一个简单而有效的算法,从中国杭州湾的GOCI数据中检索全部悬浮物质
Mingjun He1, Shuangyan He1, Shiming Lu2
1Ocean College, Zhejiang University, Zhoushan, China; Hainan Institute, Zhejiang University, Sanya, China.
The Science of the total environment
|February 26, 2025
概括
一个新的算法准确地测量了杭州湾的悬浮物质总量 (TSM),即使在极端度下也是如此. 这种遥感方法改进了现有的动态沿海水域监测技术.
科学领域:
- 海洋学 海洋学 海洋学
- 遥感 遥感 遥感 遥感
- 环境监测 环境监测
背景情况:
- 杭州湾经历了高且快速变化的总悬浮物质 (TSM) 度,经常超过标准遥感算法的极限.
- 精确的TSM监测对于了解沿海动态,沉积物运输和光学复杂水域的水质至关重要.
研究的目的:
- 开发一种简单,高效和准确的遥感算法,用于估计杭州湾等高度动态的乱沿海地区的TSM度.
- 建立一个算法,能够处理四个数量级的TSM度,克服现有方法的局限性.
主要方法:
- 开发了一种使用雷利校正反射率 (ρrc) 数据从地球静止海洋彩色成像仪 (GOCI) 的新算法.
- 校准的算法参数使用来自三个浮标的卫星-地面同步数据集 (2013-2020).
- 将拟议的基于 ρrc 的算法的性能与传统的表面留水反射率算法进行了比较.
主要成果:
- 拟议的算法表现出卓越的性能,R2为0.75,平均绝对百分比误差 (MAPE) 为45.41%.
- 与NOAA产品 (R2=0.11,MAPE=75.06%) 相比,应用到GOCI数据时,该算法显示了日准确度的提高 (R2=0.65,MAPE=38.86%).
- 该算法成功捕获了与潮再悬浮相关的小规模TSM波动,并显示可转移到Landsat-8和GOCI-II数据.
结论:
- 开发的算法为在高度动态和的沿海环境中估计TSM提供了简洁而实用的解决方案.
- 这种方法提高了对TSM变异的准确,高频监测能力,这对于沿海管理和研究至关重要.
- 该算法的稳定性和可转移性表明它在类似具有挑战性的水生系统中具有广泛的适用性.
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