Skip to main content
Dryad

HySpecNet-11k: A large-scale hyperspectral benchmark dataset

Cite this dataset

Fuchs, Martin Hermann Paul; Demir, Begüm (2023). HySpecNet-11k: A large-scale hyperspectral benchmark dataset [Dataset]. Dryad. https://doi.org/10.5061/dryad.fttdz08zh

Abstract

HySpecNet-11k is a large-scale hyperspectral benchmark dataset made up of 11,483 nonoverlapping image patches acquired by the EnMAP satellite. Each patch is a portion of 128 × 128 pixels with 224 spectral bands and with a ground sample distance of 30 m.

To construct HySpecNet-11k, a total of 250 EnMAP tiles acquired during the routine operation phase between 2 November 2022 and 9 November 2022 were considered. The considered tiles are associated with less than 10% cloud and snow cover. The tiles were radiometrically, geometrically and atmospherically corrected (L2A water & land product). Then, the tiles were divided into nonoverlapping image patches. The cropped patches at the borders of the tiles were eliminated. As a result, more than 45 patches per tile are obtained, resulting in 11,483 patches for the full dataset.

We provide predefined splits obtained by randomly dividing HySpecNet into: i) a training set that includes 70% of the patches, ii) a validation set that includes 20% of the patches, and iii) a test set that includes 10% of the patches. Depending on the way that we used for splitting the dataset, we define two different splits: i) an easy split, where patches from the same tile can be present in different sets (patchwise splitting); and ii) a hard split, where all patches from one tile belong to the same set (tilewise splitting).

Methods

For further details about HySpecNet-11k, please see our paper: M. H. P. Fuchs and B. Demіr, "HySpecNet-11k: A Large-Scale Hyperspectral Dataset for Benchmarking Learning-Based Hyperspectral Image Compression Methods", IEEE International Geoscience and Remote Sensing Symposium, Pasadena, California, 2023.

Usage notes

Funding

European Research Council