International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China; Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
Sci Bull (Beijing). 2023 Jun 30;68(12):1306-1316. doi: 10.1016/j.scib.2023.05.004. Epub 2023 May 10.
Mangrove forests deliver incredible ecosystem goods and services and are enormously relevant to sustainable living. An accurate assessment of the global status of mangrove forests warrants the necessity of datasets with sufficient information on spatial distributions and patch patterns. However, existing datasets were mostly derived from ∼30 m resolution satellite imagery and used pixel-based image classification methods, which lacked spatial details and reasonable geo-information. Here, based on Sentinel-2 imagery, we created a global mangrove forest dataset at 10-m resolution, namely, High-resolution Global Mangrove Forests (HGMF_2020), using object-based image analysis and random forest classification. We then analyzed the status of global mangrove forests from the perspectives of conservation, threats, and resistance to ocean disasters. We concluded the following: (1) globally, there were 145,068 km mangrove forests in 2020, among which Asia contained the largest coverage (39.2%); at the country level, Indonesia had the largest amount of mangrove forests, followed by Brazil and Australia. (2) Mangrove forests in South Asia were estimated to be in the better status due to the higher proportion of conservation and larger individual patch size; in contrast, mangrove forests in East and Southeast Asia were facing intensive threats. (3) Nearly, 99% of mangrove forest areas had a patch width greater than 100 m, suggesting that nearly all mangrove forests were efficient in reducing coastal wave energy and impacts. This study reports an innovative and up-to-date dataset and comprehensive information on mangrove forests status to contribute to related research and policy implementation, especially for supporting sustainable development.
红树林提供了令人难以置信的生态系统产品和服务，对可持续生活具有重要意义。准确评估全球红树林的状况需要有充分的关于空间分布和斑块模式的数据集。然而，现有的数据集大多是从 30 米分辨率的卫星图像中提取的，并使用基于像素的图像分类方法，这些方法缺乏空间细节和合理的地理信息。在这里，我们基于 Sentinel-2 图像，使用基于对象的图像分析和随机森林分类方法，创建了一个全球红树林数据集，即 10 米分辨率的高分辨率全球红树林数据集（HGMF_2020）。然后，我们从保护、威胁和抵御海洋灾害的角度分析了全球红树林的状况。我们得出以下结论：（1）全球范围内，2020 年有 145068 公里的红树林，其中亚洲的覆盖面积最大（39.2%）；在国家层面上，印度尼西亚拥有最大的红树林面积，其次是巴西和澳大利亚。（2）南亚的红树林状况估计较好，因为保护的比例较高，个体斑块的面积较大；相比之下，东亚和东南亚的红树林面临着密集的威胁。（3）几乎 99%的红树林地区的斑块宽度大于 100 米，这表明几乎所有的红树林都能有效地减少沿海波浪的能量和影响。本研究报告了一个创新的、最新的数据集和关于红树林状况的综合信息，以促进相关研究和政策实施，特别是支持可持续发展。
