Abstract. Alpine ecosystems are experiencing rapid change as a result of warming temperatures and changes in the quantity, timing and phase of precipitation. This in turn impacts patterns and processes of ecohydrologic connectivity, vegetation productivity and water provision to downstream regions. The fine-scale heterogeneous nature of these environments makes them challenging areas to measure with traditional instrumentation and spatiotemporally coarse satellite imagery. This paper describes the data collection, processing, accuracy assessment and availability of a series of approximately weekly-interval uncrewed-aerial-system (UAS) surveys flown over the Niwot Ridge Long Term Ecological Research site during the 2017 summer-snowmelt season. Visible, near-infrared and thermal-infrared imagery was collected. This unique series of 5–25 cm resolution multi-spectral and thermal orthomosaics provides a unique snapshot of seasonal transitions in a high alpine catchment. Weekly radiometrically calibrated normalised difference vegetation index maps can be used to track vegetation health at the pixel scale through time. Thermal imagery can be used to map the movement of snowmelt across and within the near sub-surface as well as identify locations where groundwater is discharging to the surface. A 10 cm resolution digital surface model and dense point cloud (146 points m−2) are also provided for topographic analysis of the snow-free surface. These datasets augment ongoing data collection within this heavily studied and important alpine site; they are made publicly available to facilitate wider use by the research community. Datasets and related metadata can be accessed through the Environmental Data Initiative Data Portal, https://doi.org/10.6073/pasta/dadd5c2e4a65c781c2371643f7ff9dc4 (Wigmore, 2022a), https://doi.org/10.6073/pasta/073a5a67ddba08ba3a24fe85c5154da7 (Wigmore, 2022c), https://doi.org/10.6073/pasta/a4f57c82ad274aa2640e0a79649290ca (Wigmore and Niwot Ridge LTER, 2021a), https://doi.org/10.6073/pasta/444a7923deebc4b660436e76ffa3130c (Wigmore and Niwot Ridge LTER, 2021b), https://doi.org/10.6073/pasta/1289b3b41a46284d2a1c42f1b08b3807 (Wigmore and Niwot Ridge LTER, 2022a), https://doi.org/10.6073/pasta/70518d55a8d6ec95f04f2d8a0920b7b8 (Wigmore and Niwot Ridge LTER, 2022b). A summary of the available datasets can be found in the data availability section below.

中文翻译：

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科罗拉多州尼沃特岭夏季融雪期间高山集水区的每周高分辨率多光谱和热无人航空系统测绘

摘要。由于气温变暖以及降水量、时间和阶段的变化，高山生态系统正在经历快速变化。这反过来会影响生态水文连通性、植被生产力和下游地区供水的模式和过程。这些环境的精细尺度异构性质使它们具有挑战性的区域，无法使用传统仪器和时空粗糙的卫星图像进行测量。本文介绍了 2017 年夏季融雪季节期间在 Niwot Ridge 长期生态研究站点上空飞行的一系列大约每周一次的无人驾驶航空系统 (UAS) 调查的数据收集、处理、准确性评估和可用性。收集了可见光、近红外和热红外图像。这个独特的 5-25 厘米分辨率多光谱和热正射镶嵌系列提供了高山集水区季节性转变的独特快照。每周辐射校准的归一化植被指数图可用于跟踪像素尺度的植被健康状况。热成像可用于绘制融雪在近地表下和内部的运动图，以及确定地下水排放到地表的位置。还提供了 10 厘米分辨率的数字表面模型和密集点云（146 点 m−2），用于无雪表面的地形分析。这些数据集增强了这个经过大量研究的重要高山站点内正在进行的数据收集；它们被公开提供，以促进研究界的更广泛使用。数据集和相关元数据可通过环境数据倡议数据门户访问，https://doi.org/10.6073/pasta/dadd5c2e4a65c781c2371643f7ff9dc4（Wigmore，2022a），https://doi.org/10.6073/pasta/073a5a67ddba08ba3a24fe85c5154,da7（Wigmore 2022c), https://doi.org/10.6073/pasta/a4f57c82ad274aa2640e0a79649290ca (Wigmore 和 Niwot Ridge LTER, 2021a), https://doi.org/10.6073/pasta/444a7923deebc4b660436e76ffa3130c (Wigmore 和 Niwot Ridge LTER, 2021a), Ridmore 和 LTER20c https ://doi.org/10.6073/pasta/1289b3b41a46284d2a1c42f1b08b3807（Wigmore 和 Niwot Ridge LTER，2022a），https://doi.org/10.6073/pasta/70518d55a8d6ec95f04f2d8a0920b7b8（Wigmore 和 Niwot Ridge LTER2）。可以在下面的数据可用性部分找到可用数据集的摘要。6073/pasta/dadd5c2e4a65c781c2371643f7ff9dc4（威格莫尔，2022a），https://doi.org/10.6073/pasta/073a5a67ddba08ba3a24fe85c5154da7（威格莫尔，2022c），https://doi.org/10.6073/pasta/pasta e0a79649290ca（Wigmore 和 Niwot Ridge LTER， 2021a), https://doi.org/10.6073/pasta/444a7923deebc4b660436e76ffa3130c (Wigmore 和 Niwot Ridge LTER, 2021b), https://doi.org/10.6073/pasta/1289b3b41a46284d2a1c42f1b08b3802一）、https ://doi.org/10.6073/pasta/70518d55a8d6ec95f04f2d8a0920b7b8（Wigmore 和 Niwot Ridge LTER，2022b）。可以在下面的数据可用性部分找到可用数据集的摘要。6073/pasta/dadd5c2e4a65c781c2371643f7ff9dc4（威格莫尔，2022a），https://doi.org/10.6073/pasta/073a5a67ddba08ba3a24fe85c5154da7（威格莫尔，2022c），https://doi.org/10.6073/pasta/pasta e0a79649290ca（Wigmore 和 Niwot Ridge LTER， 2021a), https://doi.org/10.6073/pasta/444a7923deebc4b660436e76ffa3130c (Wigmore 和 Niwot Ridge LTER, 2021b), https://doi.org/10.6073/pasta/1289b3b41a46284d2a1c42f1b08b3802一）、https ://doi.org/10.6073/pasta/70518d55a8d6ec95f04f2d8a0920b7b8（Wigmore 和 Niwot Ridge LTER，2022b）。可以在下面的数据可用性部分找到可用数据集的摘要。2021a), https://doi.org/10.6073/pasta/444a7923deebc4b660436e76ffa3130c (Wigmore 和 Niwot Ridge LTER, 2021b), https://doi.org/10.6073/pasta/1289b3b41a46284d2a1c42f1b08b3802一）、https ://doi.org/10.6073/pasta/70518d55a8d6ec95f04f2d8a0920b7b8（Wigmore 和 Niwot Ridge LTER，2022b）。可以在下面的数据可用性部分找到可用数据集的摘要。2021a), https://doi.org/10.6073/pasta/444a7923deebc4b660436e76ffa3130c (Wigmore 和 Niwot Ridge LTER, 2021b), https://doi.org/10.6073/pasta/1289b3b41a46284d2a1c42f1b08b3802一）、https ://doi.org/10.6073/pasta/70518d55a8d6ec95f04f2d8a0920b7b8（Wigmore 和 Niwot Ridge LTER，2022b）。可以在下面的数据可用性部分找到可用数据集的摘要。