IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing· 2019Q1
EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification
- 1,745citations
- Q1SCImago
- 2019year
Short summary
A new dataset, EuroSAT, featuring 27,000 labeled Sentinel-2 satellite images across 10 land use/cover classes, achieves 98.57% classification accuracy using deep convolutional neural networks.
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Key points
- Introduced EuroSAT, a new dataset with 27,000 labeled Sentinel-2 satellite images across 10 classes.
- The dataset utilizes 13 spectral bands from freely accessible Sentinel-2 imagery.
- Deep convolutional neural networks achieved 98.57% classification accuracy on the EuroSAT dataset.
- The dataset is made publicly available for earth observation applications.
AI-generated from the title and abstract; the full text is not read.
Abstract
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 that covers 13 spectral bands and is comprised of ten classes with a total of 27 000 labeled and geo-referenced images. Benchmarks are provided for this novel dataset with its spectral bands using state-of-the-art deep convolutional neural networks. An overall classification accuracy of 98.57% was achieved with the proposed novel dataset. The resulting classification system opens a gate toward a number of earth observation applications. We demonstrate how this classification system can be used for detecting land use and land cover changes, and how it can assist in improving geographical maps. The geo-referenced dataset EuroSAT is made publicly available at https://github.com/phelber/eurosat.
The authors' abstract, as published at the source. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019 · DOI ↗
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Field: Media Technology
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