Phan Trọng Trịnh

5.1k total citations · 5 hit papers
61 papers, 4.2k citations indexed

About

Phan Trọng Trịnh is a scholar working on Geophysics, Global and Planetary Change and Geology. According to data from OpenAlex, Phan Trọng Trịnh has authored 61 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Geophysics, 24 papers in Global and Planetary Change and 17 papers in Geology. Recurrent topics in Phan Trọng Trịnh's work include earthquake and tectonic studies (20 papers), Geological and Geochemical Analysis (20 papers) and Geological and Geophysical Studies (17 papers). Phan Trọng Trịnh is often cited by papers focused on earthquake and tectonic studies (20 papers), Geological and Geochemical Analysis (20 papers) and Geological and Geophysical Studies (17 papers). Phan Trọng Trịnh collaborates with scholars based in Vietnam, France and Iran. Phan Trọng Trịnh's co-authors include Robin Lacassin, Philippe Hervé Leloup, Dieu Tien Bui, Paul Tapponnier, Dalai Zhong, Urs Schärer, Xiaohan Liu, Shaocheng Ji, Ngô Văn Liêm and Binh Thai Pham and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Chemosphere and Journal of Hydrology.

In The Last Decade

Phan Trọng Trịnh

57 papers receiving 4.0k citations

Hit Papers

The Ailao Shan-Red River shear zone (Yunnan, China), Tert... 1995 2026 2005 2015 1995 2001 2020 2016 2020 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Phan Trọng Trịnh Vietnam 27 2.1k 1.1k 1.0k 877 535 61 4.2k
Alexander L. Densmore United Kingdom 45 2.4k 1.1× 1.2k 1.1× 2.9k 2.8× 441 0.5× 251 0.5× 133 6.7k
M. T. Pareschi Italy 35 1.3k 0.6× 643 0.6× 1.0k 1.0× 317 0.4× 265 0.5× 82 3.3k
Ioannis Koukouvelas Greece 34 1.8k 0.8× 177 0.2× 539 0.5× 334 0.4× 397 0.7× 118 2.8k
Andréa Zanchi Italy 33 2.6k 1.2× 198 0.2× 858 0.8× 172 0.2× 739 1.4× 98 3.9k
Ágúst Guðmundsson United Kingdom 59 7.8k 3.7× 370 0.3× 869 0.8× 473 0.5× 690 1.3× 222 10.4k
Qiang Xu China 32 473 0.2× 489 0.4× 1.8k 1.8× 656 0.7× 195 0.4× 133 3.5k
Antonio Cendrero Spain 28 699 0.3× 665 0.6× 1.3k 1.3× 230 0.3× 94 0.2× 62 2.9k
José Luis Macías Mexico 43 3.2k 1.5× 526 0.5× 1.0k 1.0× 117 0.1× 1.0k 1.9× 190 5.0k
Mahdi Motagh Germany 38 1.2k 0.6× 777 0.7× 1.2k 1.2× 111 0.1× 190 0.4× 195 4.7k
Falk Amelung United States 51 3.8k 1.8× 606 0.6× 1.5k 1.4× 304 0.3× 296 0.6× 151 7.8k

Countries citing papers authored by Phan Trọng Trịnh

Since Specialization
Citations

This map shows the geographic impact of Phan Trọng Trịnh'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 Phan Trọng Trịnh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phan Trọng Trịnh more than expected).

Fields of papers citing papers by Phan Trọng Trịnh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phan Trọng Trịnh. 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 Phan Trọng Trịnh. The network helps show where Phan Trọng Trịnh may publish in the future.

Co-authorship network of co-authors of Phan Trọng Trịnh

This figure shows the co-authorship network connecting the top 25 collaborators of Phan Trọng Trịnh. A scholar is included among the top collaborators of Phan Trọng Trịnh 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 Phan Trọng Trịnh. Phan Trọng Trịnh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dang, Kinh Bac, et al.. (2024). Deep learning models integrating multi-sensor and -temporal remote sensing to monitor landslide traces in Vietnam. International Journal of Disaster Risk Reduction. 105. 104391–104391. 5 indexed citations
4.
Duong, Van-Hao, et al.. (2023). Radiological Hazard Assessment of High-Level Natural Radionuclides in Surface Sediments Along Red River, Vietnam. Archives of Environmental Contamination and Toxicology. 85(3). 302–313. 7 indexed citations
5.
Jaafari, Abolfazl, et al.. (2023). Groundwater potential mapping in the Central Highlands of Vietnam using spatially explicit machine learning. Earth Science Informatics. 16(1). 131–146. 17 indexed citations
6.
Bui, Quang‐Thanh, Quang Hải Trương, Phan Trọng Trịnh, et al.. (2023). Coastal landscape classification using convolutional neural network and remote sensing data in Vietnam. Journal of Environmental Management. 335. 117537–117537. 16 indexed citations
7.
Trịnh, Phan Trọng, et al.. (2022). Surface ruptures and land deformation from the 21 June 2022 Afghanistan earthquake. 4 indexed citations
8.
Pham, Binh Thai, Vu Duy Vinh, Romulus Costache, et al.. (2021). Landslide susceptibility mapping using state-of-the-art machine learning ensembles. Geocarto International. 37(18). 5175–5200. 39 indexed citations
9.
Duong, Van-Hao, et al.. (2021). Cu-Au mineralization of the Sin Quyen deposit in north Vietnam: A product of Cenozoic left-lateral movement along the Red River shear zone. Ore Geology Reviews. 132. 104065–104065. 11 indexed citations
10.
Dao, Dong Van, Mahmoud Bayat, Davood Mafi-Gholami, et al.. (2020). A spatially explicit deep learning neural network model for the prediction of landslide susceptibility. CATENA. 188. 104451–104451. 264 indexed citations breakdown →
11.
Pham, Binh Thai, Chinh Luu, Tran Van Phong, et al.. (2020). Can deep learning algorithms outperform benchmark machine learning algorithms in flood susceptibility modeling?. Journal of Hydrology. 592. 125615–125615. 106 indexed citations
12.
Ha, Duong Hai, Huu Duy Nguyen, Tran Van Phong, et al.. (2020). Improvement of Credal Decision Trees Using Ensemble Frameworks for Groundwater Potential Modeling. Sustainability. 12(7). 2622–2622. 47 indexed citations
13.
Duong, Van-Hao, et al.. (2020). Natural radionuclides and assessment of radiological hazards in MuongHum, Lao Cai, Vietnam. Chemosphere. 270. 128671–128671. 35 indexed citations
14.
Phong, Tran Van, Phan Trọng Trịnh, Indra Prakash, et al.. (2019). Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam. Geocarto International. 36(15). 1685–1708. 77 indexed citations
15.
Pham, Binh Thai, Indra Prakash, Jie Dou, et al.. (2018). A novel hybrid approach of landslide susceptibility modelling using rotation forest ensemble and different base classifiers. Geocarto International. 35(12). 1267–1292. 149 indexed citations
16.
Pham, Binh Thai, Indra Prakash, Khabat Khosravi, et al.. (2018). A comparison of Support Vector Machines and Bayesian algorithms for landslide susceptibility modelling. Geocarto International. 34(13). 1385–1407. 98 indexed citations
17.
Trịnh, Phan Trọng, et al.. (2016). Some study results of Cam Ranh - Binh Thuan mud eruption strip. Vietnam Journal of Earth Sciences. 38(3). 1 indexed citations
19.
Giuliani, Gaston, Jean Dubessy, David Banks, et al.. (2003). CO2–H2S–COS–S8–AlO(OH)-bearing fluid inclusions in ruby from marble-hosted deposits in Luc Yen area, North Vietnam. Chemical Geology. 194(1-3). 167–185. 49 indexed citations
20.
Leloup, Philippe Hervé, Nicolas Arnaud, Robin Lacassin, et al.. (2001). New constraints on the structure, thermochronology, and timing of the Ailao Shan‐Red River shear zone, SE Asia. Journal of Geophysical Research Atmospheres. 106(B4). 6683–6732. 629 indexed citations breakdown →

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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