Pierre Dérian

536 total citations
17 papers, 338 citations indexed

About

Pierre Dérian is a scholar working on Environmental Engineering, Global and Planetary Change and Computer Vision and Pattern Recognition. According to data from OpenAlex, Pierre Dérian has authored 17 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Environmental Engineering, 7 papers in Global and Planetary Change and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Pierre Dérian's work include Atmospheric aerosols and clouds (6 papers), Remote Sensing and LiDAR Applications (5 papers) and Wind and Air Flow Studies (4 papers). Pierre Dérian is often cited by papers focused on Atmospheric aerosols and clouds (6 papers), Remote Sensing and LiDAR Applications (5 papers) and Wind and Air Flow Studies (4 papers). Pierre Dérian collaborates with scholars based in France, United States and China. Pierre Dérian's co-authors include Patrick Héas, Étienne Mémin, Étienne Mémin, Rafaël Almar, Shane D. Mayor, Shengze Cai, Chao Xu, Cédric Herzet, Meghdad Khazaee and Bertrand Chapron and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Renewable Energy and International Journal of Computer Vision.

In The Last Decade

Pierre Dérian

17 papers receiving 325 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pierre Dérian France 9 128 110 66 65 59 17 338
Hari Warrior India 12 162 1.3× 19 0.2× 55 0.8× 65 1.0× 65 1.1× 42 425
Cesario Vincenzo Angelino Italy 9 77 0.6× 517 4.7× 46 0.7× 59 0.9× 41 0.7× 19 782
L. Shao France 13 444 3.5× 57 0.5× 64 1.0× 158 2.4× 85 1.4× 36 546
Nan Ge China 10 36 0.3× 103 0.9× 80 1.2× 100 1.5× 163 2.8× 27 520
Jason I. Gobat United States 14 125 1.0× 18 0.2× 56 0.8× 20 0.3× 91 1.5× 37 521
R. Malki United Kingdom 8 115 0.9× 54 0.5× 25 0.4× 40 0.6× 19 0.3× 11 374
Ting Bai China 9 42 0.3× 74 0.7× 87 1.3× 70 1.1× 122 2.1× 21 454
Albert Prades Spain 11 32 0.3× 652 5.9× 57 0.9× 64 1.0× 64 1.1× 19 1.1k
S. Coudert France 13 374 2.9× 42 0.4× 70 1.1× 174 2.7× 29 0.5× 30 532
Anthony Currie United Kingdom 6 56 0.4× 37 0.3× 143 2.2× 76 1.2× 77 1.3× 11 862

Countries citing papers authored by Pierre Dérian

Since Specialization
Citations

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

Fields of papers citing papers by Pierre Dérian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pierre Dérian. 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 Pierre Dérian. The network helps show where Pierre Dérian may publish in the future.

Co-authorship network of co-authors of Pierre Dérian

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

All Works

17 of 17 papers shown
1.
Khazaee, Meghdad, et al.. (2022). A comprehensive study on Structural Health Monitoring (SHM) of wind turbine blades by instrumenting tower using machine learning methods. Renewable Energy. 199. 1568–1579. 35 indexed citations
2.
Li, Lian, et al.. (2020). New Trends in Ensemble Forecast Strategy: Uncertainty Quantification for Coarse-Grid Computational Fluid Dynamics. Archives of Computational Methods in Engineering. 28(1). 215–261. 21 indexed citations
3.
Mayor, Shane D. & Pierre Dérian. (2018). Comments on “Wind Gust Detection and Impact Prediction for Wind Turbines”. Remote Sensing. 10(10). 1625–1625. 1 indexed citations
4.
Dérian, Pierre & Rafaël Almar. (2017). Wavelet-Based Optical Flow Estimation of Instant Surface Currents From Shore-Based and UAV Videos. IEEE Transactions on Geoscience and Remote Sensing. 55(10). 5790–5797. 47 indexed citations
5.
Cai, Shengze, Étienne Mémin, Pierre Dérian, & Chao Xu. (2017). Motion estimation under location uncertainty for turbulent fluid flows. Experiments in Fluids. 59(1). 50 indexed citations
6.
Chapron, Bertrand, et al.. (2017). Large‐scale flows under location uncertainty: a consistent stochastic framework. Quarterly Journal of the Royal Meteorological Society. 144(710). 251–260. 29 indexed citations
7.
Mayor, Shane D., et al.. (2016). Comparison of an analog direct detection and a micropulse aerosol lidar at 1.5 - μ m wavelength for wind field observations—with first results over the ocean. Journal of Applied Remote Sensing. 10(1). 16031–16031. 5 indexed citations
8.
Mayor, Shane D., et al.. (2015). Two-component wind fields from single scanning aerosol lidar. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9612. 96120D–96120D. 2 indexed citations
9.
Mayor, Shane D., et al.. (2015). Comparison of aerosol backscatter and wind field estimates from the REAL and the SAMPLE. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9612. 96120G–96120G. 4 indexed citations
10.
Dérian, Pierre, et al.. (2015). Optimization of the Cross-Correlation Algorithm for Two-Component Wind Field Estimation from Single Aerosol Lidar Data and Comparison with Doppler Lidar. Journal of Atmospheric and Oceanic Technology. 33(1). 81–101. 10 indexed citations
11.
Dérian, Pierre, et al.. (2015). Wavelet-Based Optical Flow for Two-Component Wind Field Estimation from Single Aerosol Lidar Data. Journal of Atmospheric and Oceanic Technology. 32(10). 1759–1778. 20 indexed citations
12.
Dérian, Pierre, Patrick Héas, Cédric Herzet, & Étienne Mémin. (2013). Wavelets and Optical Flow Motion Estimation. Numerical Mathematics Theory Methods and Applications. 6(1). 116–137. 51 indexed citations
13.
Mayor, Shane D., et al.. (2013). Two-component wind fields from scanning aerosol lidar and motion estimation algorithms. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8872. 887208–887208. 4 indexed citations
14.
Dérian, Pierre, et al.. (2012). Divergence-Free Wavelets and High Order Regularization. International Journal of Computer Vision. 103(1). 80–99. 51 indexed citations
15.
Dérian, Pierre, Patrick Héas, & Étienne Mémin. (2011). WAVELETS TO RECONSTRUCT TURBULENCE MULTIFRACTALS FROM EXPERIMENTAL IMAGE SEQUENCES. 1–6. 2 indexed citations
16.
Mayor, Shane D., Pierre Dérian, Patrick Héas, & Étienne Mémin. (2010). Two-Component Horizontal Motion Vectors from Scanning Eye-Safe Aerosol Lidar. HAL (Le Centre pour la Communication Scientifique Directe). 2 indexed citations
17.
Dérian, Pierre, Patrick Héas, Étienne Mémin, & Shane D. Mayor. (2010). Dense Motion Estimation from Eye-Safe Aerosol Lidar Data. HAL (Le Centre pour la Communication Scientifique Directe). 4 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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