EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 12; no. 7; pp. 2217 - 2226
• Main Authors: Helber, Patrick, Bischke, Benjamin, Dengel, Andreas, Borth, Damian
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; Band spectra; Benchmark testing; Benchmarks; Classification; Dataset; Datasets; deep convolutional neural network; Deep learning; Earth; earth observation; Feature extraction; Image classification; Land cover; land cover classification; Land use; land use classification; Machine learning; Neural networks; Remote sensing; satellite image classification; Satellite imagery; satellite images; Satellites; Spaceborne remote sensing; Spatial resolution; Spectral bands

In this paper, we present a patch-based land use and land cover classification approach using Sentinel-2 satellite images. The Sentinel-2 satellite images are openly and freely accessible, and are provided in the earth observation program Copernicus. We present a novel dataset, based on these images...