These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
132 related articles for article (PubMed ID: 38387570)
21. Role of landslides on the volume balance of the Nepal 2015 earthquake sequence. Valagussa A; Frattini P; Valbuzzi E; Crosta GB Sci Rep; 2021 Feb; 11(1):3434. PubMed ID: 33564079 [TBL] [Abstract][Full Text] [Related]
22. Seismic landslide susceptibility assessment using principal component analysis and support vector machine. Xu Z; Che A; Zhou H Sci Rep; 2024 Feb; 14(1):3734. PubMed ID: 38355620 [TBL] [Abstract][Full Text] [Related]
23. Framework for rainfall-triggered landslide-prone critical infrastructure zonation. Gnyawali K; Dahal K; Talchabhadel R; Nirandjan S Sci Total Environ; 2023 May; 872():162242. PubMed ID: 36804983 [TBL] [Abstract][Full Text] [Related]
24. Hybrid machine learning approach for landslide prediction, Uttarakhand, India. Kainthura P; Sharma N Sci Rep; 2022 Nov; 12(1):20101. PubMed ID: 36418362 [TBL] [Abstract][Full Text] [Related]
25. Investigation of landslide detection using radial basis functions: a case study of the Taşkent landslide, Turkey. Zeybek M; Şanlıoğlu İ Environ Monit Assess; 2020 Mar; 192(4):230. PubMed ID: 32166522 [TBL] [Abstract][Full Text] [Related]
26. Increase in landslide activity after a low-magnitude earthquake as inferred from DInSAR interferometry. Martino S; Fiorucci M; Marmoni GM; Casaburi L; Antonielli B; Mazzanti P Sci Rep; 2022 Feb; 12(1):2686. PubMed ID: 35177659 [TBL] [Abstract][Full Text] [Related]
27. A Deep-Learning-Based Algorithm for Landslide Detection over Wide Areas Using InSAR Images Considering Topographic Features. Li N; Feng G; Zhao Y; Xiong Z; He L; Wang X; Wang W; An Q Sensors (Basel); 2024 Jul; 24(14):. PubMed ID: 39065981 [TBL] [Abstract][Full Text] [Related]
28. GIS-based data-driven bivariate statistical models for landslide susceptibility prediction in Upper Tista Basin, India. Das J; Saha P; Mitra R; Alam A; Kamruzzaman M Heliyon; 2023 May; 9(5):e16186. PubMed ID: 37234665 [TBL] [Abstract][Full Text] [Related]
29. Land use change and landslide characteristics analysis for community-based disaster mitigation. Chen CY; Huang WL Environ Monit Assess; 2013 May; 185(5):4125-39. PubMed ID: 22961329 [TBL] [Abstract][Full Text] [Related]
30. Convolutional neural network (CNN) with metaheuristic optimization algorithms for landslide susceptibility mapping in Icheon, South Korea. Hakim WL; Rezaie F; Nur AS; Panahi M; Khosravi K; Lee CW; Lee S J Environ Manage; 2022 Mar; 305():114367. PubMed ID: 34968941 [TBL] [Abstract][Full Text] [Related]
31. An ensemble learning-based experimental framework for smart landslide detection, monitoring, prediction, and warning in IoT-cloud environment. Sharma A; Mohana R; Kukkar A; Chodha V; Bansal P Environ Sci Pollut Res Int; 2023 Dec; 30(58):122677-122699. PubMed ID: 37971588 [TBL] [Abstract][Full Text] [Related]
32. Effects of land-use changes on landslides in a landslide-prone area (Ardesen, Rize, NE Turkey). Karsli F; Atasoy M; Yalcin A; Reis S; Demir O; Gokceoglu C Environ Monit Assess; 2009 Sep; 156(1-4):241-55. PubMed ID: 18780152 [TBL] [Abstract][Full Text] [Related]
33. Analysis of the spatial distribution of the landslides triggered by the 1923 Great Kanto Earthquake, Japan. Endo R; Iwahashi J Proc Jpn Acad Ser B Phys Biol Sci; 2024 Feb; 100(2):123-139. PubMed ID: 38171809 [TBL] [Abstract][Full Text] [Related]
34. Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China). Wang Y; Sun D; Wen H; Zhang H; Zhang F Int J Environ Res Public Health; 2020 Jun; 17(12):. PubMed ID: 32545618 [TBL] [Abstract][Full Text] [Related]
35. A hybrid machine learning model for landslide-oriented risk assessment of long-distance pipelines. Wen H; Liu L; Zhang J; Hu J; Huang X J Environ Manage; 2023 Sep; 342():118177. PubMed ID: 37210819 [TBL] [Abstract][Full Text] [Related]
36. Landslide Susceptibility Evaluation Based on Potential Disaster Identification and Ensemble Learning. Wang X; Zhang X; Bi J; Zhang X; Deng S; Liu Z; Wang L; Guo H Int J Environ Res Public Health; 2022 Oct; 19(21):. PubMed ID: 36361127 [TBL] [Abstract][Full Text] [Related]
37. Using archaeological and geomorphological evidence for the establishment of a relative chronology and evolution pattern for Holocene landslides. Niculiţă M; Mărgărint MC; Cristea AI PLoS One; 2019; 14(12):e0227335. PubMed ID: 31891649 [TBL] [Abstract][Full Text] [Related]
38. Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics. Pokharel B; Alvioli M; Lim S Sci Rep; 2021 Oct; 11(1):21333. PubMed ID: 34716368 [TBL] [Abstract][Full Text] [Related]
39. Enhancing co-seismic landslide susceptibility, building exposure, and risk analysis through machine learning. Pyakurel A; K C D; Dahal BK Sci Rep; 2024 Mar; 14(1):5902. PubMed ID: 38467642 [TBL] [Abstract][Full Text] [Related]
40. Slide type landslide susceptibility assessment of the Büyük Menderes watershed using artificial neural network method. Tekin S; Çan T Environ Sci Pollut Res Int; 2022 Jul; 29(31):47174-47188. PubMed ID: 35178630 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]