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Publication details

Document type
Journal articles

Document subtype
Full paper

Title
On the deep learning approach for improving the representation of urban climate: The Paris urban heat island and temperature extremes

Participants in the publication
Frederico Johannsen (Author)
IDL
Pedro M.M. Soares (Author)
Dep. Engenharia Geográfica, Geofísica e Energia
IDL
Gaby S. Langendijk (Author)

Date of Publication
2024-07

Where published
Urban Climate

Publication Identifiers
ISSN - 2212-0955

Publisher
Elsevier BV

Volume
56

Starting page
102039

Document Identifiers
DOI - https://doi.org/10.1016/j.uclim.2024.102039
URL - https://doi.org/10.1016/j.uclim.2024.102039

Rankings
Web Of Science Q1 (2023) - 6.0 - ENVIRONMENTAL SCIENCES
SCIMAGO Q1 (2023) - 1.318 - Environmental Science (miscellaneous)
SCOPUS Q1 (2023) - 9.7 - Environmental Science (miscellaneous)


Export

APA
Frederico Johannsen, Pedro M.M. Soares, Gaby S. Langendijk, (2024). On the deep learning approach for improving the representation of urban climate: The Paris urban heat island and temperature extremes. Urban Climate, 56, ISSN 2212-0955. eISSN . https://doi.org/10.1016/j.uclim.2024.102039

IEEE
Frederico Johannsen, Pedro M.M. Soares, Gaby S. Langendijk, "On the deep learning approach for improving the representation of urban climate: The Paris urban heat island and temperature extremes" in Urban Climate, vol. 56, 2024. 10.1016/j.uclim.2024.102039

BIBTEX
@article{64689, author = {Frederico Johannsen and Pedro M.M. Soares and Gaby S. Langendijk}, title = {On the deep learning approach for improving the representation of urban climate: The Paris urban heat island and temperature extremes}, journal = {Urban Climate}, year = 2024, volume = 56 }