高分六号影像在内陆水体叶绿素a反演中的应用潜力分析  

Application Potential Analysis on Chlorophyll-a Retrieval for Inland Water based on a Gaofen-6 WFV Imagery

作　　者：曹引 冶运涛[1] 赵红莉[1] 蒋云钟[1] 董甲平 严登明 CAO Yin;YE Yuntao;ZHAO Hongli;JIANG Yunzhong;DONG Jiaping;Yan Dengming(Department of Water Resources,China Institute of Water Resources and Hydropower Research,Beijing 100038,China;Yellow River Engineering Consulting Co.,Ltd.,Zhengzhou 450000,China)

机构地区：[1]中国水利水电科学研究院水资源研究所,北京100038 [2]黄河勘测规划设计研究院有限公司,郑州450000

出　　处：《地球信息科学学报》2022年第3期546-557,共12页Journal of Geo-information Science

基　　金：高分辨率对地观测系统重大专项(08-Y30F02-9001-20/22);国家重点研发计划课题(2018YFC0407705);中国工程科技知识中心水利专业知识服务系统(CKCEST-2020-2-9)。

摘　　要：GF-6 WFV影像具有宽覆盖、高时空分辨率、高光谱分辨率等特点,目前在农业和林业遥感领域都有一定应用,但是在水质遥感中的应用潜力还缺乏系统的评估。本文以潘家口和大黑汀水库为研究区,采用2019年9月24—25日获取的潘家口和大黑汀水库叶绿素a浓度、实测遥感反射率和准同步GF-6 WFV影像,构建了潘家口和大黑汀水库叶绿素a浓度经验反演模型,探索GF-6 WFV在内陆水体叶绿素a浓度遥感监测中的应用潜力。研究结果表明,基于GF-6 WFV模拟光谱构建的潘家口和大黑汀水库叶绿素a浓度经验模型决定系数均在0.90以上,GF-6 WFV影像在水体叶绿素a遥感监测中具有应用潜力,尤其是新增的黄波段和红边波段1,有助于提高GF-6 WFV影像叶绿素a浓度遥感监测能力;GF-6 WFV影像大气校正误差降低了叶绿素a浓度遥感监测精度,GF-6 WFV影像水体大气校正精度有待改进,以提升GF-6 WFV影像水质遥感监测能力。Gaofen-6 wide field of view(GF-6 WFV)imagery,with wide coverage,high temporal,spatial,and spectral resolution,has been applied in the fields of remote sensing of agriculture and forestry.However,the application potential of GF-6 imagery in the field of remote sensing of water quality lacks a systematic assessment.In this study,four empirical models of single-band model,band-ratio model,partial least squares model,and support vector machine model were developed to retrieve Chlorophyll-a(Chl-a)in Panjiakou and Daheiting reservoirs.The retrieval was based on measured Chl-a concentration and in situ remote sensing reflectance of 37 samples acquired in September 24 and 25,2019,as well as a quasi-synchronous GF-6 WFV imagery.The application potential of GF-6 imagery in the field of remote sensing of water quality was evaluated according to the performance of four empirical models for Chl-a retrieval in Panjiakou and Daheiting reservoirs.The determination coefficients and comprehensive errors of four empirical models based on GF-6 WFV reflectance simulated by in situ reflectance were above 0.9 and less than 15%for Chl-a retrieval in Panjiakou and Daheiting reservoirs,respectively.The partial least squares model had the highest accuracy among the four empirical models,with a determination coefficient of 0.96 and a comprehensive error of 13.22%.Finally,the partial least squares model was applied to retrieve the spatial distribution of Chl-a concentration in Panjiakou and Daheiting reservoirs based on the GF-6 WFV imagery acquired on September 26,2019.The Chl-a retrieval result indicated that Chl-a concentration was less than 10μg/L in Panjiakou reservoir but more than 10μg/L in Daheiting reservoir.The trophic states of Panjiakou reservoir and Daheiting reservoir were respectively mesotrophic and eutrophic according to trophic level index calculated by Chl-a concentration.GF-6 WFV imagery,with eight bands in visible and near-infrared,has application potential in remote sensing of Chl-a concentration in inland water.In pa

关 键 词：高分六号 内陆水体 潘家口和大黑汀水库 叶绿素A 遥感 大气校正 经验模型 应用潜力 

分 类 号：X832[环境科学与工程—环境工程] X87