Satellite Color Images, Vegetation Indices, and Metabolism Indices from Schlüchtern, Germany from 1984 – 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）”数据集是一套覆盖全德国、时间跨度为1984年至2023年的陆地卫星（Landsat）时序影像与矢量化分割成果。该影像数据按TK100分幅组织（详见：1:10万地形图分幅（Blattschnitt der Topographischen Karte 1:100 000））。数据集为每一年度提供优化后的6波段影像，覆盖夏季（5月至7月）与秋季（8月至10月）两个时段，同时同步提供同期的植被指数产品，包括归一化差分植被指数（Normalized Difference Vegetation Index，简称NDVI）与植被近红外反射率（Near-Infrared Reflectance of Vegetation，简称NirV）。此外，数据集还提供各年份的近似同质像素矢量化“区域”产品。影像数据的光谱特性与这些区域的形态学特征均以矢量属性形式存储（详见文档"Mosaic (1984–2023) - Data Description"）。本文档中，所有分幅的覆盖范围与质量情况以矢量图层形式呈现，该图层命名为D-Mosaik_Sheet-Sections。
德国马赛克数据集亦可视作一个时空数据立方体，支持开展高阶空间分析并集成至存在多维数据需求的工作流中。该数据结构支持用户执行特定时段数据查询、数十年尺度趋势分析，或聚合空间信息以生成定制化研究洞察，适配广泛的科研应用场景。
中纬度地区的植被季节变化——进而反映在影像数据中的变化——通常比多年间的变化更为显著。本数据集的时序分割方案设计为覆盖完整植被生长期（5月至10月），划分为夏季与秋季两个时段以捕捉自然生境的季节性代谢动态变化，同时也可记录绝大多数农业活动变化，包括播种与收获作业。受天气条件影响，单幅影像数据为对应时段的中值、均值或最优可用影像（详见文档"Mosaic (1984–2023) - Data Description"）。
遥感技术已成为环境研究，尤其是景观分析领域不可或缺的技术手段。除常规应用外，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。通过提供精细的时空数据，该数据集可用于虚拟生态系统建模，助力可持续管理相关的模拟、情景推演与预测分析。此外，遥感参数所捕捉的时空趋势可与生物学、生态学、地理学与流行病学研究中的传统研究方法形成互补。