37 lines
1.8 KiB
Markdown
37 lines
1.8 KiB
Markdown
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## Cropland-CD
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The pytorch implementation for **MSCANet** in paper "[A CNN-transformer Network with Multi-scale Context Aggregation for Fine-grained Cropland Change Detection](https://ieeexplore.ieee.org/document/9780164)" on [IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing](https://www.grss-ieee.org/publications/journal-of-selected-topics-in-applied-earth-observations-and-remote-sensing/).
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## Requirements
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- Python 3.6
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- Pytorch 1.7.0
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## Datasets
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### CropLand Change Dection (CLCD) Dataset
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The CLCD dataset consists of 600 pairs image of cropland change samples, with 360 pairs for training, 120 pairs for validation and 120 pairs for testing.
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The bi-temporal images in CLCD were collected by Gaofen-2 in Guangdong Province, China, in 2017 and 2019, respectively, with spatial resolution ranged from 0.5 to 2 m. Each group of samples is composed of two images of 512 × 512 and a corresponding binary label of cropland change.
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- Download the CLCD Dataset: [OneDrive](https://mail2sysueducn-my.sharepoint.com/:f:/g/personal/liumx23_mail2_sysu_edu_cn/Ejm7aufQREdIhYf5yxSZDIkBr68p2AUQf_7BAEq4vmV0pg?e=ZWI3oy) | [Baidu](https://pan.baidu.com/s/1Un-bVxUm1N9IHiDOXLLHlg?pwd=miu2)
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- Download the [HRSCD Dataset](https://ieee-dataport.org/open-access/hrscd-high-resolution-semantic-change-detection-dataset)
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## Citation
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Please cite our paper if you use this code in your work:
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```
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@ARTICLE{9780164,
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author={Liu, Mengxi and Chai, Zhuoqun and Deng, Haojun and Liu, Rong},
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journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
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title={A CNN-Transformer Network With Multiscale Context Aggregation for Fine-Grained Cropland Change Detection},
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year={2022},
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volume={15},
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number={},
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pages={4297-4306},
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doi={10.1109/JSTARS.2022.3177235}}
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```
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