使用Google Earth引擎中的Sentinel-2图像在高度动态的河流中估计度的度:印度戈达瓦里河的案例研究
Meena Kumari Kolli1,2, Pennan Chinnasamy3,4,5,6,7,8
1Centre for Technology Alternatives for Rural Areas, Indian Institute of Technology (IITB), Powai, Mumbai, Maharashtra, 400076, India.
概括
这项研究引入了一种新的遥感方法,用于估计戈达瓦里河的水度. 红边带算法被证明是对大面积的水质监测最准确的.
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:
- 度是影响水生生态系统的关键水质指标.
- 由于后勤和成本限制,发展中国家的传统监测具有挑战性.
研究的目的:
- 开发和验证一种新的半分析遥感方法来估计度.
- 评估不同算法对水体的有效性.
主要方法:
- 在谷歌地球引擎平台上使用 Sentinel-2 多光谱成像仪数据.
- 开发了两个算法:规范差异度指数 (NDTI) 和一个半实证单带算法.
- 相关的光谱反射率与使用立方多项式回归的现场度数据.
主要成果:
- 单带红边算法实现了最高的精度 (R2=0.91,RMSE=0.003).
- 此外,NDTI算法也表现出良好的性能 (R2=0.85,RMSE=0.05).
- 这两种方法都在中度到高度水中表现出有效性.
结论:
- 遥感为大规模,经济高效的度监测提供了可行的解决方案.
- 提出的方法可以帮助实现戈达瓦里河的水质标准.
- 这种方法提高了数据稀缺地区的水资源管理能力.
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