34 citations as recorded by crossref.

1. Topographic profile and morphology analysis of shallow landslides inside and outside of forests with a semi-automatic mapping approach and bi-temporal airborne laser scanning data L. de Vugt et al. https://doi.org/10.5194/nhess-26-1375-2026
2. An object-based spectral and elevation feature fusion framework for landslide mapping using time-series Landsat-8 imagery T. Wen & T. Teo https://doi.org/10.1080/19475705.2025.2471014
3. An approach to reduce mapping errors in the production of landslide inventory maps M. Santangelo et al. https://doi.org/10.5194/nhess-15-2111-2015
4. Identifying Spatio-Temporal Landslide Hotspots on North Island, New Zealand, by Analyzing Historical and Recent Aerial Photography D. Hölbling et al. https://doi.org/10.3390/geosciences6040048
5. Landslide shape, ellipticity and length‐to‐width ratios F. Taylor et al. https://doi.org/10.1002/esp.4479
6. The influence of the inventory on the determination of the rainfall-induced shallow landslides susceptibility using generalized additive models M. Bordoni et al. https://doi.org/10.1016/j.catena.2020.104630
7. An integrated approach for investigating geomorphic response to extreme events: methodological framework and application to the October 2011 flood in the Magra River catchment, Italy M. Rinaldi et al. https://doi.org/10.1002/esp.3902
8. Semiautomated object-based classification of rain-induced landslides with VHR multispectral images on Madeira Island S. Heleno et al. https://doi.org/10.5194/nhess-16-1035-2016
9. Comparison of Earthquake-Triggered Landslide Inventories: A Case Study of the 2015 Gorkha Earthquake, Nepal S. Meena & S. Tavakkoli Piralilou https://doi.org/10.3390/geosciences9100437
10. Mapping landslide susceptibility using data-driven methods J. Zêzere et al. https://doi.org/10.1016/j.scitotenv.2017.02.188
11. Shallow landslide initiation on terraced slopes: inferences from a physically based approach L. Schilirò et al. https://doi.org/10.1080/19475705.2018.1430066
12. Response of Terraced Slopes to a Very Intense Rainfall Event and Relationships with Land Abandonment: A Case Study from Cinque Terre (Italy) P. Brandolini et al. https://doi.org/10.1002/ldr.2672
13. The influence of geological–morphological and land use settings on shallow landslides in the Pogliaschina T. basin (northern Apennines, Italy) C. Bartelletti et al. https://doi.org/10.1080/17445647.2017.1279082
14. Landslide Inventory Mapping From Bitemporal High-Resolution Remote Sensing Images Using Change Detection and Multiscale Segmentation Z. Lv et al. https://doi.org/10.1109/JSTARS.2018.2803784
15. Influences of the Shadow Inventory on a Landslide Susceptibility Model C. Liu et al. https://doi.org/10.3390/ijgi7090374
16. Visual interpretation of stereoscopic NDVI satellite images to map rainfall-induced landslides F. Fiorucci et al. https://doi.org/10.1007/s10346-018-1069-y
17. Rainfall-Induced Landslide Hazard Assessment Considering Multi-Temporal-Scale Rainfall Factors in Jiangwan Town, Shaoguan, Guangdong Province, China J. Yang et al. https://doi.org/10.3390/geosciences16090352
18. Measures of Spatial Autocorrelation Changes in Multitemporal SAR Images for Event Landslides Detection A. Mondini https://doi.org/10.3390/rs9060554
19. Landslide susceptibility assessment using different rainfall event-based landslide inventories: advantages and limitations S. Oliveira et al. https://doi.org/10.1007/s11069-024-06691-1
20. Landslide Susceptibility Mapping (LSM) in Kelud Volcano Using Spatial Multi-Criteria Evaluation S. Bachri et al. https://doi.org/10.1088/1755-1315/273/1/012014
21. Dynamics of large wood during a flash flood in two mountain catchments A. Lucía et al. https://doi.org/10.5194/nhess-15-1741-2015
22. Developing landslide hazard scenario using the historical events for the Kashmir Himalaya B. Shah et al. https://doi.org/10.1007/s11069-022-05542-1
23. Landslides triggered by an extraordinary rainfall event in Central Italy on September 15, 2022 M. Donnini et al. https://doi.org/10.1007/s10346-023-02109-4
24. Channel response to extreme floods: Insights on controlling factors from six mountain rivers in northern Apennines, Italy N. Surian et al. https://doi.org/10.1016/j.geomorph.2016.02.002
25. Assessing Many Image Processing Products Retrieved from Sentinel-2 Data to Monitor Shallow Landslides in Agricultural Environments R. Cavalli et al. https://doi.org/10.3390/rs16132286
26. Databases in geohazard science: An introduction M. Klose et al. https://doi.org/10.1016/j.geomorph.2015.06.029
27. Factors controlling the formation and movement of clustered shallow landslides triggered by the extreme rainstorm in July 2023 in Beijing, China H. Ma & F. Wang https://doi.org/10.1016/j.geomorph.2025.109728
28. Separating Landslide Source and Runout Signatures with Topographic Attributes and Data Mining to Increase the Quality of Landslide Inventory J. Lai https://doi.org/10.3390/app10196652
29. Upper limits of flash flood stream power in Europe L. Marchi et al. https://doi.org/10.1016/j.geomorph.2015.11.005
30. Retrospective evaluation of landslide susceptibility maps and review of validation practice P. Fleuchaus et al. https://doi.org/10.1007/s12665-021-09770-9
31. Characteristics of landslides and assessment of deep-seated landslide susceptibility in Northern Turkey T. Duman & T. Çan https://doi.org/10.1007/s42990-023-00105-3
32. Terrain visibility impact on the preparation of landslide inventories: a practical example in Darjeeling district (India) T. Bornaetxea et al. https://doi.org/10.5194/nhess-22-2929-2022
33. Hydrometeorological Characterization of a Flash Flood Associated with Major Geomorphic Effects: Assessment of Peak Discharge Uncertainties and Analysis of the Runoff Response W. Amponsah et al. https://doi.org/10.1175/JHM-D-16-0081.1
34. How to better link landslide inventory mapping with loss and damage reporting D. Urueña et al. https://doi.org/10.1016/j.ijdrr.2026.106242