Charlotte Pelletier

2.2k total citations · 2 hit papers
27 papers, 1.5k citations indexed

About

Charlotte Pelletier is a scholar working on Media Technology, Ecology and Signal Processing. According to data from OpenAlex, Charlotte Pelletier has authored 27 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Media Technology, 12 papers in Ecology and 6 papers in Signal Processing. Recurrent topics in Charlotte Pelletier's work include Remote-Sensing Image Classification (14 papers), Remote Sensing in Agriculture (12 papers) and Image and Signal Denoising Methods (4 papers). Charlotte Pelletier is often cited by papers focused on Remote-Sensing Image Classification (14 papers), Remote Sensing in Agriculture (12 papers) and Image and Signal Denoising Methods (4 papers). Charlotte Pelletier collaborates with scholars based in France, Australia and Austria. Charlotte Pelletier's co-authors include Silvia Valero, Nicolas Champion, Jordi Inglada, Gérard Dedieu, Claire Marais Sicre, Geoffrey I. Webb, Sébastien Lefèvre, François Petitjean, Stefan Lang and Marco Körner and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Remote Sensing.

In The Last Decade

Charlotte Pelletier

26 papers receiving 1.5k citations

Hit Papers

2 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Assessing the robustness of Random Forests to map land cover with high resolution satellite image time series over large areas

2016 471 citations Charlotte Pelletier, Silvia Valero et al. Remote Sensing of Environment profile →
Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series

2019 374 citations Charlotte Pelletier MDPI (MDPI AG) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Charlotte Pelletier France	12	905	434	424	418	343	27	1.5k
Silvia Valero France	17	1.1k 1.2×	580 1.3×	630 1.5×	617 1.5×	443 1.3×	46	1.9k
Pieter Kempeneers Belgium	21	743 0.8×	420 1.0×	324 0.8×	392 0.9×	250 0.7×	60	1.3k
Raffaele Gaetano France	21	788 0.9×	308 0.7×	823 1.9×	395 0.9×	357 1.0×	64	1.7k
Marco Körner Germany	21	477 0.5×	396 0.9×	550 1.3×	440 1.1×	253 0.7×	57	1.7k
Ziheng Sun United States	20	469 0.5×	410 0.9×	157 0.4×	288 0.7×	197 0.6×	82	1.5k
Ovidiu Csillik United States	14	1.4k 1.5×	749 1.7×	625 1.5×	717 1.7×	481 1.4×	23	2.2k
Monica Pepe Italy	20	489 0.5×	263 0.6×	211 0.5×	328 0.8×	375 1.1×	66	1.5k
Emma Izquierdo‐Verdiguier Spain	16	485 0.5×	295 0.7×	254 0.6×	268 0.6×	207 0.6×	60	982
Lina Hu China	7	770 0.9×	308 0.7×	234 0.6×	319 0.8×	248 0.7×	7	1.1k
Meixia Deng United States	18	534 0.6×	393 0.9×	137 0.3×	243 0.6×	207 0.6×	37	1.0k

Countries citing papers authored by Charlotte Pelletier

Since Specialization

Citations

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

Fields of papers citing papers by Charlotte Pelletier

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Charlotte Pelletier

This figure shows the co-authorship network connecting the top 25 collaborators of Charlotte Pelletier. A scholar is included among the top collaborators of Charlotte Pelletier 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 Charlotte Pelletier. Charlotte Pelletier 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

Pelletier, Charlotte, et al.. (2025). Mapping intra-annual integrated crop-livestock systems in Mato Grosso using deep learning and MODIS time series. SPIRE - Sciences Po Institutional REpository. 26–26.

Zhang, Hankui K., Gustau Camps‐Valls, Shunlin Liang, et al.. (2025). Preface: Advancing deep learning for remote sensing time series data analysis. Remote Sensing of Environment. 322. 114711–114711. 4 indexed citations

Audebert, Nicolas, et al.. (2024). Cross-sensor super-resolution of irregularly sampled Sentinel-2 time series. SPIRE - Sciences Po Institutional REpository. 502–511. 1 indexed citations

Pelletier, Charlotte, et al.. (2024). Forecasting water resources from satellite image time series using a graph-based learning strategy. SHILAP Revista de lepidopterología. XLVIII-2-2024. 81–88. 1 indexed citations

Miller, Lynn, Charlotte Pelletier, & Geoffrey I. Webb. (2024). Deep Learning for Satellite Image Time-Series Analysis: A review. IEEE Geoscience and Remote Sensing Magazine. 12(3). 81–124. 20 indexed citations

Pelletier, Charlotte, et al.. (2023). Elastic similarity and distance measures for multivariate time series. Knowledge and Information Systems. 65(6). 2665–2698. 16 indexed citations

Pelletier, Charlotte, et al.. (2023). Detecting Land Cover Changes between Satellite Image Time Series by Exploiting Self-Supervised Representation Learning Capabilities. SPIRE - Sciences Po Institutional REpository. 7168–7171. 2 indexed citations

Pelletier, Charlotte, et al.. (2021). A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping. Machine Learning. 112(6). 1941–1973. 24 indexed citations

Pelletier, Charlotte, et al.. (2021). Crop Type Mapping from Optical and Radar Time Series Using Attention-Based Deep Learning. Remote Sensing. 13(22). 4668–4668. 57 indexed citations

10.

Mboga, Nicholus, Stefano D’Aronco, Taïs Grippa, et al.. (2021). Domain Adaptation for Semantic Segmentation of Historical Panchromatic Orthomosaics in Central Africa. ISPRS International Journal of Geo-Information. 10(8). 523–523. 10 indexed citations

11.

Rußwurm, Marc, et al.. (2020). BREIZHCROPS: A TIME SERIES DATASET FOR CROP TYPE MAPPING. HAL (Le Centre pour la Communication Scientifique Directe). 61 indexed citations

12.

Pelletier, Charlotte. (2019). Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series. MDPI (MDPI AG). 374 indexed citations breakdown →

13.

Kennedy, Jenny, et al.. (2019). What Can 100,000 Books Tell Us about the International Public Library e-lending Landscape?. LawArXiv (OSF Preprints). 9 indexed citations

14.

Pelletier, Charlotte, Geoffrey I. Webb, & François Petitjean. (2019). Deep Learning for the Classification of Sentinel-2 Image Time Series. 461–464. 25 indexed citations

15.

Pelletier, Charlotte, Silvia Valero, Jordi Inglada, Gérard Dedieu, & Nicolas Champion. (2017). New iterative learning strategy to improve classification systems by using outlier detection techniques. 3676–3679. 3 indexed citations

16.

Ferrant, Sylvain, Michel Le Page, Pierre‐Alexis Herrault, et al.. (2017). Detection of Irrigated Crops from Sentinel-1 and Sentinel-2 Data to Estimate Seasonal Groundwater Use in South India. Remote Sensing. 9(11). 1119–1119. 82 indexed citations

17.

Pelletier, Charlotte, Silvia Valero, Jordi Inglada, Gérard Dedieu, & Nicolas Champion. (2017). Filtering mislabeled data for improving time series classification. 7. 1–4. 8 indexed citations

18.

Pelletier, Charlotte, Silvia Valero, Jordi Inglada, Gérard Dedieu, & Nicolas Champion. (2016). An assessment of image features and random forest for land cover mapping over large areas using high resolution Satellite Image Time Series. 3338–3341. 8 indexed citations

19.

Valero, Silvia, Charlotte Pelletier, & Marta Bertolino. (2016). Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities. 2308–2311. 6 indexed citations

20.

Pelletier, Charlotte, et al.. (2015). Primal sketch of image series with edge preserving filtering application to change detection. 1–4. 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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