metadata

language: en
license: unknown
task_categories:
  - image-classification
paperswithcode_id: uc-merced-land-use-dataset
pretty_name: UC Merced
tags:
  - remote-sensing
  - earth-observation
  - geospatial
  - satellite-imagery
  - land-cover-classification
  - USGS National Map
  - USGS
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': agricultural
            '1': airplane
            '2': baseballdiamond
            '3': beach
            '4': buildings
            '5': chaparral
            '6': denseresidential
            '7': forest
            '8': freeway
            '9': golfcourse
            '10': harbor
            '11': intersection
            '12': mediumresidential
            '13': mobilehomepark
            '14': overpass
            '15': parkinglot
            '16': river
            '17': runway
            '18': sparseresidential
            '19': storagetanks
            '20': tenniscourt
  splits:
    - name: train
      num_bytes: 438356371.8
      num_examples: 2100
  download_size: 416445676
  dataset_size: 438356371.8
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

UC Merced

The UC Merced Land Use dataset is a land use classification dataset of 2.1k 256x256 1ft resolution RGB images of urban locations around the U.S. extracted from the USGS National Map Urban Area Imagery collection with 21 land use classes (100 images per class).

Paper: https://arxiv.org/abs/1911.06721
Homepage: http://weegee.vision.ucmerced.edu/datasets/landuse.html

Description

Total Number of Images: 2100
Bands: 3 (RGB)
Image Size: 256x256
Resolution: 0.3m
Land Cover Classes: 21
Classes: agricultural, airplane, baseballdiamond, beach, buildings, chaparral, denseresidential, forest, freeway, golfcourse, harbor, intersection, mediumresidential, mobilehomepark, overpass, parkinglot, river, runway, sparseresidential, storagetanks, tenniscourt
Source: USGS

Usage

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

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

Citation

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

@article{neumann2019indomain,
  title   = {In-domain representation learning for remote sensing},
  author  = {Maxim Neumann and Andre Susano Pinto and Xiaohua Zhai and Neil Houlsby},
  year    = {2019},
  journal = {arXiv preprint arXiv: 1911.06721}
}