177 related articles for article (PubMed ID: 36849465)
1. SBAS-InSAR based validated landslide susceptibility mapping along the Karakoram Highway: a case study of Gilgit-Baltistan, Pakistan.
Kulsoom I; Hua W; Hussain S; Chen Q; Khan G; Shihao D
Sci Rep; 2023 Feb; 13(1):3344. PubMed ID: 36849465
[TBL] [Abstract][Full Text] [Related]
2. Landslide Susceptibility Mapping Using Machine Learning Algorithm Validated by Persistent Scatterer In-SAR Technique.
Hussain MA; Chen Z; Zheng Y; Shoaib M; Shah SU; Ali N; Afzal Z
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590807
[TBL] [Abstract][Full Text] [Related]
3. Landslide Susceptibility Mapping of Karakorum Highway Combined with the Application of SBAS-InSAR Technology.
Zhao F; Meng X; Zhang Y; Chen G; Su X; Yue D
Sensors (Basel); 2019 Jun; 19(12):. PubMed ID: 31207868
[TBL] [Abstract][Full Text] [Related]
4. Landslide Susceptibility Mapping with Integrated SBAS-InSAR Technique: A Case Study of Dongchuan District, Yunnan (China).
Zhu Z; Gan S; Yuan X; Zhang J
Sensors (Basel); 2022 Jul; 22(15):. PubMed ID: 35898090
[TBL] [Abstract][Full Text] [Related]
5. Landslide detection and inventory updating using the time-series InSAR approach along the Karakoram Highway, Northern Pakistan.
Hussain S; Pan B; Afzal Z; Ali M; Zhang X; Shi X; Ali M
Sci Rep; 2023 May; 13(1):7485. PubMed ID: 37161025
[TBL] [Abstract][Full Text] [Related]
6. Combined SBAS-InSAR and PSO-RF Algorithm for Evaluating the Susceptibility Prediction of Landslide in Complex Mountainous Area: A Case Study of Ludian County, China.
Xiao B; Zhao J; Li D; Zhao Z; Zhou D; Xi W; Li Y
Sensors (Basel); 2022 Oct; 22(20):. PubMed ID: 36298394
[TBL] [Abstract][Full Text] [Related]
7. Detection and analysis of potential landslides based on SBAS-InSAR technology in alpine canyon region.
Li Y; Feng X; Li Y; Jiang W; Yu W
Environ Sci Pollut Res Int; 2024 Jan; 31(4):6492-6510. PubMed ID: 38151559
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Dynamic landslide susceptibility mapping based on the PS-InSAR deformation intensity.
Jin B; Zeng T; Yin K; Gui L; Guo Z; Wang T
Environ Sci Pollut Res Int; 2024 Jan; 31(5):7872-7888. PubMed ID: 38170358
[TBL] [Abstract][Full Text] [Related]
10. Identifying the essential influencing factors of landslide susceptibility models based on hybrid-optimized machine learning with different grid resolutions: a case of Sino-Pakistani Karakorum Highway.
Wu J; Zhang Y; Yang L; Zhang Y; Lei J; Zhi M; Ma G
Environ Sci Pollut Res Int; 2023 Sep; 30(45):100675-100700. PubMed ID: 37639095
[TBL] [Abstract][Full Text] [Related]
11. Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China.
Wang Y; Wu X; Chen Z; Ren F; Feng L; Du Q
Int J Environ Res Public Health; 2019 Jan; 16(3):. PubMed ID: 30696105
[TBL] [Abstract][Full Text] [Related]
12. Landslide Monitoring along the Dadu River in Sichuan Based on Sentinel-1 Multi-Temporal InSAR.
Huang H; Ju S; Duan W; Jiang D; Gao Z; Liu H
Sensors (Basel); 2023 Mar; 23(7):. PubMed ID: 37050447
[TBL] [Abstract][Full Text] [Related]
13. Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan.
Dou J; Yunus AP; Tien Bui D; Merghadi A; Sahana M; Zhu Z; Chen CW; Khosravi K; Yang Y; Pham BT
Sci Total Environ; 2019 Apr; 662():332-346. PubMed ID: 30690368
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. GIS-based landslide susceptibility mapping in the Longmen Mountain area (China) using three different machine learning algorithms and their comparison.
Huang Z; Peng L; Li S; Liu Y; Zhou S
Environ Sci Pollut Res Int; 2023 Aug; 30(38):88612-88626. PubMed ID: 37440134
[TBL] [Abstract][Full Text] [Related]
16. Research on Time Series Monitoring of Surface Deformation in Tongliao Urban Area Based on SBAS-PS-DS-InSAR.
Chen Y; Ding C; Huang P; Yin B; Tan W; Qi Y; Xu W; Du S
Sensors (Basel); 2024 Feb; 24(4):. PubMed ID: 38400328
[TBL] [Abstract][Full Text] [Related]
17. Selecting optimal conditioning parameters for landslide susceptibility: an experimental research on Aqabat Al-Sulbat, Saudi Arabia.
Alqadhi S; Mallick J; Talukdar S; Bindajam AA; Van Hong N; Saha TK
Environ Sci Pollut Res Int; 2022 Jan; 29(3):3743-3762. PubMed ID: 34389958
[TBL] [Abstract][Full Text] [Related]
18. A novel evolutionary combination of artificial intelligence algorithm and machine learning for landslide susceptibility mapping in the west of Iran.
Shen Y; Ahmadi Dehrashid A; Bahar RA; Moayedi H; Nasrollahizadeh B
Environ Sci Pollut Res Int; 2023 Dec; 30(59):123527-123555. PubMed ID: 37987977
[TBL] [Abstract][Full Text] [Related]
19. InSAR-based landslide hazard mapping and identification of at-risk infrastructures in a selected district of North Shewa Zone, Ethiopia.
Melkamu T; Bagyaraj M; Adimaw M; Berihun A
Environ Sci Pollut Res Int; 2024 May; 31(22):32553-32570. PubMed ID: 38658507
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]
