Datasets:
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---
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](https://www.sciencedirect.com/science/article/pii/S0034425719303414)
### Licensing Information
Public domain.
## Citation Information
[Land-cover classification with high-resolution remote sensing images using transferable deep models](https://www.sciencedirect.com/science/article/pii/S0034425719303414)
```
@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
}
``` |