Mapping the fine spatial distribution of global offshore surface seawater mariculture using remote sensing big data
文献类型：期刊论文
| 作者 | Liu, Yueming; Yang, Xiaomei6; Wang, Zhihua6; Liu, Bin6; Zhang, Junyao6; Liu, Xiaoliang6; Meng, Dan6; Gao, Ku6; Zeng, Xiaowei5,6; Yu, Guo6 |
| 刊名 | INTERNATIONAL JOURNAL OF DIGITAL EARTH
 |
| 出版日期 | 2024-12-31 |
| 卷号 | 17期号:1页码:2402418 |
| 关键词 | Mariculture remote sensing big data global mapping coastal zone sustainable development |
| DOI | 10.1080/17538947.2024.2402418 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Against the backdrop of near-saturation in global marine capture fisheries, current mariculture production now exceeds one-third of capture production and continues to hold significant growth potential. However, the lack of spatially detailed global offshore surface seawater mariculture (OSSM) data hampers scientific understanding and management from a spatial perspective. In this study, utilizing multi-source remote sensing time-series imagery, we achieve the world's first spatially detailed mapping of both raft and cage mariculture types. The results show that (1) in 2020, the total global OSSM area was 20,079.97 km(2), comprising 85.04% raft mariculture and 14.96% cage mariculture. 95.33% of the OSSM was concentrated in Asia. (2) The interpreted national OSSM areas align well with the FAO production statistics trends. Obtaining these areas using remote sensing offers greater timeliness compared to production statistics, which is advantageous for dynamic monitoring and production estimation. (3) Through analysis of global pond aquaculture data, it was found that most coastal areas worldwide had a single-type of aquaculture. However, in parts of Asia, regions with both OSSM and pond aquaculture coexisted. The data acquired in this study, characterized by detailed spatial information, provide significant insights for constructing spatial models of mariculture, researching resource-environment effects, and informing management practices. |
| WOS关键词 | AQUACULTURE ; AREA ; EXTRACTION ; IMAGES |
| WOS研究方向 | Physical Geography ; Remote Sensing |
| WOS记录号 | WOS:001310047800001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/207986]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Yang, Xiaomei; Wang, Zhihua |
| 作者单位 | 1.NUIST, Sch Remote Sensing & Geomat Engn, Nanjing, Peoples R China 2.Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo, Peoples R China 3.China Agr Univ, Coll Land Sci & Technol, Beijing, Peoples R China 4.China Univ Geosci Wuhan, Sch Geog & Informat Engn, Wuhan, Peoples R China 5.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Yueming,Yang, Xiaomei,Wang, Zhihua,et al. Mapping the fine spatial distribution of global offshore surface seawater mariculture using remote sensing big data[J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH,2024,17(1):2402418. |
| APA | Liu, Yueming.,Yang, Xiaomei.,Wang, Zhihua.,Liu, Bin.,Zhang, Junyao.,...&Zhou, Meiqi.(2024).Mapping the fine spatial distribution of global offshore surface seawater mariculture using remote sensing big data.INTERNATIONAL JOURNAL OF DIGITAL EARTH,17(1),2402418. |
| MLA | Liu, Yueming,et al."Mapping the fine spatial distribution of global offshore surface seawater mariculture using remote sensing big data".INTERNATIONAL JOURNAL OF DIGITAL EARTH 17.1(2024):2402418. |
入库方式： OAI收割
来源：地理科学与资源研究所
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