Satellite Color Images, Vegetation Indices, and Metabolism Indices from Gummersbach, Germany from 1985 – 2023

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.

“德国马赛克（Germany Mosaic）”是一套覆盖1984年至2023年全德国范围的陆地卫星（Landsat）时序影像与矢量化分割数据集。该影像数据按照TK100分幅进行划分（详见：1:10万比例尺地形图分幅（Blattschnitt der Topographischen Karte 1:100 000））。数据集为每年提供优化后的6波段影像，分别对应夏季（5月至7月）与秋季（8月至10月）两个时段，同时包含同期的归一化差分植被指数（NDVI, Normalized Difference Vegetation Index）以及植被近红外反射率（NirV, Near-Infrared Reflectance of Vegetation）等植被指数产品。此外，数据集还为每年提供近似同质像元的矢量化“区域”单元。影像数据的光谱特征与上述区域单元的形态学特征均作为矢量化属性字段收录其中（详见文档“Mosaic (1984–2023) - Data Description”）。本文件中还提供了名为D-Mosaik_Sheet-Sections的矢量化图层，用于展示所有分幅的覆盖范围与数据质量概况。德国马赛克数据集亦可被视为时空数据立方体（spatial-temporal Data Cube），支持针对多维数据需求开展高级分析与工作流集成。该结构支持用户开展各类操作，例如跨特定时段的数据查询、数十年尺度的趋势分析，或是聚合空间信息以生成适配多类科研应用的定制化研究结论。在中纬度地区，植被的季节变化——进而带动影像数据的变化——通常比多年间的变化更为显著。数据集的时序分割方案覆盖了完整的植被生长期（5月至10月），其中夏季与秋季的时段划分可捕捉自然生境的季节性代谢变化。该分割方案同时可记录绝大多数农业活动变化，例如播种与收割作业。根据天气条件的不同，单幅影像数据可选取指定时段内的中值、均值或是最优可用影像（详见文档“Mosaic (1984–2023) - Data Description”）。遥感技术现已成为环境科研领域不可或缺的工具，在景观分析场景中尤为如此。除常规应用场景外，德国马赛克数据集还可支撑环境系统研究中的数字孪生开发工作。凭借详实的时空数据支撑，该数据集可实现虚拟生态系统建模，为可持续管理相关的模拟、情景测试与预测分析提供便利。此外，遥感参数所捕获的时空趋势可补充生物学、生态学、地理学与流行病学研究中的传统分析方法。