GF-1与GF-6 WFV影像在滇池悬浮物浓度反演中的对比分析  

Comparative Analysis of GF-1 and GF-6 WFV Images in Suspended Matter Concentration Inversion in Dianchi Lake

作　　者：赵冉 杨凤芸[1] 孟庆岩 康育鹏 郑佳媛 胡新礼 杨杭 ZHAO Ran;YANG Feng-yun;MENG Qing-yan;KANG Yu-peng;ZHENG Jia-yuan;HU Xin-li;YANG Hang(School of Civil Engineering,University of Science and Technology Liaoning,Anshan 114051,China;The Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100101,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China;School of Surveying and Land Information Engineering,Henan Polytechnic University,Jiaozuo 454003,China)

机构地区：[1]辽宁科技大学土木工程学院,辽宁鞍山114051 [2]中国科学院空天信息创新研究院,北京100101 [3]中国科学院大学资源与环境学院,北京100049 [4]河南理工大学测绘与国土信息工程学院,河南焦作454003

出　　处：《光谱学与光谱分析》2023年第1期198-205,共8页Spectroscopy and Spectral Analysis

基　　金：三亚市院地科技合作项目(2018YD10);国家重点研发计划项目(2016YFC0801600);国家高分辨率对地观测重大科技专项项目“环境保护遥感动态监测信息服务系统(二期)”(05-Y30B01-9001-19/20-1);气溶胶辐射效应对农作物光合作用及GCP遥感估算累积影响研究项目(41871352)资助。

摘　　要：总悬浮物(TSM)是水环境评价的重要参数之一,也是遥感水质反演的重要指标。GF-1/WFV和GF-6/WFV作为高分系列对外免费开放的卫星数据,在遥感监测中的应用较为广泛,但目前针对两种数据的对比分析以及GF-6/WFV新增波段在水体水质参数反演中的适用性研究较少。以云南滇池水域为研究区域,对与水体实测数据同步过境(或时相相近)的GF-1/WFV和GF-6/WFV遥感影像采用统计分析的方法进行相同波段(蓝、绿、红、近红外)一致性分析,在此基础上运用经验回归方法分别构建两种数据的TSM反演模型,并将加入GF-6/WFV新增波段的模型与GF-1/WFV构建的模型进行对比分析,选择最优模型应用于滇池2020年的6幅GF-6/WFV图像得到滇池TSM分布图。结果表明:GF-1/WFV与GF-6/WFV的蓝、绿、红、近红外波段的相关系数分别为0.98,0.98,0.97和0.99,两种数据的表观反射率具有很高的一致性。GF-1/WFV基于蓝、绿、近红外波段构建的差值模型“B2+B4-B1”反演精度较高,模型反演的均方根误差为6.35 mg·L^(-1),平均绝对百分比误差为23.60%。GF-6/WFV基于近红外、红边1和红边2波段构建的比值模型“1/B5+B6”反演精度较高,模型反演的均方根误差(RMSE)为3.07 mg·L^(-1),平均绝对百分比误差(MAPE)为20.65%,以GF-1/WFV构建的差值模型“B1-B4”与GF-6/WFV构建的“B5-B4”对比发现后者均方根误差减小了2.61 mg·L^(-1),平均绝对百分比降低了32.33%,实验表明加入红边波段的模型反演效果较其他模型更好。采用建模公式得到了2020年滇池TSM分布图,滇池TSM的变化范围在4~45 mg·L^(-1),均值为18.23 mg·L^(-1),总体空间分布呈现北重南轻的分布态势,滇池TSM时间分布表现为上升-下降趋势。该研究不仅可以为湖泊水质监测传感器波段设置提供参考和借鉴,也为滇池水资源监管部门进行水质遥感监测提供了技术支撑。Total suspended matter(TSM)is one of the important parameters of water environment assessment and an important index of remote sensing water retrieval.GF-1/WFV and GF-6/WFV are free and open satellite data of the gaofen series,which are widely used in remote sensing monitoring.However,there are few studies on the applicability of the new bands of GF-6/WFV in water quality parameter inversion.This study takes Dianchi Lake in Yunnan province as the research area,based on the testing data synchronization with water transit(or similar)of the phase of GF-1/WFV and GF-6/WFV remote sensing image using statistics analysis method to the same band(blue,green,red and near-infrared)consistency analysis,regression method based on using the experience of the TSM inversion models of the two kinds of data,respectively,The model with GF-6/WFV added bands were compared with the model constructed by GF-1/WFV.The optimal model was applied to six GF-6/WFV images in 2020 to obtain the TSM distribution map of Dianchi Lake.The results show that the correlation coefficients of GF-1/WFV and GF-6/WFV in blue,green,red and near infrared bands are 0.98,0.98,0.97 and 0.99,respectively.The apparent reflectance of the two kinds of data is highly consistent.The inversion accuracy of GF-1/WFV difference model“B2+B4-B1”based on blue,green and near-infrared red bands is high,and the root means square error of model inversion is 6.35 mg·L^(-1),and the average absolute percentage error is 23.60%.The ratio model“1/B5+B6”constructed by GF-6/WFV based on near-infrared,red-edge 1 and red-edge 2 bands has a high inversion accuracy.Model inversion’s root mean square error(RMSE)is 3.07 mg·L^(-1),and the mean absolute percentage error(MAPE)is 20.65%.By comparing the difference model“B1-B4”constructed by GF-1/WFV with“B5-B4”constructed by GF-6/WFV,it is found that the root means square error of the latter is reduced by 2.61 mg·L^(-1),and the average absolute percentage is reduced by 32.33%.The experiment shows that the inversion effect of

关 键 词：GF-1/WFV GF-6/WFV 滇池 总悬浮物 对比分析 

分 类 号：P237[天文地球—摄影测量与遥感]