The pytorch implementation for MSCANet in paper "A CNN-transformer Network with Multi-scale Context Aggregation for Fine-grained Cropland Change Detection" on IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
- Python 3.6
- Pytorch 1.7.0
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. 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.
- Download the CLCD Dataset: OneDrive | Baidu
- Download the HRSCD Dataset
Please cite our paper if you use this code in your work:
@ARTICLE{9780164,
author={Liu, Mengxi and Chai, Zhuoqun and Deng, Haojun and Liu, Rong},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title={A CNN-Transformer Network With Multiscale Context Aggregation for Fine-Grained Cropland Change Detection},
year={2022},
volume={15},
number={},
pages={4297-4306},
doi={10.1109/JSTARS.2022.3177235}}