CORRIGENDUM: Scaling traffic variables from sensors sample to the entire city at high spatiotemporal resolution with machine learning: applications to the Paris megacity (2024 <i>Environ. Res.: Infrastruct. Sustain.</i>  4 035010)

CORRIGENDUM: Scaling traffic variables from sensors sample to the entire city at high spatiotemporal resolution with machine learning: applications to the Paris megacity (2024 Environ. Res.: Infrastruct. Sustain. 4 035010), Bonnemaizon, Xavier, Ciais, Philippe, Zhou, Chuanlong, Arous, Simon Ben, Davis, Steven J, Megel, Nicolas

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Publication Details

Journal
Environmental Research Infrastructure and Sustainability
Published
2026-01-14
DOI
https://doi.org/10.1088/2634-4505/ae34e5
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
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article

CORRIGENDUM: Scaling traffic variables from sensors sample to the entire city at high spatiotemporal resolution with machine learning: applications to the Paris megacity (2024 Environ. Res.: Infrastruct. Sustain.  4 035010)

Steven J. Davis, Simon Ben Arous, Chuanlong Zhou, Xavier Bonnemaizon et al.
Environmental Research Infrastructure and Sustainability
Traffic Prediction and Management Techniques
article

CORRIGENDUM: Scaling traffic variables from sensors sample to the entire city at high spatiotemporal resolution with machine learning: applications to the Paris megacity (2024 Environ. Res.: Infrastruct. Sustain.  4 035010)

Steven J. Davis, Simon Ben Arous, Chuanlong Zhou, Xavier Bonnemaizon, Nicolas Megel, Philippe Ciais
article en

Abstract

CORRIGENDUM: Scaling traffic variables from sensors sample to the entire city at high spatiotemporal resolution with machine learning: applications to the Paris megacity (2024 Environ. Res.: Infrastruct. Sustain. 4 035010), Bonnemaizon, Xavier, Ciais, Philippe, Zhou, Chuanlong, Arous, Simon Ben, Davis, Steven J, Megel, Nicolas

Environmental Research Infrastructure and SustainabilityVol. 6(1)
Centre National de la Recherche Scientifique (FR), Université de Versailles Saint-Quentin-en-Yvelines (FR), University of California, Irvine (US), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris-Saclay (FR), Nexans (France) (FR), Laboratoire des Sciences du Climat et de l'Environnement (FR), CEA Paris-Saclay (FR)
Sustainable cities and communities
Openalex Percentile: Top 87%
Traffic Prediction and Management Techniques
DOIOpen Access PDFOpenAlex
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CORRIGENDUM: Scaling traffic variables from sensors sample to the entire city at high spatiotemporal resolution with machine learning: applications to the Paris megacity (2024 <i>Environ. Res.: Infrastruct. Sustain.</i>  4 035010) — Steven J. Davis, Simon Ben Arous, et al. · Environmental Research Infrastructure and Sustainability (2026) | TGRS Research Map | TGRS