E-TRAINEE: open E-learning course on time series analysis in remote sensing

• Verfasst von: Potůčková, Markéta [VerfasserIn]
• Verfasst von: Albrechtová, Jana [VerfasserIn]
• Verfasst von: Anders, Katharina [VerfasserIn]
• Verfasst von: Červená, Lucie [VerfasserIn]
• Verfasst von: Dvořák, Jakub [VerfasserIn]
• Verfasst von: Gryguc, Krzysztof [VerfasserIn]
• Verfasst von: Höfle, Bernhard [VerfasserIn]
• Verfasst von: Hunt, Lena [VerfasserIn]
• Verfasst von: Lhotáková, Zuzana [VerfasserIn]
• Verfasst von: Marcinkowska-Ochtyra, Adriana [VerfasserIn]
• Verfasst von: Mayr, Andreas [VerfasserIn]
• Verfasst von: Neuwirthová, Eva [VerfasserIn]
• Verfasst von: Ochtyra, Adrian [VerfasserIn]
• Verfasst von: Rutzinger, Martin [VerfasserIn]
• Verfasst von: Šedová, Adéla [VerfasserIn]
• Verfasst von: Šrollerů, Alex [VerfasserIn]
• Verfasst von: Kupková, Lucie [VerfasserIn]
• Titel: E-TRAINEE: open E-learning course on time series analysis in remote sensing
• Verf.angabe: Markéta Potůčková, Jana Albrechtová, Katharina Anders, Lucie Červená, Jakub Dvořák, Krzysztof Gryguc, Bernhard Höfle, Lena Hunt, Zuzana Lhotáková, Adriana Marcinkowska-Ochtyra, Andreas Mayr, Eva Neuwirthová, Adrian Ochtyra, Martin Rutzinger4, Adéla Šedová, Alex Šrollerů, Lucie Kupková
• E-Jahr: 2023
• Jahr: 13 Dec 2023
• Umfang: 8 S.
• Fussnoten: Gesehen am 11.04.2024
• Titel Quelle: Enthalten in: ISPRS Geospatial Week (2023 : Kairo)ISPRS Geospatial Week 2023
• Ort Quelle: Hannover : ISPRS, 2023
• Jahr Quelle: 2023
• Band/Heft Quelle: (2023), Seite 989-996
• DOI: doi:10.5194/isprs-archives-XLVIII-1-W2-2023-989-2023
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: 3D point cloud
• Sach-SW: E-learning
• Sach-SW: Image spectroscopy
• Sach-SW: Laboratory spectroscopy
• Sach-SW: Multispectral imagery
• Sach-SW: Open educational resources
• Sach-SW: Remote sensing
• Sach-SW: Time series analysis
• K10plus-PPN: 1885643284

Abstract

Time series (TS) analysis has always been an important topic in Remote Sensing (RS). Open access to archives of Earth Observation missions, periodically acquired nation-wide aerial imagery and LiDAR point clouds, and various research datasets, together with open tools for TS data processing, have brought new possibilities in RS research but also challenges in education. The topic of TS analysis in RS has become an essential part of MSc curricula in geoinformatics, geography, and related fields. Open learning materials systematically addressing the issue of TS at the master's level are rare and their development is time and resource demanding. Thus, based on previous collaboration, the four research groups from Charles University, Heidelberg University, University of Innsbruck, and University of Warsaw joint their specific expertise and developed an open E-learning course on Time Series Analysis in RS for Understanding Human-Environment Interactions (E-TRAINEE). The course consists of four Modules covering the topics of TS from general approaches (M1) to specific methods of processing TS of satellite multispectral images (M2), 3D/4D point clouds (M3), and aerial image and laboratory spectroscopy (M4). Theoretical parts are supported with exercises/tutorials and case studies based on research activities of the involved teams. The course is accessible via a web site and is published under the CC-BY SA 4.0 license. The primary target group are MSc and PhD students of geoinformatics and geography, but it is also relevant to students of environmental studies, ecology, or geology, as well as potential users from the public and private sectors dealing with applications of RS.