摘要
2021年12月26日,我国成功发射资源一号02E(ZY1-02E)卫星,其搭载了新一代高光谱相机(Advanced Hyperspectral Imager,AHSI),拥有30 m空间分辨率的可见光到短波红外范围内的166个波段,在内陆水体水质参数反演方面具有重要潜力。本研究以北京市沙河水库和金海湖为研究区,开展基于ZY1-02E AHSI影像数据的叶绿素a浓度和透明度反演研究,以评价其实际应用效果。基于京津冀地区12个湖库的遥感反射率和叶绿素a浓度实测数据,构建叶绿素a反演半经验模型。将该模型和基于准解析算法(Quasi-Analytical Algorithm,QAA)的透明度半分析模型应用于ZY1-02E AHSI影像,并利用在沙河水库和金海湖两个研究区获取的星地同步实测水质数据对反演结果进行精度评价。结果表明,基于670 nm和705 nm波长的归一化指数的叶绿素a反演半经验模型的精度最高,拟合度和平均相对误差分别为0.79和21.70%;基于QAA-V6的透明度半分析模型的精度最高,拟合度和平均相对误差分别为0.93和13.90%。该研究结果初步证明了ZY1-02E高光谱数据在内陆水体水质参数反演中的潜力。
The ZY1-02E satellite,launched on December 26 in 2021,carries the new-generation Advanced Hyperspectral Imager(AHSI).It has 166 bands in the visible to shortwave infrared range with a spatial resolution of 30 m,and has considerable potential in retrieving water quality parameters in inland waters.This study evaluated the practical application of ZY1-02E AHSI imagery in the retrieval of chlorophyll-a concentration and Secchi-disk depth in the Shahe Reservoir and Jinhai Lake in Beijing,China.Based on the measured data of remote sensing reflectance and chlorophyll-a concentration of 12 lakes and reservoirs in the Beijing-Tianjin-Hebei region,the semi-empirical models for chlorophyll-a retrieval were established.The established chlorophyll-a retrieval model and Secchi-disk depth retrieval model with the Quasi-Analytical Algorithm(QAA) were applied to the ZY1-02E AHSI images,and the accuracy assessment was conducted using the synchronized measured in-situ water quality data in Shahe Reservoir and Jinhai Lake.The results showed that the normalized difference index at 670 nm and 705 nm wavelengths based chlorophyll-a concentration retrieval model achieved the highest accuracy,with R~2 and mean relative error to be 0.79 and 21.70%,respectively.The QAA-V6 based Secchi-disk depth retrieval model achieved the highest accuracy with R~2 and mean relative error to be 0.93 and 13.90%,respectively.These findings preliminarily demonstrated the potential of ZY1-02E hyperspectral data in the retrieval of water quality parameters in inland water.
作者
姚华鑫
肖潇
陈品祥
周庆
郭津
刘瑶
张方方
王胜蕾
李俊生
YAO Huaxin;XIAO Xiao;CHEN Pinxiang;ZHOU Qing;GUO Jin;LIU Yao;ZHANG Fangfang;WANG Shenglei;LI Junsheng(Key Laboratory of Digital Earth Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100049,China;International Research Center of Big Data for Sustainable Development Goals,Beijing 100094,China;Beijing Institute of Surveying and Mapping,Beijing 100038,China;Beijing Key Laboratory of Urban Spatial Information Engineering,Beijing 100038,China;Land Satellite Remote Sensing Application Center,Ministry of Natural Resources of China,Beijing 100048,China;School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《华北水利水电大学学报（自然科学版）》
北大核心
2024年第1期11-20,30,共11页
Journal of North China University of Water Resources and Electric Power：Natural Science Edition
基金
北京市测绘设计研究院委托项目
“自然资源卫星遥感技术体系建设与应用示范”项目
中欧科技合作“龙计划”项目(59193)。
