Selsam, Peter; Lausch, Angela; Bumberger, Jan: Satellite Color Images, Vegetation Indices, and Metabolism Indices from Paderborn, Germany from 1985 – 2023 [dataset]. Helmholtz Centre for Environmental Research - UFZ, PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.972277 (dataset in review), In: Selsam, P et al.: Germany Mosaic: A 40-Year High-Resolution Remote Sensing Time Series of Germany [dataset publication series]. Helmholtz Centre for Environmental Research - UFZ, PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.967266 (dataset in review)
Abstract:
The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document.
The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications.
In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description).
Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.
Keyword(s):
Related to:
Selsam, Peter; Bumberger, Jan; Wellmann, Thilo; Pause, Marion; Gey, Ronny; Borg, Erik; Lausch, Angela (2024): Ecosystem Integrity Remote Sensing—Modelling and Service Tool—ESIS/Imalys. Remote Sensing, 16(7), 1139, https://doi.org/10.3390/rs16071139
Selsam, Peter; Gey, Ronny; Lausch, Angela; Bumberger, Jan (2023): Imalys - Image Analysis [software]. Zenodo, https://doi.org/10.5281/ZENODO.8116370
Related code / software:
Selsam, Peter (2024): Imalys – ESIS tool for Image Analysis. https://github.com/c7sepe2/Imalys_ESIS-Software-Tools
Documentation:
Further details:
Coverage:
Median Latitude: 51.798651 * Median Longitude: 8.998936 * South-bound Latitude: 51.598673 * West-bound Longitude: 8.665652 * North-bound Latitude: 51.998628 * East-bound Longitude: 9.332221
Date/Time Start: 1985-05-01T00:00:00 * Date/Time End: 2023-10-31T00:00:00
Event(s):
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Area/locality | Area | ||||
| 2 | Year of observation | Year obs | a AD | |||
| 3 | Date/time start | Date/time start | ||||
| 4 | Date/time end | Date/time end | ||||
| 5 | File content | Content | ||||
| 6 | Raster graphic, GeoTIFF format | GeoTIFF | ||||
| 7 | Geospatial vector, shapefiles | Shapefile | ||||
| 8 | File type | File type | ||||
| 9 | Site information | Site info |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0) (License comes into effect after moratorium ends)
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
2184 data points
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