Controllably Deep Supervision and Multi-Scale Feature Fusion Network for Cloud and Snow Detection Based on Medium- and High-Resolution Imagery Dataset

Contents

• CSD-Net
• Requirements
• Setup
• CSWV
• Dataset Access
• Citation

CSD-Net

•     In our work, a convolutional neural network named CSD-Net 🚀🚀🚀was proposed for cloud and snow detection in medium- and high-resolution satellite images of distinct sensors.

Requirements

• Python 3.7
• Pytorch 1.8+ & CUDA&CUDNN with corresponding version

Setup

• Clone this repository.

git clone https://github.com/zhanggb1997/CSDNet-CSWV.git

CSWV

•     Additionally , a novel high-resolution cloud and snow dataset (CSWV) was created and released. It contains two sub-datasets: the submeter-level high-resolution cloud and snow dataset (CSWV_S6) comprises six scenes with a resolution of 0.5 m; the meter- level high-resolution cloud and snow dataset (CSWV_M21) includes 21 resampled scenes with a resolution of 1–10 m.

DatasetAccess

•     The full CSWV dataset can be downloaded at Baidu Disk (password: cswv) or Google Drive. Any questions, contact Mr. Guangbin Zhang 💌<202072509@Yangtzeu.edu.cn>. This dataset is shared for academic purpose only. If you use the dataset, you should appropriately cite our paper (PDF):

Citation

@article{RN306,
   author = {Zhang, Guangbin and Gao, Xianjun and Yang, Yuanwei and Wang, Mingwei and Ran, Shuhao},
   title = {Controllably Deep Supervision and Multi-Scale Feature Fusion Network for Cloud and Snow Detection Based on Medium- and High-Resolution Imagery Dataset},
   journal = {Remote Sensing},
   volume = {13},
   number = {23},
   ISSN = {2072-4292},
   DOI = {10.3390/rs13234805},
   year = {2021},
   type = {Journal Article}
}