image
array 3D
label
class label
10 classes
filename
stringlengths
11
29
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0Annual Crop
AnnualCrop_1.tif
[[[1133,902,1046,597,1295,4093,5159,4969,1899,15,1215,564,5361],[1133,902,1046,597,1295,4093,5159,49(...TRUNCATED)
0Annual Crop
AnnualCrop_10.tif
[[[1387,1035,997,741,1143,2908,3547,3443,765,14,2315,1206,3868],[1387,1035,997,741,1143,2908,3547,34(...TRUNCATED)
0Annual Crop
AnnualCrop_100.tif
[[[1712,1698,1860,2289,2434,2875,3197,3073,721,15,4034,3035,3524],[1712,1698,1860,2289,2434,2875,319(...TRUNCATED)
0Annual Crop
AnnualCrop_1000.tif
[[[1301,986,888,560,910,2860,3991,3722,1079,13,1532,713,4247],[1301,986,888,560,910,2860,3991,3722,1(...TRUNCATED)
0Annual Crop
AnnualCrop_1001.tif
[[[1240,1174,1194,1646,1795,2191,2596,2823,902,12,2094,1130,3228],[1240,1174,1194,1646,1795,2191,259(...TRUNCATED)
0Annual Crop
AnnualCrop_1004.tif
[[[1252,1005,943,712,924,2362,3146,2811,562,9,1833,866,3416],[1252,1005,943,712,924,2362,3146,2811,5(...TRUNCATED)
0Annual Crop
AnnualCrop_1005.tif
[[[1446,1330,1314,1690,1847,2177,2543,2534,672,14,2568,1453,3089],[1446,1330,1314,1690,1847,2177,254(...TRUNCATED)
0Annual Crop
AnnualCrop_1006.tif
[[[1391,1112,1085,1221,1675,2240,2639,2528,767,15,2862,1552,3141],[1391,1112,1085,1221,1675,2240,263(...TRUNCATED)
0Annual Crop
AnnualCrop_1009.tif
[[[1570,1636,1871,2822,3120,3601,4190,4215,1058,17,4363,2346,4974],[1570,1636,1871,2822,3120,3601,41(...TRUNCATED)
0Annual Crop
AnnualCrop_1010.tif

EuroSAT MSI

EuroSAT MSI

EUROSAT is a classification dataset based on Sentinel-2 satellite images covering 13 spectral bands and consisting of 10 classes with 27000 labeled and geo-referenced samples.

Description

The EuroSAT dataset is a comprehensive land cover classification dataset that focuses on images taken by the ESA Sentinel-2 satellite. It contains a total of 27,000 images, each with a resolution of 64x64 pixels. These images cover 10 distinct land cover classes and are collected from over 34 European countries.

The dataset is available in two versions: RGB only and all 13 (this repo) Multispectral (MS) Sentinel-2 bands. EuroSAT is considered a relatively easy dataset, with approximately 98.6% accuracy achievable using a ResNet-50 architecture.

  • Total Number of Images: 27000
  • Bands: 13 (MSI)
  • Image Resolution: 64x64m
  • Land Cover Classes: 10
  • Classes: Annual Crop, Forest, Herbaceous Vegetation, Highway, Industrial Buildings, Pasture, Permanent Crop, Residential Buildings, River, SeaLake

Usage

To use this dataset, simply use datasets.load_dataset("blanchon/EuroSAT_MSI").

from datasets import load_dataset
EuroSAT_MSI = load_dataset("blanchon/EuroSAT_MSI")

Citation

If you use the EuroSAT dataset in your research, please consider citing the following publication:

@article{helber2017eurosat,
   title={EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification},
   author={Helber, et al.},
   journal={ArXiv preprint arXiv:1709.00029},
   year={2017}
}
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