High-resolution hyperspectral images of Council, Alaska 2019

Hyperspectral data are gaining popularity in remote sensing and signal processing communities because of the increased spectral information relative to multispectral data. Several airborne and spaceborne hyperspectral datasets are publicly available, facilitating the development of various applications and algorithms. However, hyperspectral data are usually limited by their narrow, highly correlated, and contiguous spectral bands in both processing and analysis. Moreover, the resolution of available hyperspectral datasets is not sufficiently high for the identification of small objects. Nevertheless, with the rapidly advancing technology, hyperspectral imaging systems can now be mounted on small aerial vehicles for detecting small objects at low altitude. To properly handle these high spectral and spatial resolution data, new or redesigned data processing or analysis pipelines must be developed. However, such datasets are currently not publicly available. Therefore, we provide two hyperspectral datasets from GNSS/INS-assisted co-aligned pushbroom hyperspectral scanners on a drone. The hyperspectral datasets consist of raw/post-processed hyperspectral data, raw/post-processed Global Navigation System Satellite/Inertial Measurement Unit (GNSS/IMU) data, and digital surface models, and were radiometrically and geometrically evaluated. These datasets are expected to aid the improvement of UAV-based hyperspectral data processing and analysis algorithms.高光谱数据（hyperspectral data）相较于多光谱数据拥有更丰富的光谱信息，因此在遥感与信号处理领域愈发受到青睐。目前已有多款机载与星载高光谱数据集公开发布，为各类应用与算法的研发提供了支撑。然而，高光谱数据在处理与分析过程中，往往受限于其窄带、高度相关且连续的光谱波段特性。此外，现有公开高光谱数据集的分辨率不足以支持小型目标的识别任务。不过随着技术的快速进步，高光谱成像系统现已可搭载于小型航空器上，以实现低空小型目标探测。为妥善处理这类兼具高光谱与高空间分辨率的数据，亟需开发全新或经过优化重构的数据处理与分析流程。但目前这类数据集尚未公开。因此，我们发布了两款搭载于无人机（UAV）的、由全球导航卫星系统/惯性导航系统（GNSS/INS）辅助的共对准推扫式高光谱扫描仪采集的高光谱数据集。本数据集包含原始/后处理高光谱数据、原始/后处理全球导航卫星系统/惯性测量单元（GNSS/IMU）数据以及数字表面模型，并已完成辐射与几何性能评估。本数据集有望助力无人机载高光谱数据处理与分析算法的性能提升。