- AutorIn
- Katharina Anders 3DGeo Research Group, Heidelberg University, Germany#Department of Aerospace and Geodesy, TUM School of Engineering and Design, Technical University of Munich, Germany
- Bernhard Höfle3DGeo Research Group, Heidelberg University, Germany
- Sina Zumstein3DGeo Research Group, Heidelberg University, Germany
- Jakub Dvořák
- Krzysztof Gryguc
- Lucie Kupková
- Adriana Marcinkowska-Ochtyra
- Andreas Mayr
- Adrian Ochtyra
- Markéta Potůčková
- Martin Rutzinger
- Titel
- Time Series Analysis of 3D/4D Point Clouds within the Open-Source Online Course E-TRAINEE
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-984931
- Konferenz
- 5th Virtual Geoscience Conference. Dresden, 21. - 22. September 2023
- Quellenangabe
- VGC 2023 - Unveiling the dynamic Earth with digital methods
Herausgeber: Helmholtz-Institut Freiberg für Ressourcentechnologie
Herausgeber: Technische Universität Dresden
Erscheinungsort: Dresden
Erscheinungsjahr: 2023
Seiten: 22-23 - Erstveröffentlichung
- 2023
- DOI
- https://doi.org/10.25368/2025.163
- Abstract (EN)
- Analyzing time series of remote sensing data has become an essential but challenging task of current research and many applications of environmental monitoring and understanding human-environment interactions. Besides global Earth observation programs which provide extensive image archives, point cloud data are becoming increasingly available at local to national scales. Depending on the survey purpose and properties (i.e., sensor and platform), laser scanning or photogrammetric acquisitions are repeated at annual or seasonal timescales, down to daily and hourly observations in fixed monitoring settings.
- Freie Schlagwörter (DE)
- Änderungsanalyse, topografische Überwachung, Fernerkundung, Lehre, E-Learning
- Freie Schlagwörter (EN)
- change analysis, topographic monitoring, remote sensing, teaching, e-learning
- Klassifikation (DDC)
- 550
- Klassifikation (RVK)
- RB 10081
- Herausgeber (Institution)
- Helmholtz-Institut Freiberg für Ressourcentechnologie, Freiberg
- Technische Universität Dresden, Dresden
- Förder- / Projektangaben
- European Commission (EC)
ERASMUS+ | Cooperation for innovation and the exchange of good practices | Strategic Partnerships for higher education
E-learning course on Time Series Analysis in Remote Sensing for Understanding Human-Environment Interactions
ID: 2020-1-CZ01-KA203-078308 - Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-984931
- Veröffentlichungsdatum Qucosa
- 15.08.2025
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY 4.0