metadata

dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': arbor woodland
            '1': artificial grassland
            '2': dry cropland
            '3': garden plot
            '4': industrial land
            '5': irrigated land
            '6': lake
            '7': natural grassland
            '8': paddy field
            '9': pond
            '10': river
            '11': rural residential
            '12': shrub land
            '13': traffic land
            '14': urban residential
  splits:
    - name: train
      num_bytes: 1777210275
      num_examples: 30000
  download_size: 1263253291
  dataset_size: 1777210275
license: other
task_categories:
  - image-classification
  - zero-shot-image-classification

Dataset Card for "GID"

Dataset Description

Paper Land-cover classification with high-resolution remote sensing images using transferable deep models

Licensing Information

Public domain.

Citation Information

Land-cover classification with high-resolution remote sensing images using transferable deep models

@article{GID2020,
  title        = {Land-cover classification with high-resolution remote sensing images using transferable deep models},
  author       = {Tong, Xin-Yi and Xia, Gui-Song and Lu, Qikai and Shen, Huanfeng and Li, Shengyang and You, Shucheng and Zhang, Liangpei},
  year         = 2020,
  journal      = {Remote Sensing of Environment},
  volume       = 237,
  pages        = 111322
}