Camille Lelong

1.5k total citations · 1 hit paper
29 papers, 1.1k citations indexed

About

Camille Lelong is a scholar working on Ecology, Analytical Chemistry and Media Technology. According to data from OpenAlex, Camille Lelong has authored 29 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Ecology, 7 papers in Analytical Chemistry and 5 papers in Media Technology. Recurrent topics in Camille Lelong's work include Remote Sensing in Agriculture (11 papers), Spectroscopy and Chemometric Analyses (7 papers) and Remote-Sensing Image Classification (5 papers). Camille Lelong is often cited by papers focused on Remote Sensing in Agriculture (11 papers), Spectroscopy and Chemometric Analyses (7 papers) and Remote-Sensing Image Classification (5 papers). Camille Lelong collaborates with scholars based in France, Belgium and Pakistan. Camille Lelong's co-authors include Frédéric Baret, Guillaume Jubelin, Philippe Burger, Bruno Roux, Sabrina Labbé, Hervé Poilvé, P. Pinet, Agnès Bégué, Diego de Abelleyra and Julie Betbeder and has published in prestigious journals such as Remote Sensing of Environment, Sensors and International Journal of Remote Sensing.

In The Last Decade

Camille Lelong

24 papers receiving 999 citations

Hit Papers

Remote Sensing and Cropping Practices: A Review 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Camille Lelong France 11 677 360 340 260 139 29 1.1k
Valentine Lebourgeois France 11 668 1.0× 386 1.1× 290 0.9× 333 1.3× 102 0.7× 18 968
K. R. Manjunath India 19 560 0.8× 250 0.7× 222 0.7× 267 1.0× 143 1.0× 46 966
Raphaël d’Andrimont Italy 15 683 1.0× 276 0.8× 340 1.0× 414 1.6× 224 1.6× 38 1.2k
Alain A. Viau Canada 17 602 0.9× 374 1.0× 506 1.5× 354 1.4× 173 1.2× 64 1.4k
Claire Marais-Sicre France 8 520 0.8× 230 0.6× 323 0.9× 232 0.9× 88 0.6× 18 698
Chunhua Liao Canada 16 557 0.8× 214 0.6× 365 1.1× 264 1.0× 151 1.1× 34 910
Paolo Villa Italy 20 861 1.3× 651 1.8× 361 1.1× 542 2.1× 202 1.5× 53 2.0k
Marcela Arias France 6 852 1.3× 248 0.7× 335 1.0× 420 1.6× 305 2.2× 8 1.1k
Xiaohe Gu China 18 617 0.9× 455 1.3× 318 0.9× 169 0.7× 68 0.5× 117 1.0k
S. Panigrahy India 17 478 0.7× 292 0.8× 309 0.9× 261 1.0× 133 1.0× 56 988

Countries citing papers authored by Camille Lelong

Since Specialization
Citations

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

Fields of papers citing papers by Camille Lelong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Camille Lelong

This figure shows the co-authorship network connecting the top 25 collaborators of Camille Lelong. A scholar is included among the top collaborators of Camille Lelong 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 Camille Lelong. Camille Lelong 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.
Lelong, Camille, et al.. (2026). Rhodiola rosea L. roots powder strongly reduces anxiety and corticosterone level induced by chronic stress in a murine model. Journal of Pharmaceutical Health Care and Sciences. 12(1). 21–21.
2.
Petitjean, Simon J. L., Marylène Lecocq, Camille Lelong, et al.. (2022). Salvia miltiorrhiza Bunge as a Potential Natural Compound against COVID-19. Cells. 11(8). 1311–1311. 26 indexed citations
4.
Lelong, Camille, et al.. (2020). Assessing Worldview-3 multispectral imaging abilities to map the tree diversity in semi-arid parklands. International Journal of Applied Earth Observation and Geoinformation. 93. 102211–102211. 24 indexed citations
5.
Bégué, Agnès, Damien Arvor, Beatriz Bellón, et al.. (2018). Remote Sensing and Cropping Practices: A Review. Remote Sensing. 10(1). 99–99. 312 indexed citations breakdown →
6.
Lelong, Camille, Valérie Soti, Annelise Tran, et al.. (2014). A remote sensing and GIS approach to the relationship between canegrub infestations and natural vegetation in the sugarcane landscape of Queensland, Australia. Agritrop (Cirad). 1 indexed citations
7.
Dupuy, Stéphane, et al.. (2014). Discrimination of tropical agroforestry systems in very high resolution satellite imagery using object-based hierarchical classification: a case-study on cocoa in Cameroon. Agritrop (Cirad). 2 indexed citations
8.
Soti, Valérie, Véronique Chevalier, Agnès Bégué, et al.. (2013). Identifying landscape features associated with Rift Valley fever virus transmission, Ferlo region, Senegal, using very high spatial resolution satellite imagery. International Journal of Health Geographics. 12(1). 10–10. 24 indexed citations
9.
Rabatel, Gilles, et al.. (2012). An iterative hyperspectral image segmentation method using a cross analysis of spectral and spatial information. Chemometrics and Intelligent Laboratory Systems. 117. 213–223. 15 indexed citations
10.
Soti, Valérie, Véronique Chevalier, Agnès Bégué, et al.. (2011). Landscape characterization of Rift Valley Fever risk areas using very high spatial resolution imagery - case study in the Ferlo area, Senegal. Agritrop (Cirad).
11.
Kpalma, Kidiyo, et al.. (2011). Fusion of Textural and Spectral Information for Tree Crop and Other Agricultural Cover Mapping With Very-High Resolution Satellite Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 5(1). 225–235. 33 indexed citations
12.
Lelong, Camille, et al.. (2010). Evaluation of Oil-Palm Fungal Disease Infestation with Canopy Hyperspectral Reflectance Data. Sensors. 10(1). 734–747. 78 indexed citations
13.
Gorretta, Nathalie, Jean‐Michel Roger, Christophe Fiorio, et al.. (2009). Proposition d'une stratégie de segmentation d'images hyperspectrales. SPIRE - Sciences Po Institutional REpository. 26(2). 161–174. 1 indexed citations
14.
Gorretta, Nathalie, Gilles Rabatel, Jean‐Michel Roger, et al.. (2008). Hyperspectral Imaging System Calibration Using Image Translations and Fourier Transform. Journal of Near Infrared Spectroscopy. 16(4). 371–380. 1 indexed citations
15.
Lelong, Camille, Philippe Burger, Guillaume Jubelin, et al.. (2008). Assessment of Unmanned Aerial Vehicles Imagery for Quantitative Monitoring of Wheat Crop in Small Plots. Sensors. 8(5). 3557–3585. 317 indexed citations
16.
Delenne, Carole, Sylvie Durrieu, Gilles Rabatel, et al.. (2007). Textural approaches for vineyard detection and characterization using very high spatial resolution remote sensing data. International Journal of Remote Sensing. 29(4). 1153–1167. 37 indexed citations
17.
Avelino, Jacques, Jean-Jacques Perriot, Michel Jacquet, et al.. (2005). Developing a geographical indication for Arabica coffee in Bali : Description of the "Terroir" of Kintamani. Agritrop (Cirad). 922–928. 2 indexed citations
18.
19.
Lelong, Camille. (1976). For beef cattle, all forms of maize can be used. Animal Feed Science and Technology. 1(2-3). 521–529.
20.
Lelong, Camille. (1976). Maize and animal production in France. Animal Feed Science and Technology. 1(2-3). 141–147. 1 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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