2017

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

Helber, Patrick, Bischke, Benjamin, Dengel, Andreas et al.

Understand

In this paper, we address the challenge of land use and land cover classification using Sentinel-2 satellite images.

The Sentinel-2 satellite images are openly and freely accessible provided in the Earth observation program Copernicus.
We present a novel dataset based on Sentinel-2 satellite images covering 13 spectral bands and consisting out of 10 classes with in total 27,000 labeled and geo-referenced images.
We provide benchmarks for this novel dataset with its spectral bands using state-of-the-art deep Convolutional Neural Network (CNNs).

Built on

A practical guide to splines
C. De Boor, C. De Boor, E.-U. Mathématicien, C. De Boor, and C. De Boor · 1978
Earlier work this paper cites.
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
Earlier work this paper cites.
Structural high-resolution satellite image indexing
G.-S. Xia, W. Yang, J. Delon, Y. Gousseau, H. Sun, and H. Maître · 2010
Earlier work this paper cites.
Bag-of-visual-words and spatial extensions for land-use classification
Y. Yang and S. Newsam · 2010
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Earlier work this paper cites.
High-resolution satellite scene classification using a sparse coding based multiple feature combination
G. Sheng, W. Yang, T. Xu, and H. Sun · 2012
Earlier work this paper cites.
European Commission. Mapping guide for a European urban atlas. https://ec.europa.eu/regional_policy/sources/tender/pdf/2012066/annexe2.pdf , 2012
2012
Earlier work this paper cites.
Network in network
Original
M. Lin, Q. Chen, and S. Yan · 2013
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Original
K. Simonyan and A. Zisserman · 2014
Earlier work this paper cites.
Deepsat: a learning framework for satellite imagery
S. Basu, S. Ganguly, S. Mukhopadhyay, R. DiBiano, M. Karki, and R. Nemani · 2015
Earlier work this paper cites.
Land use classification in remote sensing images by convolutional neural networks
Original
M. Castelluccio, G. Poggi, C. Sansone, and L. Verdoliva · 2015
Earlier work this paper cites.
Multiview deep learning for land-use classification
F. P. Luus, B. P. Salmon, F. van den Bergh, and B. Maharaj · 2015
Earlier work this paper cites.
Large-scale deep learning on the yfcc100m dataset
Original
K. Ni, R. Pearce, K. Boakye, B. Van Essen, D. Borth, B. Chen, and E. Wang · 2015
Earlier work this paper cites.
Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?
O. A. Penatti, K. Nogueira, and J. A. dos Santos · 2015
Earlier work this paper cites.

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