NEON Teaching Data: Full Hyperspectral Image from SJER
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This is a full 1km by 1km tile of NEON AOP imaging spectrometer hyperspectral data from the San Joaquin Experimental Range in the central valley of California, USA. This dataset contains imagery at 1m spatial resolution, and ~5nm spectral resolution, with a total of 426 bands. These data were gathered in March, 2019. All NEON AOP missions are flown at or near peak 'greenness,' which comes fairly early in the year for this region. This dataset is uploaded here for teaching purposes, in particular with the tutorials found on https://www.neonscience.org/resources/data-tutorials. This particular tile makes for a good teaching example because this image captures a large school complex that is under construction, which means that it contains a wide variety of recognizable land cover types. Spectral signatures and indices derived from these surfaces make for good teaching examples because of their strong differences between land cover types. However, this file is rather large (~622Mb), so users may consider using our smaller (~50Mb) example subsets derived from this dataset. <br>Citation:National Ecological Observatory Network. 2020. Data Product DP3.30006.001, Spectrometer orthorectified surface directional reflectance - mosaic. Provisional data downloaded from http://data.neonscience.org on February 21, 2020. Battelle, Boulder, CO, USA NEON. 2020.<br>
本数据集为取自美国加利福尼亚州中央谷地圣华金实验牧场的完整1km×1km NEON AOP(美国国家生态观测网机载观测平台,National Ecological Observatory Network Airborne Observation Platform)成像光谱仪高光谱数据瓦片。该数据集空间分辨率为1米,光谱分辨率约5纳米,共包含426个波段。该批次数据采集于2019年3月。所有NEON AOP飞行任务均安排在植被峰值绿度期或临近时段开展,而该区域的植被峰值绿度期出现于每年较早阶段。本数据集上传至此用于教学用途,尤其适配https://www.neonscience.org/resources/data-tutorials平台上的配套教学教程。该瓦片适宜作为教学示例,原因在于其影像覆盖了一处在建的大型校区建筑群,因而包含多种易于辨识的土地覆盖类型。从这些地表提取的光谱特征与光谱指数,因不同土地覆盖类型间差异显著,同样适合作为教学示例。不过该文件体积较大(约622Mb),用户可选用本数据集衍生的小型示例子集(约50Mb)。
引用:美国国家生态观测网,2020年。数据产品DP3.30006.001:成像光谱仪正射校正地表方向反射率——镶嵌数据集。2020年2月21日从http://data.neonscience.org下载的临时数据。美国科罗拉多州博尔德市巴特尔纪念研究所(Battelle),NEON,2020年。
提供机构:
figshare
创建时间:
2020-02-24



