Xuzhou HYSPEX dataset

The Xuzhou dataset was collected by an airborne HYSPEX hyperspectral camera over the Xuzhou peri-urban site in November 2014. This dataset consists of 500 × 260 pixels, with a very high spatial resolution of 0.73 m/pixel. The number of spectral bands used in the experiment was 436, after removing the noisy bands ranging from 415 nm to 2508 nm. The scene is peri-urban and is characterized by nine categories, including crops, vegetation, man-made structures, and coal fields The very high spatial resolution and the complex mixed categories make this dataset a challenging dataset for classification. If you think it helpful, we would appreciate if you cite these papers in your work.Tan K , Wu F , Du Q , et al. A Parallel Gaussian–Bernoulli Restricted Boltzmann Machine for Mining Area Classification With Hyperspectral Imagery[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019:1-10.Wang X, Tan K, Du Q, et al. Caps-TripleGAN: GAN-Assisted CapsNet for Hyperspectral Image Classification[J]. IEEE Trans. Geoscience and Remote Sensing 2019, 1–14.

徐州数据集由一架搭载于航空平台上的HYSPEX高光谱相机于2014年11月在徐州近郊地区采集而成。该数据集包含500×260像素，具有极高的空间分辨率，每像素分辨率为0.73米。实验中使用的光谱波段数量为436个，经过去除噪声波段（波长范围从415纳米至2508纳米）后得到。场景为近郊地带，特征分为九类，包括农作物、植被、人造结构以及煤矿等。极高的空间分辨率与复杂的混合类别使得该数据集成为分类任务中的挑战性数据集。如认为引用以下论文有助于工作，我们将不胜感激：Tan K, Wu F, Du Q, et al. A Parallel Gaussian–Bernoulli Restricted Boltzmann Machine for Mining Area Classification With Hyperspectral Imagery[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019:1-10. Wang X, Tan K, Du Q, et al. Caps-TripleGAN: GAN-Assisted CapsNet for Hyperspectral Image Classification[J]. IEEE Trans. Geoscience and Remote Sensing 2019, 1–14.

搜集汇总

背景与挑战

背景概述

Xuzhou HYSPEX数据集是一个用于高光谱图像分类的挑战性遥感数据集，采集自2014年徐州郊区，具有高空间分辨率（0.73米/像素）和436个光谱波段，覆盖九类复杂地物类别，包括作物、植被和人造结构等。该数据集以MATLAB格式提供，适用于地球科学与遥感领域的研究，尤其适合测试分类算法在混合场景中的性能。