Ashok Dahal

600 total citations
25 papers, 309 citations indexed

About

Ashok Dahal is a scholar working on Management, Monitoring, Policy and Law, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Ashok Dahal has authored 25 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Management, Monitoring, Policy and Law, 11 papers in Global and Planetary Change and 8 papers in Atmospheric Science. Recurrent topics in Ashok Dahal's work include Landslides and related hazards (20 papers), Flood Risk Assessment and Management (10 papers) and Cryospheric studies and observations (7 papers). Ashok Dahal is often cited by papers focused on Landslides and related hazards (20 papers), Flood Risk Assessment and Management (10 papers) and Cryospheric studies and observations (7 papers). Ashok Dahal collaborates with scholars based in Netherlands, China and Saudi Arabia. Ashok Dahal's co-authors include Luigi Lombardo, Hakan Tanyaş, Raphaël Huser, C.J. van Westen, Zhice Fang, Weiming Cheng, P. Martín, M. van der Meijde, Min Zhao and Hongyan Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Environmental Pollution.

In The Last Decade

Ashok Dahal

22 papers receiving 300 citations

Peers

Ashok Dahal

MMPL

GPC

CSE

SRRQ

Martina Sättele Switzerland

Feng Qing China

Muhammad Afaq Hussain China

Tina Peternel Slovenia

Giulia Bossi Italy

Gaetano Pecoraro Italy

Tianjun Qi China

Graham Gilbert Norway

K.S. Yin Hong Kong

Marco Mulas Italy

Martina Sättele Switzerland

Ashok Dahal

197 ×0.8

MMPL

102 ×0.8

GPC

88 ×0.8

49 ×1.0

CSE

52 ×1.1

SRRQ

Citations per year, relative to Ashok Dahal Ashok Dahal (= 1×) peers Martina Sättele

Countries citing papers authored by Ashok Dahal

Since Specialization

Citations

This map shows the geographic impact of Ashok Dahal's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ashok Dahal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashok Dahal more than expected).

Fields of papers citing papers by Ashok Dahal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashok Dahal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ashok Dahal. The network helps show where Ashok Dahal may publish in the future.

Co-authorship network of co-authors of Ashok Dahal

This figure shows the co-authorship network connecting the top 25 collaborators of Ashok Dahal. A scholar is included among the top collaborators of Ashok Dahal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ashok Dahal. Ashok Dahal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Dahal, Ashok, et al.. (2025). First Pockmark susceptibility map of the Italian continental margins. Marine and Petroleum Geology. 176. 107337–107337. 4 indexed citations

Lombardo, Luigi, Stefan Steger, Hakan Tanyaş, et al.. (2025). Pan‐European Landslide Risk Assessment: From Theory to Practice. Reviews of Geophysics. 63(1). 5 indexed citations

He, Jun, Hakan Tanyaş, Ashok Dahal, Da Huang, & Luigi Lombardo. (2025). Spatial prediction of InSAR-derived hillslope velocities via deep learning. Bulletin of Engineering Geology and the Environment. 84(3).

Wang, Tengfei, Kunlong Yin, Zheng Wang, et al.. (2025). Long and short-term perspectives on space–time landslide modelling. International Journal of Applied Earth Observation and Geoinformation. 142. 104694–104694.

Dahal, Ashok, et al.. (2025). Distribution and characteristics of microplastics in fluvial sediments from the Koshi River Basin, Nepal. Environmental Pollution. 374. 126189–126189.

Dahal, Ashok & Luigi Lombardo. (2024). Towards physics-informed neural networks for landslide prediction. Engineering Geology. 344. 107852–107852. 12 indexed citations

Tanyaş, Hakan, et al.. (2024). Distribution-agnostic landslide hazard modelling via Graph Transformers. Environmental Modelling & Software. 183. 106231–106231. 1 indexed citations

Dahal, Ashok, Raphaël Huser, & Luigi Lombardo. (2024). At the Junction Between Deep Learning and Statistics of Extremes: Formalizing the Landslide Hazard Definition. University of Twente Research Information. 1(3). 12 indexed citations

Chang, Ling, et al.. (2024). A closer look into variables controlling hillslope deformations in the Three Gorges Reservoir Area. Engineering Geology. 337. 107584–107584. 4 indexed citations

10.

Dahal, Ashok, Hakan Tanyaş, & Luigi Lombardo. (2024). Full seismic waveform analysis combined with transformer neural networks improves coseismic landslide prediction. Communications Earth & Environment. 5(1). 16 indexed citations

11.

Dahal, Ashok, Hakan Tanyaş, C.J. van Westen, et al.. (2024). Space–time landslide hazard modeling via Ensemble Neural Networks. Natural hazards and earth system sciences. 24(3). 823–845. 18 indexed citations

12.

Dahal, Ashok, Hakan Tanyaş, P. Martín, et al.. (2024). Quantifying the influence of topographic amplification on the landslides triggered by the 2015 Gorkha earthquake. Communications Earth & Environment. 5(1). 7 indexed citations

13.

Wang, Nan, Hongyan Zhang, Ashok Dahal, et al.. (2024). On the use of explainable AI for susceptibility modeling: Examining the spatial pattern of SHAP values. Geoscience Frontiers. 15(4). 101800–101800. 36 indexed citations

14.

Lim, Jana P., et al.. (2024). An ensemble neural network approach for space–time landslide predictive modelling. International Journal of Applied Earth Observation and Geoinformation. 132. 104037–104037. 3 indexed citations

15.

Richards, J. Ian, et al.. (2024). Deep graphical regression for jointly moderate and extreme Australian wildfires. Spatial Statistics. 59. 100811–100811. 16 indexed citations

16.

Mishra, Bhogendra, et al.. (2023). High-Resolution Mapping of Seasonal Crop Pattern Using Sentinel Imagery in Mountainous Region of Nepal: A Semi-Automatic Approach. SHILAP Revista de lepidopterología. 3(2). 312–327. 1 indexed citations

17.

Castellaro, Silvia, et al.. (2023). Assessing multi-hazard susceptibility to cryospheric hazards: Lesson learnt from an Alaskan example. The Science of The Total Environment. 898. 165289–165289. 15 indexed citations

18.

He, Kun, Luigi Lombardo, Ling Chang, et al.. (2023). Investigating earthquake legacy effect on hillslope deformation using InSAR‐derived time series. Earth Surface Processes and Landforms. 49(3). 980–990. 12 indexed citations

19.

Dahal, Ashok & Luigi Lombardo. (2023). Explainable artificial intelligence in geoscience: A glimpse into the future of landslide susceptibility modeling. Computers & Geosciences. 176. 105364–105364. 65 indexed citations

20.

Fang, Zhice, Hakan Tanyaş, Tolga Görüm, et al.. (2023). Speech-recognition in landslide predictive modelling: A case for a next generation early warning system. Environmental Modelling & Software. 170. 105833–105833. 21 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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