Benoît Gschwind

1.4k total citations
15 papers, 916 citations indexed

About

Benoît Gschwind is a scholar working on Artificial Intelligence, Global and Planetary Change and Atmospheric Science. According to data from OpenAlex, Benoît Gschwind has authored 15 papers receiving a total of 916 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 9 papers in Global and Planetary Change and 5 papers in Atmospheric Science. Recurrent topics in Benoît Gschwind's work include Solar Radiation and Photovoltaics (10 papers), Atmospheric aerosols and clouds (6 papers) and Photovoltaic System Optimization Techniques (4 papers). Benoît Gschwind is often cited by papers focused on Solar Radiation and Photovoltaics (10 papers), Atmospheric aerosols and clouds (6 papers) and Photovoltaic System Optimization Techniques (4 papers). Benoît Gschwind collaborates with scholars based in France, Germany and Finland. Benoît Gschwind's co-authors include Lucien Wald, Mireille Lefèvre, Philippe Blanc, Marion Schroedter‐Homscheidt, Zhipeng Qu, Bella Espinar, Armel Oumbe, Antti Arola, Lionel Ménard and Jean‐Jacques Morcrette and has published in prestigious journals such as Remote Sensing, Environmental Modelling & Software and Progress in Photovoltaics Research and Applications.

In The Last Decade

Benoît Gschwind

15 papers receiving 877 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benoît Gschwind France 10 696 411 367 161 155 15 916
Bella Espinar France 11 797 1.1× 479 1.2× 375 1.0× 173 1.1× 161 1.0× 12 937
Armel Oumbe France 9 584 0.8× 322 0.8× 325 0.9× 162 1.0× 94 0.6× 16 674
Barbara Ridley Australia 6 416 0.6× 293 0.7× 189 0.5× 139 0.9× 107 0.7× 8 645
A. Zelenka Switzerland 12 728 1.0× 429 1.0× 438 1.2× 250 1.6× 107 0.7× 19 990
Karl Hemker United States 10 814 1.2× 547 1.3× 187 0.5× 166 1.0× 383 2.5× 11 984
Vicente Lara-Fanego Spain 12 594 0.9× 308 0.7× 338 0.9× 289 1.8× 349 2.3× 19 931
Óscar Perpiñán Spain 18 648 0.9× 505 1.2× 171 0.5× 84 0.5× 381 2.5× 26 946
Francisco J. Santos‐Alamillos Spain 18 510 0.7× 252 0.6× 493 1.3× 413 2.6× 478 3.1× 28 1.2k
James Schlemmer United States 15 571 0.8× 404 1.0× 272 0.7× 233 1.4× 244 1.6× 27 880
Richard Mueller Germany 14 512 0.7× 183 0.4× 521 1.4× 303 1.9× 50 0.3× 18 831

Countries citing papers authored by Benoît Gschwind

Since Specialization
Citations

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

Fields of papers citing papers by Benoît Gschwind

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benoît Gschwind

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

All Works

15 of 15 papers shown
1.
Saint‐Drenan, Yves‐Marie, et al.. (2023). Retrieval of surface solar irradiance from satellite imagery using machine learning: pitfalls and perspectives. Atmospheric measurement techniques. 16(18). 4165–4181. 5 indexed citations
2.
Gschwind, Benoît, et al.. (2022). An alternative cloud index for estimating downwelling surface solar irradiance from various satellite imagers in the framework of a Heliosat-V method. Atmospheric measurement techniques. 15(12). 3683–3704. 4 indexed citations
3.
Gschwind, Benoît, Lucien Wald, Philippe Blanc, et al.. (2019). Improving the McClear model estimating the downwelling solar radiation at ground level in cloud-free conditions – McClear‑v3. Meteorologische Zeitschrift. 28(2). 147–163. 77 indexed citations
4.
Blanc, Philippe, Benoît Gschwind, Lionel Ménard, & Lucien Wald. (2018). Monthly-averaged maps of surface BRDF parameters in ten spectralbands for land and water masses. Biogeosciences (European Geosciences Union). 3 indexed citations
5.
Jones, P. D., Colin Harpham, Alberto Troccoli, et al.. (2017). Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables. Earth system science data. 9(2). 471–495. 43 indexed citations
6.
Pérez‐López, Paula, Benoît Gschwind, Philippe Blanc, et al.. (2016). ENVI‐PV: an interactive Web Client for multi‐criteria life cycle assessment of photovoltaic systems worldwide. Progress in Photovoltaics Research and Applications. 25(7). 484–498. 20 indexed citations
7.
Qu, Zhipeng, Armel Oumbe, Philippe Blanc, et al.. (2016). Fast radiative transfer parameterisation for assessing the surface solar irradiance: The Heliosat‑4 method. Meteorologische Zeitschrift. 26(1). 33–57. 173 indexed citations
8.
Qu, Zhipeng, Benoît Gschwind, Mireille Lefèvre, & Lucien Wald. (2014). Improving HelioClim-3 estimates of surface solar irradiance using the McClear clear-sky model and recent advances in atmosphere composition. Atmospheric measurement techniques. 7(11). 3927–3933. 40 indexed citations
9.
Lefèvre, Mireille, Philippe Blanc, Bella Espinar, et al.. (2014). The HelioClim-1 Database of Daily Solar Radiation at Earth Surface: An Example of the Benefits of GEOSS Data-CORE. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 7(5). 1745–1753. 31 indexed citations
10.
Gschwind, Benoît, Mireille Lefèvre, Isabelle Blanc, et al.. (2014). Including the temporal change in PM2.5 concentration in the assessment of human health impact: Illustration with renewable energy scenarios to 2050. Environmental Impact Assessment Review. 52. 62–68. 21 indexed citations
11.
Lefèvre, Mireille, Armel Oumbe, Philippe Blanc, et al.. (2013). McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions. Atmospheric measurement techniques. 6(9). 2403–2418. 289 indexed citations
12.
Ménard, Lionel, Isabelle Blanc, Didier Beloin‐Saint‐Pierre, et al.. (2012). Benefit of GEOSS Interoperability in Assessment of Environmental Impacts Illustrated by the Case of Photovoltaic Systems. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 5(6). 1722–1728. 8 indexed citations
13.
Blanc, Philippe, Benoît Gschwind, Mireille Lefèvre, & Lucien Wald. (2011). The HelioClim Project: Surface Solar Irradiance Data for Climate Applications. Remote Sensing. 3(2). 343–361. 132 indexed citations
14.
Oumbe, Armel, Philippe Blanc, Benoît Gschwind, et al.. (2011). Solar irradiance in clear atmosphere: study of parameterisations of change with altitude. Advances in science and research. 6(1). 199–203. 6 indexed citations
15.
Gschwind, Benoît, Lionel Ménard, Michel Albuisson, & Lucien Wald. (2006). Converting a successful research project into a sustainable service: The case of the SoDa Web service. Environmental Modelling & Software. 21(11). 1555–1561. 64 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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