globalchange  > 气候变化与战略
DOI: 10.1016/j.envsoft.2020.104631
论文题名:
Visualizing and labeling dense multi-sensor earth observation time series: The EO Time Series Viewer
作者: Jakimow B.; van der Linden S.; Thiel F.; Frantz D.; Hostert P.
刊名: Environmental Modelling and Software
ISSN: 13648152
出版年: 2020
卷: 125
语种: 英语
英文关键词: Change detection ; EO time series viewer ; Open-source ; QGIS plugin ; Training ; Validation
Scopus关键词: Application programs ; Land use ; Observatories ; Open source software ; Personnel training ; Time series ; Visualization ; Change detection ; EO time series viewer ; Open sources ; Plug-ins ; Validation ; Data visualization ; ArcGIS ; calibration ; detection method ; instrumentation ; model validation ; observational method ; satellite data ; sensor ; software ; time series ; training ; visualization
英文摘要: Multi-spectral spaceborne sensors with different spatial resolutions produce Earth observation (EO) time series (TS) with global coverage. The interactive visualization and interpretation of TS is essential to better understand changes in land-use and land-cover and to extract reference information for model calibration and validation. However, available software tools are often limited to specific sensors or optimized for application-specific visualizations. To overcome these limitations, we developed the EO Time Series Viewer, a free and open source QGIS plugin for user-friendly visualization, interpretation and labeling of multi-sensor TS data. The EO Time Series Viewer (i) combines advantages of spatial, spectral and temporal data visualization concepts that are so far not available in a single tool, (ii) provides maximum flexibility in terms of supported data formats, (iii) minimizes the user-interactions required to load and visualize multi-sensor TS data and (iv) speeds-up labeling of TS data based on enhanced GIS vector tools and formats. © 2020 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/158982
Appears in Collections:气候变化与战略

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作者单位: Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin, 10099, Germany; Department of Geography and Geology, University of Greifswald, Friedrich-Ludwig-Jahn-Str. 16, Greifswald, 17489, Germany; Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin, 10099, Germany

Recommended Citation:
Jakimow B.,van der Linden S.,Thiel F.,et al. Visualizing and labeling dense multi-sensor earth observation time series: The EO Time Series Viewer[J]. Environmental Modelling and Software,2020-01-01,125
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