “Landslide hazard zonation and evaluation around Debre Markos town, NW Ethiopia—a GIS-based bivariate statistical approach,” Sci. African, vol. 15, p. e01129, (2022), doi: 10.1016/j.sciaf.2022.e01129. [Google Scholar]
  21. B. Zhao, Q. Dai, L. Zhuo, S. Zhu, Q. Shen, and D. Han, “Assessing the potential of different satellite soil moisture products in landslide hazard assessment,” Remote Sens. Environ., vol. 264, no. June, p. 112583, (2021), doi: 10.1016/j.rse.2021.112583. [CrossRef] [Google Scholar]
  22. A. A. Mekonnen, T. K. Raghuvanshi, K. V. Suryabhagavan, and T. Kassawmar, “GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia,” Environ. Challenges, vol. 8, no. July, p. 100586, (2022), doi: 10.1016/j.envc.2022.100586. [CrossRef] [Google Scholar]
  23. I. Sonker, J. N. Tripathi, and A. K. Singh, “Landslide susceptibility zonation using geospatial technique and analytical hierarchy process in Sikkim Himalaya,” Quat. Sci. Adv., vol. 4, p. 100039, (2021), doi: 10.1016/j.qsa.2021.100039. [CrossRef] [Google Scholar]
  24. J. Efiong, D. I. Eni, J. N. Obiefuna, and S. J. Etu, “Geospatial modelling of landslide susceptibility in Cross River State of Nigeria,” Sci. African, vol. 14, (2021), doi: 10.1016/j.sciaf.2021.e01032. [Google Scholar]
  25. T. Arumugam, S. Kinattinkara, S. Velusamy, M. Shanmugamoorthy, and S. Murugan, “GIS based landslide susceptibility mapping and assessment using weighted overlay method in Wayanad: A part of Western Ghats, Kerala,” Urban Clim., vol. 49, no. December 2022, p. 101508, (2023), doi: 10.1016/j.uclim.2023.101508. [CrossRef] [Google Scholar]
  26. Ihsan, H. M., Astari, A. J., Bratanegara, A. S., Aliyan, S. A. and Wulandari, E. P. “The Comparison of Spatial Models in Peak Ground Acceleration (PGA) Study,” Int. J. Geoinformatics, vol. 17, no. 6, pp. 27–33, (2021), doi: 10.52939/ijg.v17i6.2061. [Google Scholar]

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