U.S. Geological Survey, Madison, WI, USA.
University of Wisconsin - Madison, Madison, WI, USA.
Sci Data. 2024 Jan 16;11(1):77. doi: 10.1038/s41597-024-02921-0.
Lake trophic state is a key ecosystem property that integrates a lake's physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.
湖泊营养状态是一个关键的生态系统属性，它综合了湖泊的物理、化学和生物过程。尽管营养状态作为衡量湖泊水质的标准很重要，但标准化和可机器读取的观测数据并不常见。遥感提供了一个机会，可以使用可重复、稳健的方法在时间和空间上检测和分析湖泊营养状态。我们使用陆地卫星表面反射率数据，为美国本土 55662 个至少 10 公顷的湖泊创建了第一个年度湖泊营养状态汇编，这些湖泊的数据可追溯到 1984 年至 2020 年。该数据集的构建考虑了 FAIR 数据原则（可查找、可访问、可互操作和可重复使用），其中数据是公开可用的，保留了来自父数据集的关系键，并且所有数据处理和建模例程都被编写为将来的重复使用。总的来说，该资源提供了关键数据，可在一系列空间和时间尺度上解决有关湖泊水质的基础研究和应用研究问题。
