Satellite Color Images, Vegetation Indices, and Metabolism Indices from Bad Tölz, 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）”是一套涵盖1984年至2023年全德国境内的陆地卫星（Landsat）时序影像与矢量化分割地块数据集。该影像数据按TK100分幅进行切割（详细信息参见：1:10万比例尺地形图分幅规则（Blattschnitt der Topographischen Karte 1:100 000））。数据集为每一年提供了优化后的6波段影像，涵盖夏季（5月至7月）与秋季（8月至10月）两个时段，同时同步提供对应时期的植被指数产品，包括归一化植被指数（NDVI，Normalized Difference Vegetation Index）与近红外植被反射率（NirV，Near-Infrared Reflectance of Vegetation）。此外，数据集还提供了各年份下近似均质像元的矢量化“地块”。影像数据的光谱属性与这些地块的形态学特征均被纳入矢量化属性字段（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，用于展示所有分幅数据的覆盖范围与质量概况。“德国马赛克”亦可被视为一个时空数据立方体（spatial-temporal Data Cube），支持面向多维数据需求的高级分析与工作流集成。该结构允许用户执行特定时段数据查询、数十年趋势分析，或聚合空间信息以生成适配各类研究应用的定制化洞察结果。在中纬度地区，植被的季节变化——进而影像数据的季节变化——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），划分为夏季与秋季时段以捕捉自然生境的季节性代谢变化，同时也可记录绝大多数农业活动（如播种与收获）的变化信息。根据天气条件，单幅影像数据可代表指定时段内的影像中值、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工具。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，该数据集支持虚拟生态系统建模，助力可持续管理相关的模拟、情景测试与预测分析。此外，遥感参数所捕获的时空趋势可补充传统生物学、生态学、地理学与流行病学研究的分析方法。