Datasets:
				
			
			
	
			
			
	
		Tasks:
	
	
	
	
	Image Classification
	
	
	Formats:
	
	
	
		
	
	parquet
	
	
	Languages:
	
	
	
		
	
	English
	
	
	Size:
	
	
	
	
	10K - 100K
	
	
	ArXiv:
	
	
	
	
	
	
	
	
Tags:
	
	
	
	
	remote-sensing
	
	
	
	
	earth-observation
	
	
	
	
	geospatial
	
	
	
	
	satellite-imagery
	
	
	
	
	land-cover-classification
	
	
	
	
	sentinel-2
	
	
	License:
	
	
	
	
	
	
	
🤗 Add DatasetCard
Browse files
    	
        README.md
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            ---
         
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            language: en
         
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            license: unknown
         
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            size_categories:
         
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            - 10K<n<100K
         
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            task_categories:
         
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            - image-classification
         
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            paperswithcode_id: eurosat
         
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            pretty_name: EuroSAT RGB
         
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            tags:
         
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            - remote-sensing
         
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            - earth-observation
         
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            - geospatial
         
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            - satellite-imagery
         
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            - land-cover-classification
         
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            - sentinel-2
         
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            ---
         
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            # EuroSAT RGB
         
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            <!-- Dataset thumbnail -->
         
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            <!-- Provide a quick summary of the dataset. -->
         
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            EUROSAT RGB is the RGB version of the EUROSAT dataset based on Sentinel-2 satellite images covering 13 spectral bands and consisting of 10 classes with 27000 labeled and geo-referenced samples.
         
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            - **Paper:** https://arxiv.org/abs/1709.00029
         
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            - **Homepage:** https://github.com/phelber/EuroSAT
         
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            ## Description
         
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            <!-- Provide a longer summary of what this dataset is. -->
         
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            The EuroSAT dataset is a comprehensive land cover classification dataset that focuses on images taken by the [ESA Sentinel-2 satellite](https://sentinel.esa.int/web/sentinel/missions/sentinel-2). 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.
         
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            The dataset is available in two versions: **RGB only** (this repo) and all 13 [Multispectral (MS) Sentinel-2 bands](https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/resolutions/spatial). EuroSAT is considered a relatively easy dataset, with approximately 98.6% accuracy achievable using a ResNet-50 architecture.
         
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            - **Total Number of Images**: 27000
         
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            - **Bands**: 3 (RGB)
         
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            - **Image Resolution**: 64x64m
         
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            - **Land Cover Classes**: 10
         
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            - Classes: Annual Crop, Forest, Herbaceous Vegetation, Highway, Industrial Buildings, Pasture, Permanent Crop, Residential Buildings, River, SeaLake
         
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            ## Usage
         
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            To use this dataset, simply use `datasets.load_dataset("blanchon/EuroSAT_RGB")`.
         
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            <!-- Provide any additional information on how to use this dataset. -->
         
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            ```python
         
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            from datasets import load_dataset
         
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            EuroSAT_RGB = load_dataset("blanchon/EuroSAT_RGB")
         
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            ```
         
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            ## Citation 
         
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            <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
         
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            If you use the EuroSAT dataset in your research, please consider citing the following publication:
         
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            ```bibtex
         
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            @article{helber2017eurosat,
         
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               title={EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification},
         
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               author={Helber, et al.},
         
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               journal={ArXiv preprint arXiv:1709.00029},
         
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               year={2017}
         
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            }
         
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            ```
         
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