CAS Landslide Dataset: A Large-Scale and Multisensor Dataset for Deep Learning-Based Landslide Detection
文献类型:期刊论文
作者 | Xu, Yulin2,3; Ouyang, Chaojun3; Xu, Qingsong1; Wang, Dongpo2; Zhao, Bo3; Luo, Yutao2,3 |
刊名 | SCIENTIFIC DATA |
出版日期 | 2024-01-02 |
卷号 | 11期号:1页码:11 |
ISSN号 | 2052-4463 (online) |
关键词 | 无 |
DOI | 10.1038/s41597-023-02847-z |
英文摘要 | In this work, we present the CAS Landslide Dataset, a large-scale and multisensor dataset for deep learning-based landslide detection, developed by the Artificial Intelligence Group at the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (CAS). The dataset aims to address the challenges encountered in landslide recognition. With the increase in landslide occurrences due to climate change and earthquakes, there is a growing need for a precise and comprehensive dataset to support fast and efficient landslide recognition. In contrast to existing datasets with dataset size, coverage, sensor type and resolution limitations, the CAS Landslide Dataset comprises 20,865 images, integrating satellite and unmanned aerial vehicle data from nine regions. To ensure reliability and applicability, we establish a robust methodology to evaluate the dataset quality. We propose the use of the Landslide Dataset as a benchmark for the construction of landslide identification models and to facilitate the development of deep learning techniques. Researchers can leverage this dataset to obtain enhanced prediction, monitoring, and analysis capabilities, thereby advancing automated landslide detection. |
WOS关键词 | CLOUD DETECTION ; INSIGHTS |
资助项目 | National Natural Science Foundation of China (National Science Foundation of China)[XDA23090303] ; Strategic Priority Research Program of CAS[42022054] ; NSFC[2022YFS0543] ; NSFC[2022YFG0140] ; Sichuan Science and Technology Program[Y201970] ; Youth Innovation Promotion Association |
WOS研究方向 | Science & Technology - Other Topics |
语种 | 英语 |
出版者 | NATURE PORTFOLIO |
WOS记录号 | WOS:001135385400013 |
资助机构 | National Natural Science Foundation of China (National Science Foundation of China) ; Strategic Priority Research Program of CAS ; NSFC ; Sichuan Science and Technology Program ; Youth Innovation Promotion Association |
源URL | [http://ir.imde.ac.cn/handle/131551/57843] |
专题 | 成都山地灾害与环境研究所_山地灾害与地表过程重点实验室 |
通讯作者 | Ouyang, Chaojun |
作者单位 | 1.Tech Univ Munich, Data Sci Earth Observat, D-80333 Munich, Germany 2.Chengdu Univ Technol, State Key Lab Geohazard Prevent & Geoenvironm Prot, Chengdu 610059, Peoples R China 3.Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Hazards & Surface Proc, Chengdu 610299, Peoples R China |
推荐引用方式 GB/T 7714 | Xu, Yulin,Ouyang, Chaojun,Xu, Qingsong,et al. CAS Landslide Dataset: A Large-Scale and Multisensor Dataset for Deep Learning-Based Landslide Detection[J]. SCIENTIFIC DATA,2024,11(1):11. |
APA | Xu, Yulin,Ouyang, Chaojun,Xu, Qingsong,Wang, Dongpo,Zhao, Bo,&Luo, Yutao.(2024).CAS Landslide Dataset: A Large-Scale and Multisensor Dataset for Deep Learning-Based Landslide Detection.SCIENTIFIC DATA,11(1),11. |
MLA | Xu, Yulin,et al."CAS Landslide Dataset: A Large-Scale and Multisensor Dataset for Deep Learning-Based Landslide Detection".SCIENTIFIC DATA 11.1(2024):11. |
入库方式: OAI收割
来源:成都山地灾害与环境研究所
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