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marjandl
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BigEarthNet-19-HMLC

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Image Classification
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image_path Urban fabric Industrial or commercial units Arable land Permanent crops Pastures Complex cultivation patterns Land principally occupied by agriculture, with significant areas of natural vegetation Agro-forestry areas Broad-leaved forest Coniferous forest Mixed forest Natural grassland and sparsely vegetated areas Moors, heathland and sclerophyllous vegetation Transitional woodland, shrub Beaches, dunes, sands Inland wetlands Coastal wetlands Inland waters Marine waters Artificial surfaces Agricultural areas Heterogeneous agricultural areas Forests and semi-natural areas Forests Shrub and/or herbaceous vegetation association Wetlands Water bodies
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Extended label set of BigEarthNet-19 for Hierarchical Multi-Label Classification

This dataset contains an extended version of the original label set of BigEarthNet-19 for Hierarchical Multi-Label Classification.

Dataset creation

It was created based on the CORINE Land Cover database of the year 2018 (CLC 2018), which provides detailed information about the land cover classes at multiple levels of the hierarchy

Loading the Dataset

To load the dataset into your project, you can use the following code snippet:

import pandas as pd
from datasets import load_dataset

# Load the dataset from Hugging Face
dataset = load_dataset(
    "marjandl/BigEarthNet-19-HMLC", 
    split='train'
)

data = [line.split('\t')[1:] for line in dataset['text']]
df = pd.DataFrame(data)

# Set the first row as the header and drop it from the DataFrame
df.columns = df.iloc[0]
df = df.drop(0).reset_index(drop=True)
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Number of rows:
590,327