Deep learning for 250m resolution annual land cover mapping from 2010 to 2024 in Canada using MODIS time-series data

Category

Published in:

Abstracts of the ICA
Vol. 10.2025 (12.12.2025), art. no. 62, p. 1-2

Volume:

10.2025

Publication date:

12.12.2025

URN:

urn:nbn:de:0307-20260122-003-2

DOI:

10.5194/ica-abs-10-62-2025

Language:

English

Type of Resource:

Text

Extent:

1 Online-Ressource (Seite 1-2, 977,91 kB) : 2 Illustrationen, 1 Textdatei (PDF)

Keywords:

Land cover change detection; MODIS MOD13Q1; Deep Learning^GND; Transition matrices; 250m resolution Landsat product; Spatial-temporal residual neural network; Canadian land cover mapping; Feature extraction; Landbedeckungsänderung-Erkennung; Tiefgehendes Lernen; Übergangsmatrize; Landsat-Produkt für 250m-Auflösung; raum-zeitliches residuales neuronales Netzwerk; Kartierung der Landbedeckung in Kanada; Merkmalsextraktion^GND

DDC subject of DNB:

520 Astronomy & allied sciences

URL:

https://doi.org/10.5194/ica-abs-10-62-2025

URL:

https://ica-abs.copernicus.org/articles/10/62/2025/

Link to Raw Object:

https://ica-abs.copernicus.org/articles/10/62/2025/ica-abs-10-62-2025.pdf

Hosting institution:

University of Calgary (UC) [CA]

Hosting institution:

Internationale Forschungseinrichtungen

Statement of responsibility:

Zachary Dewis, Lincoln Linlin Xu

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