使用现场测量和使用基于机器学习的GIS和遥感技术评估红树林息地的碳库存
Khaled Al-Jabri1, Yaseen Al-Mulla1,2, Ahmad Tabook3
1Department of Soils, Water and Agricultural Engineering, Sultan Qaboos University, Al-Khoud 123, Muscat, Oman.
iScience
|December 24, 2025
概括
这项研究使用现场数据和卫星图像来量化阿维森尼亚海红树林的地面生物质和碳. 结果显示,碳储存显著,有助于干旱地区的保护和碳核算.
科学领域:
- 生态生态学 生态生态学
- 遥感 遥感 遥感 遥感
- 气候科学 气候科学
背景情况:
- 红树林生态系统是对减缓气候变化至关重要的蓝色碳汇.
- 对于全球碳核算来说,准确评估红树林的地表生物质 (AGB) 和碳库存至关重要.
研究的目的:
- 评估Avicennia海红树林在超干旱环境中的AGB和碳库存.
- 整合现场数据和遥感,以进行可靠的生物质和碳库存估计.
主要方法:
- 结合了破坏性采样,现场调查和高分辨率的Pléiades Neo卫星图像.
- 开发并校准了一种用于生物质估计的新型全度模型.
- 利用基于机器学习的遥感模型,结合光谱指数和天花板反射率.
主要成果:
- 全度模型表现出高精度 (R2 = 0.93),估计碳储存量为每棵树0.023tC.
- 遥感模型在生物质预测方面显示出可靠的性能 (R2 = 0.643).
- 在研究的超干旱红树林生态系统中量化碳储存潜力.
结论:
- 红树林在国家和全球碳预算中发挥着重要作用.
- 结果为保护规划和碳抵消框架提供了实际数据.
- 强调综合现场和遥感方法在干旱沿海地区生物质评估的有效性.
相关概念视频
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