使用 Sentinel 2 MSI 预测地中海高缩单体水库中的水质变异:考虑模型功能形式的重要性
Mohamad Abbas1, Ibrahim Alameddine2
1Department of Civil and Environmental Engineering, American University of Beirut, Beirut, Lebanon.
Environmental monitoring and assessment
|July 6, 2023
概括
使用Sentinel 2的遥感有效地预测水质和水库中的有害藻类繁殖. 随机森林模型显示了高精度的叶绿素-a,总悬浮固体和Secchi盘深度.
科学领域:
- 环境科学 环境科学
- 遥感 遥感 遥感 遥感
- 水质管理水质管理
背景情况:
- 人类造成的化是影响淡水生态系统的全球性问题,导致有害的藻类繁殖 (HAB).
- 传统的监测缺乏有效管理湖泊和水库所需的时空分辨率.
- 遥感为了解水质变化提供了先进的能力.
研究的目的:
- 评估Sentinel 2在预测超高的Qaraoun水库的时空水质变化的潜力.
- 评估现有的Landsat模型与Sentinel 2数据的可转移性.
- 开发和比较新的基于Sentinel 2的水质模型.
主要方法:
- 评估了Landsat 7/8模型对Sentinel 2数据的可转移性.
- 在两年内使用153个水质样本开发了新的Sentinel 2模型.
- 应用了多重线性回归,MARS,随机森林 (RF) 和支持向量回归 (SVR) 模型.
主要成果:
- 即使在重新校准后,Landsat到Sentinel 2模型的可转移性也很差.
- 射频模型在预测叶绿素a,总悬浮固体 (TSS),Secchi盘深度 (SDD) 和植物方面明显优于MLR,MARS和SVR.
- 射频模型的R平方值在85% (TSS) 到95% (SDD) 之间.
结论:
- 哨兵2号,特别是使用射频模型,显示了监测水库水质和HABs的巨大潜力.
- 从Sentinel 2图像中间接量化毒素是可行的,因为与叶绿素-a的相关性.
- 这种方法可以改善内陆淡水水质管理决策.
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