基于GF-1影像的巢湖浊度遥感监测及时空变化研究

大气与环境光学学报 ›› 2021, Vol. 16 ›› Issue (2): 149-157.

基于GF-1影像的巢湖浊度遥感监测及时空变化研究

晁明灿1, 赵强2, 杨铁利1∗, 李华富1, 谢发之2, 吴蕾3

1 辽宁科技大学土木工程学院, 辽宁鞍山 117004; 2 安徽建筑大学环境与能源工程学院, 安徽合肥 230601; 3 安徽省环境科学研究院, 安徽合肥 230022

收稿日期:2020-08-21 修回日期:2020-12-17 出版日期:2021-03-28 发布日期:2021-03-28
通讯作者: E-mail: 262439340@qq.com E-mail:262439340@qq.com
作者简介:晁明灿 (1995- ), 安徽六安人, 硕士研究生, 主要从事水质遥感方面的研究。 E-mail: cmc2877160956@163.com
基金资助:
Supported by National Natural Science Foundation of China (国家自然科学基金项目, 21777001), Key Research and Development Projects of Anhui Province (安徽省重点研发计划项目, 202004i07020006)

Remote Sensing Monitoring and Spatiotemporal Variation of Turbidity of Chaohu Lake Based on GF-1 Image

CHAO Mingcan1, ZHAO Qiang2, YANG Tieli1∗, LI Huafu1, XIE Fazhi2, WU Lei3

1 School of Civil Engineering, University of Science and Technology Liaoning, Anshan 114051, China; 2 School of Environment and Energy Engineering, Anhui Jianzhu University, Hefei 230601, China; 3 Anhui Academy of Environmental Science and Research, Hefei 230022, China

Received:2020-08-21 Revised:2020-12-17 Published:2021-03-28 Online:2021-03-28

摘要/Abstract

摘要： 浊度监测可以为湖泊水质的污染防控和预警提供科学依据。为了提高湖泊浊度的动态监测能力, 将卫星遥感监测和浮标检测站监测相结合, 对 2019 年巢湖浊度的时空变化进行分析。浮标检测站监测通过高频次连续的实测浊度数据的统计分析, 研究巢湖浊度时空变化特征; 遥感监测通过构建最优波段组合模型对浊度进行定量反演。研究结果表明: (1) 巢湖整体浊度动态变化过程明显, 短时间内变异显著; (2) 浊度对红色波段和近红外波段敏感; (3) 蓝藻爆发时间段巢湖整体浊度较高, 且日间浊度动态变化显著。该研究为水质监测提供新思路, 同时推进了空地联合方式在水质监测方面的应用。

关键词: 遥感, 浊度, 波段组合, 巢湖

Abstract: Turbidity monitoring can provide a scientific basis for the prevention, control and early warning of lake water quality. In order to improve the dynamic monitoring capability of lake turbidity, satellite remote sensing monitoring and buoy detection station monitoring are combined to study the temporal and spatial changes of Chaohu Lake turbidity in 2019. The temporal and spatial variation characteristics of Chaohu Lake′s turbidity are studied through the statistical analysis of high-frequency continuous measured turbidity data at the buoy detection station, while the turbidity is quantitatively retrieved by constructing the optimal band combination model for remote sensing monitoring. The results showed that (1) the overall turbidity dynamics of Chaohu Lake is obvious, and the variation is significant within a short period of time, (2) the turbidity is sensitive to the red band and near-infrared band, (3) the overall turbidity of Chaohu Lake during the cyanobacteria outbreak period is relatively high, and diurnal turbidity changes significantly. This work provides a new idea for water quality monitoring, and at the same time promotes the application of air-ground joint methods in water quality monitoring.

Key words: remote sensing, turbidity, band combination, Chaohu Lake

中图分类号:

P237

晁明灿, 赵强, 杨铁利∗, 李华富, 谢发之, 吴蕾. 基于GF-1影像的巢湖浊度遥感监测及时空变化研究[J]. 大气与环境光学学报, 2021, 16(2): 149-157.

CHAO Mingcan, ZHAO Qiang, YANG Tieli∗, LI Huafu, XIE Fazhi, WU Lei. Remote Sensing Monitoring and Spatiotemporal Variation of Turbidity of Chaohu Lake Based on GF-1 Image[J]. Journal of Atmospheric and Environmental Optics, 2021, 16(2): 149-157.

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