使用Sentinel-2卫星图像对河水质量的监测和空间可追溯性
Yingyin Zhang1, Xianqiang He2, Gang Lian3
1Ocean College, Zhejiang University, Zhoushan 316021, China.
The Science of the total environment
|June 22, 2023
概括
来自Sentinel-2的卫星图像有效地追踪了河流污染热点. 这种方法克服了传统现场测量的局限性,使得诸如江省的河流等河流能够精确控制水质.
科学领域:
- 环境遥感 环境遥感
- 水质监测 水质监测
- 地理空间分析的研究.
背景情况:
- 传统的现场河流监测局限于空间覆盖,阻碍了污染热点的识别.
- 高空间时空分辨率卫星图像为全面的河流质量评估提供了潜在的解决方案.
- 卫星Sentinel-2的数据提供了一个常规监测和追踪河流水质量参数的机会.
研究的目的:
- 用Sentinel-2卫星图像来说明河水质量参数的空间可追溯性.
- 建立区域检索模型,用于酸盐指数 (CODMn),总 (TP) 和总 (TN).
- 确定中国江省七条主要河流沿线的特定高污染地区.
主要方法:
- 使用Sentinel-2卫星数据开发CODMn,TP和TN的区域检索模型.
- 从2016年到2021年为七条河流生成时间序列CODMn,TP和TN产品.
- 基于卫星衍生产品的水质参数空间和季节性变化的分析.
主要成果:
- 检索模型的相关系数 (R) 为CODMn为0.68,TP为0.82和TN为0.7.
- 一般来说,CODMn,TP和TN在下游河流段的度较高.
- 关于污染物分布的Cao'e河 (CEJ) 和永江河 (YJ) 特别例外.
结论:
- 卫星Sentinel-2卫星图像有效地追踪了河流沿线高污染地区的特定位置.
- 这种方法提高了河流系统的精确水质控制和管理策略.
- 这项研究证明了遥感对于大规模,详细的河流污染评估的实用性.
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