摘要
为了定量表征南四湖水体中叶绿素a浓度时空变化规律,以高分一号宽幅覆盖相机数据为数据源,采用经验模型反演算法,以单波段反射率或波段反射率组合为基础,建立遥感数据与实时或准实时叶绿素a浓度的回归分析模型,验证模型精度并进行反演。结果表明,λ_(B2)/(λ_(B1)+λ_(B3))是最优反演波段组合,决定系数大于0.7,模型平均相对误差为11.11%,归一化均方根误差为11.46%,模型精度较高,可用于南四湖水域中叶绿素a浓度的定量反演;将反演模型应用于2021年不同季节的四景影像上,得到南四湖水域中不同季节的叶绿素a浓度时空分布情况,与实际情况基本吻合。
To quantitatively represent the temporal-spatial variation of chlorophyll a concentration in the Nansi Lake water,empirical model inversion algorithm was adopted to establish regression analysis model of remote sensing data and real-time or quasi-real-time chlorophyll a concentration based on single band reflectance or band reflectance combination,based on the data from the wide field of view camera in Gaofen-1 satellite as data source.The accuracy of the model was verified and inversion was performed.The results show that λ_(B2)/(λ_(B1)+λ_(B3)) is the optimal inversion band,the determination coefficient is greater than 0.7,the average relative error of the model is 11.11%,and the normalized root mean square error is 11.46%.The accuracy of the model is high,and it can be used for the quantitative inversion of chlorophyll a concentration in the waters of the Nansi Lake.The inversion model was applied to four landscape images in different seasons in 2021,and the temporal-spatial distribution of chlorophyll a concentration in different seasons in the waters of the Nansi Lakes is obtained,which is basically consistent with the actual situation.
作者
刁超
桑国庆
彭涛
王君诺
DIAO Chao;SANG Guoqing;PENG Tao;WANG Junnuo(School of Water Conservancy and Environment,University of Jinan,Jinan 250022,Shandong,China;Rizhao Water Conservancy Bureau,Rizhao 262300,Shandong,China;Shuifa Planning and Design Co.,Ltd,Jinan 250100,Shandong,China)
出处
《济南大学学报（自然科学版）》
CAS
北大核心
2023年第4期408-414,420,共8页
Journal of University of Jinan(Science and Technology)
基金
国家自然科学基金项目(51909104)
山东省自然科学基金项目(ZR2020ME249)。
关键词
遥感数据
叶绿素A
反演模型
南四湖
remote sensing data
chlorophyll a
retrieval model
the Nansihu Lake
