Xiao An

State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing

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Guangyi Yang

Wuhan University

Hongyan Zhang

China University of Geosciences

Jingxin Hu

Wuhan University

Zhuohong Li

Chengdu University of Traditional Chinese Medicine

Yan Huang

Kunming University of Science and Technology

Mofan Cheng

Wuhan University

Wei He

State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing

Zikai Wang

Chinese PLA General Hospital

Haoyuan Deng

City University of Hong Kong

Jiaqi Zou

State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing

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Wuhan University

State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing

Tsinghua University

Chengdu University of Traditional Chinese Medicine

Second Affiliated Hospital of Chengdu University of Traditional Chinese

Taiyuan University of Technology

Guangzhou University

Xiyuan Hospital

Kunming University of Science and Technology

Chinese PLA General Hospital

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SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (User guide V2.4)

Zenodo (CERN European Organization for Nuclear Research) (2023)

Zhuohong Li Wei He Mofan Cheng Jingxin Hu Xiao An

The User guide V2.4 of the SinoLC-1 land-cover product. The SinoLC-1 was created by the Low-to-High Network (L2HNet), which can be found at: https://doi.org/10.1016/j.isprsjprs.2022.08.008. More detailed description of the data can be found at the paper published at Earth System Science Data: https://doi.org/10.5194/essd-15-4749-2023 Click to check all the data versions and download the data (点击查看/下载所有数据版本) NOTE: If you have any data needs, questions, or technical issues, please get in touch with us at ashelee@whu.edu.cn (Zhuohong Li), and we will reply carefully and provide assistance. The latest update is on August 4, 2023. The tiff file of image capture time and original tiles with the size of 6000 × 6000 pixels ( including 1-m Google imagery and 1-m SinoLC-1 results) of Nanchang City, Jiangxi Province, Shanghai City, Hefei City, Anhui Province, Chengdu City, Sichuan Province have been updated. We will keep collecting users' feedback and updating the data, stay tuned! Citation format of paper:Li, Z., He, W., Cheng, M., Hu, J., Yang, G., and Zhang, H.: SinoLC-1: the first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data, Earth Syst. Sci. Data, 15, 4749–4780, https://doi.org/10.5194/essd-15-4749-2023, 2023. BibTex format of paper: @Article{essd-15-4749-2023, AUTHOR = {Li, Z. and He, W. and Cheng, M. and Hu, J. and Yang, G. and Zhang, H.}, TITLE = {SinoLC-1: the first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data}, JOURNAL = {Earth System Science Data}, VOLUME = {15}, YEAR = {2023}, NUMBER = {11}, PAGES = {4749--4780}, DOI = {10.5194/essd-15-4749-2023} }

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10.5281/zenodo.8214871

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SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (Update data: August, 2023)

Zenodo (CERN European Organization for Nuclear Research) (2023)

Zhuohong Li Wei He Mofan Cheng Jingxin Hu Xiao An

The Update data (August 4, 2023) of the SinoLC-1 land-cover product. The SinoLC-1 was created by the Low-to-High Network (L2HNet), which can be found at: https://doi.org/10.1016/j.isprsjprs.2022.08.008. NOTE: If you have any data needs, questions, or technical issues, please get in touch with us at ashelee@whu.edu.cn (Zhuohong Li), and we will reply carefully and provide assistance. The latest update is on August 4, 2023. The tiff file of image capture time and original tiles with the size of 6000 × 6000 pixels ( including 1-m Google imagery and 1-m SinoLC-1 results) of Nanchang City, Jiangxi Province, Shanghai City, Hefei City, Anhui Province, Chengdu City, Sichuan Province have been updated. We will keep collecting users' feedback and updating the data, stay tuned!
Currently, the preprint of this product is under review in Earth System Science Data Discussion: https://essd.copernicus.org/preprints/essd-2023-87/ Citation format of preprint: Li, Z., He, W., Cheng, M., Hu, J., Yang, G., and Zhang, H.: SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-87, in review, 2023.

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10.5281/zenodo.8214467

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Pretrain a Remote Sensing Foundation Model by Promoting Intra-instance Similarity

IEEE Transactions on Geoscience and Remote Sensing (2024)

Xiao An Wei He Jiaqi Zou Guangyi Yang Hongyan Zhang

Similarity (geometry)

Foundation (evidence)

10.1109/tgrs.2024.3469568

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SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (North of China)

Zenodo (CERN European Organization for Nuclear Research) (2023)

Zhuohong Li Wei He Mofan Cheng Jingxin Hu Xiao An

The Version North of China including the SinoLC-1 land-cover product for the provincial administrative region of Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia. The SinoLC-1 was created by the Low-to-High Network (L2HNet), which can be found at: https://doi.org/10.1016/j.isprsjprs.2022.08.008. NOTE: If you have any data needs, questions, or technical issues, please contact us at ashelee@whu.edu.cn (Zhuohong Li), and we will reply carefully and provide assistance. Currently, the preprint of this product is under review in Earth System Science Data Discussion: https://essd.copernicus.org/preprints/essd-2023-87/ Citation format of preprint: Li, Z., He, W., Cheng, M., Hu, J., Yang, G., and Zhang, H.: SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-87, in review, 2023.

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10.5281/zenodo.7709035

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SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (Update data: June, 2023)

Zenodo (CERN European Organization for Nuclear Research) (2023)

Zhuohong Li Wei He Mofan Cheng Jingxin Hu Xiao An

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10.5281/zenodo.8103779

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SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (Northeast of China)

Zenodo (CERN European Organization for Nuclear Research) (2023)

Zhuohong Li Wei He Mofan Cheng Jingxin Hu Xiao An

The Version Northeast of China includes the SinoLC-1 land-cover product for the provincial administrative region of Heilongjiang, Jilin, and Liaoning. The SinoLC-1 was created by the Low-to-High Network (L2HNet), which can be found at: https://doi.org/10.1016/j.isprsjprs.2022.08.008. NOTE: If you have any data needs, questions, or technical issues, please contact us at ashelee@whu.edu.cn (Zhuohong Li), and we will reply carefully and provide assistance. Currently, the preprint of this product is under review in Earth System Science Data Discussion: https://essd.copernicus.org/preprints/essd-2023-87/ Citation format of preprint: Li, Z., He, W., Cheng, M., Hu, J., Yang, G., and Zhang, H.: SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-87, in review, 2023.

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10.5281/zenodo.7711587

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SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (Southwest of China)

Zenodo (CERN European Organization for Nuclear Research) (2023)

Zhuohong Li Wei He Mofan Cheng Jingxin Hu Xiao An

The Version Southwest of China including the SinoLC-1 land-cover product for the provincial administrative region of Guizhou, Chongqing, Sichuan, Yunnan, and Xinjiang. The SinoLC-1 was created by the Low-to-High Network (L2HNet), which can be found at: https://doi.org/10.1016/j.isprsjprs.2022.08.008. NOTE: If you have any data needs, questions, or technical issues, please contact us at ashelee@whu.edu.cn (Zhuohong Li), and we will reply carefully and provide assistance. Currently, the preprint of this product is under review in Earth System Science Data Discussion: https://essd.copernicus.org/preprints/essd-2023-87/ Citation format of preprint: Li, Z., He, W., Cheng, M., Hu, J., Yang, G., and Zhang, H.: SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-87, in review, 2023.

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10.5281/zenodo.7707462

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SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (User guides V2.3)

Zenodo (CERN European Organization for Nuclear Research) (2023)

Zhuohong Li Wei He Mofan Cheng Jingxin Hu Xiao An

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10.5281/zenodo.8105314

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No-Reference Image Quality Assessment via Degenerate Decision Logic

2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC) (2022)

Haoyuan Deng Zikai Wang Xiao An Guangyi Yang

In this study, a no-reference (NR) IQA method based on degenerate decision logic (DDL) is proposed. DDL uses wavelet transform to extract the wavelet sub-band features of images and then maps these features to higher- level features through a hybrid network, thereby achieving effective extraction of mixing characteristics and avoiding the redundant information of low level features. DDL also adds decision logic to the assessment, combining decision logic differentiation training and fine-tuning training to allow the assessment result to approach that of human subjective cognition as closely as possible. The performance of the proposed DDL method is evaluated on the LIVE database.

10.1109/ipec54454.2022.9777360

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SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (East of China)

Zenodo (CERN European Organization for Nuclear Research) (2023)

Zhuohong Li Wei He Mofan Cheng Jingxin Hu Xiao An

The Version East of China including the SinoLC-1 land-cover product for the provincial administrative region of Anhui, Fujian, Shanghai, Jiangsu, Zhejiang, Jiangxi, Shandong, and Taiwan. The SinoLC-1 was created by the Low-to-High Network (L2HNet), which can be found at: https://doi.org/10.1016/j.isprsjprs.2022.08.008. NOTE: If you have any data needs, questions, or technical issues, please contact us at ashelee@whu.edu.cn (Zhuohong Li), and we will reply carefully and provide assistance. Currently, the preprint of this product is under review in Earth System Science Data Discussion: https://essd.copernicus.org/preprints/essd-2023-87/ Citation format of preprint: Li, Z., He, W., Cheng, M., Hu, J., Yang, G., and Zhang, H.: SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2023-87, in review, 2023.

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10.5281/zenodo.7709370

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