AI-based plant phenology mapping and analysis using satellite imagery and meteorological data

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published

Published in:: Abstracts of the ICA
Vol. 10.2025 (12.12.2025), art. no. 145, p. 1-3
Volume:: 10.2025
Publication date:: 12.12.2025
URN:: urn:nbn:de:0307-20260210-004-9
DOI:: 10.5194/ica-abs-10-145-2025
Language:: English
Type of Resource:: Text
Extent:: 1 Online-Ressource (Seite 1-3, 838,14 kB) : 3 Illustrationen, 1 Textdatei (PDF)
Keywords:: Remote Sensing; Climate Change; Phenology; Artificial Intelligence; Phenology Map; Fernerkundung^GND; Klimaänderung^GND; Phänologie^GND; Künstliche Intelligenz^GND; Phänologiekarte
DDC subject of DNB:: 520 Astronomy & allied sciences
URL:: https://doi.org/10.5194/ica-abs-10-145-2025
URL:: https://ica-abs.copernicus.org/articles/10/145/2025/
Link to Raw Object:: https://ica-abs.copernicus.org/articles/10/145/2025/ica-abs-10-145-2025.pdf
Hosting institution:: Pukyong National University (PKNU) [KR]
Hosting institution:: Internationale Forschungseinrichtungen
Statement of responsibility:: Geunah Kim, Yangwon Lee
Bibliographic notes:: Published in: Abstracts of the ICA, Volume 10, 2025 - 32nd International Cartographic Conference (ICC 2025); 17–22 August 2025, Vancouver, Canada; Editors: Mir Abolfazl Mostafavi, Jonathan Li, and Emmanuel Stefanakis | https://ica-abs.copernicus.org/articles/10/index.html