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)
1. Identifying recurrent and persistent landslides using satellite imagery and deep learning: A 30-year analysis of the Himalaya. Chen TK; Kincey ME; Rosser NJ; Seto KC Sci Total Environ; 2024 Apr; 922():171161. PubMed ID: 38387570 [TBL] [Abstract][Full Text] [Related]
2. Discovering Vegetation Recovery and Landslide Activities in the Wenchuan Earthquake Area with Landsat Imagery. Zhong C; Li C; Gao P; Li H Sensors (Basel); 2021 Aug; 21(15):. PubMed ID: 34372479 [TBL] [Abstract][Full Text] [Related]
3. Exploitation of optical and SAR amplitude imagery for landslide identification: a case study from Sikkim, Northeast India. Sivasankar T; Ghosh S; Joshi M Environ Monit Assess; 2021 Jun; 193(7):386. PubMed ID: 34091764 [TBL] [Abstract][Full Text] [Related]
4. Generating multi-temporal landslide inventories through a general deep transfer learning strategy using HR EO data. Bhuyan K; Tanyaş H; Nava L; Puliero S; Meena SR; Floris M; van Westen C; Catani F Sci Rep; 2023 Jan; 13(1):162. PubMed ID: 36599911 [TBL] [Abstract][Full Text] [Related]
5. Spatial prediction of landslide susceptibility in parts of Garhwal Himalaya, India, using the weight of evidence modelling. Guri PK; Ray PK; Patel RC Environ Monit Assess; 2015 Jun; 187(6):324. PubMed ID: 25944750 [TBL] [Abstract][Full Text] [Related]
6. Spatio-temporal landslide inventory and susceptibility assessment using Sentinel-2 in the Himalayan mountainous region of Pakistan. Bacha AS; Shafique M; van der Werff H; van der Meijde M; Hussain ML; Wahid S Environ Monit Assess; 2022 Sep; 194(11):845. PubMed ID: 36175580 [TBL] [Abstract][Full Text] [Related]
7. Evaluation of landslides susceptibility in Southeastern Tibet considering seismic sensitivity. Yeqi Z; Yonggang G; Guowen W; Shengjie W Heliyon; 2024 Sep; 10(18):e36800. PubMed ID: 39309935 [TBL] [Abstract][Full Text] [Related]
8. SAR and optical images correlation illuminates post-seismic landslide motion after the Mw 7.8 Gorkha earthquake (Nepal). Lacroix P; Gavillon T; Bouchant C; Lavé J; Mugnier JL; Dhungel S; Vernier F Sci Rep; 2022 Apr; 12(1):6266. PubMed ID: 35428776 [TBL] [Abstract][Full Text] [Related]
9. Detecting landslide-dammed lakes on Sentinel-2 imagery and monitoring their spatio-temporal evolution following the Kaikōura earthquake in New Zealand. Abad L; Hölbling D; Spiekermann R; Prasicek G; Dabiri Z; Argentin AL Sci Total Environ; 2022 May; 820():153335. PubMed ID: 35077801 [TBL] [Abstract][Full Text] [Related]
11. Evaluating the influence of road construction on landslide susceptibility in Saudi Arabia's mountainous terrain: a Bayesian-optimised deep learning approach with attention mechanism and sensitivity analysis. Alqadhi S; Mallick J; Hang HT; Al Asmari AFS; Kumari R Environ Sci Pollut Res Int; 2024 Jan; 31(2):3169-3194. PubMed ID: 38082044 [TBL] [Abstract][Full Text] [Related]
12. A new strategy to map landslides with a generalized convolutional neural network. Prakash N; Manconi A; Loew S Sci Rep; 2021 May; 11(1):9722. PubMed ID: 33958656 [TBL] [Abstract][Full Text] [Related]
13. Exploring machine learning and statistical approach techniques for landslide susceptibility mapping in Siwalik Himalayan Region using geospatial technology. Saha A; Tripathi L; Villuri VGK; Bhardwaj A Environ Sci Pollut Res Int; 2024 Feb; 31(7):10443-10459. PubMed ID: 38198087 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. Game-theoretic optimization of landslide susceptibility mapping: a comparative study between Bayesian-optimized basic neural network and new generation neural network models. Mallick J; Alkahtani M; Hang HT; Singh CK Environ Sci Pollut Res Int; 2024 Apr; 31(20):29811-29835. PubMed ID: 38592629 [TBL] [Abstract][Full Text] [Related]
16. Development of landslide susceptibility maps of Tripura, India using GIS and analytical hierarchy process (AHP). Nath NK; Gautam VK; Pande CB; Mishra LR; Raju JT; Moharir KN; Rane NL Environ Sci Pollut Res Int; 2024 Jan; 31(5):7481-7497. PubMed ID: 38159190 [TBL] [Abstract][Full Text] [Related]
17. 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]
18. Automated Landslide-Risk Prediction Using Web GIS and Machine Learning Models. Tengtrairat N; Woo WL; Parathai P; Aryupong C; Jitsangiam P; Rinchumphu D Sensors (Basel); 2021 Jul; 21(13):. PubMed ID: 34283153 [TBL] [Abstract][Full Text] [Related]
19. The dynamic threat from landslides following large continental earthquakes. Arrell K; Rosser NJ; Kincey ME; Robinson TR; Horton P; Densmore AL; Oven KJ; Shrestha R; Pujara DS PLoS One; 2024; 19(8):e0308444. PubMed ID: 39167597 [TBL] [Abstract][Full Text] [Related]
20. 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] [Next] [New Search]