Department of Earth and Environment, Boston University, Boston, USA.
School of Informatics, Computing & Cyber Systems, Northern Arizona University, Flagstaff, USA.
Sci Data. 2022 Jul 27;9(1):448. doi: 10.1038/s41597-022-01570-5.
Vegetation phenology is a key control on water, energy, and carbon fluxes in terrestrial ecosystems. Because vegetation canopies are heterogeneous, spatially explicit information related to seasonality in vegetation activity provides valuable information for studies that use eddy covariance measurements to study ecosystem function and land-atmosphere interactions. Here we present a land surface phenology (LSP) dataset derived at 3 m spatial resolution from PlanetScope imagery across a range of plant functional types and climates in North America. The dataset provides spatially explicit information related to the timing of phenophase changes such as the start, peak, and end of vegetation activity, along with vegetation index metrics and associated quality assurance flags for the growing seasons of 2017-2021 for 10 × 10 km windows centred over 104 eddy covariance towers at AmeriFlux and National Ecological Observatory Network (NEON) sites. These LSP data can be used to analyse processes controlling the seasonality of ecosystem-scale carbon, water, and energy fluxes, to evaluate predictions from land surface models, and to assess satellite-based LSP products.
植被物候学是控制陆地生态系统水分、能量和碳通量的关键因素。由于植被冠层具有异质性，因此与植被活动季节性相关的空间显式信息为利用涡度相关测量来研究生态系统功能和陆地-大气相互作用的研究提供了有价值的信息。在这里，我们提供了一个源自 PlanetScope 影像的陆地表面物候学（LSP）数据集，该数据集在北美范围内的多种植物功能类型和气候条件下，以 3 米的空间分辨率呈现。该数据集提供了与物候期变化时间相关的空间显式信息，例如植被活动的开始、峰值和结束，以及 2017 年至 2021 年生长季节的植被指数指标和相关质量保证标志，这些信息的时间窗口为 104 个 AmeriFlux 和国家生态观测网络（NEON）站点的涡度协方差塔的中心 10×10 公里。这些 LSP 数据可用于分析控制生态系统尺度碳、水和能量通量季节性的过程，评估来自土地表面模型的预测，并评估基于卫星的 LSP 产品。
