文献类型：期刊文献

中文题名：湛江湾水体颗粒物后向散射特性及其遥感反演研究

英文题名：Particulate Backscattering Characteristics and Remote Sensing Retrieval in the Zhanjiang Bay

作者：余果[1,2];钟雅枫[1];付东洋[2,3,4];刘大召[2,3,4];徐华兵[2]

机构：[1]广东海洋大学化学与环境学院,广东湛江524088;[2]广东海洋大学电子与信息工程学院,广东湛江524088;[3]南方海洋科学与工程广东省实验室(湛江),南海资源大数据中心,广东湛江524025;[4]广东省海洋遥感与信息技术工程技术中心,广东湛江524088

年份：2024

卷号：44

期号：3

起止页码：793

中文期刊名：光谱学与光谱分析

外文期刊名：Spectroscopy and Spectral Analysis

收录：北大核心2023、SCI-EXPANDED(收录号：WOS:001202652600028)、CSTPCD、、EI(收录号：20241215764015)、CSCD2023_2024、Scopus、WOS、北大核心、CSCD、PubMed

基金：国家自然科学基金项目(42106148,42206187);广东省教育厅重点研究项目(2019KZDXM019);南方海洋科学与工程广东省实验室(湛江)项目(ZJW-2019-08);国家重点研发计划项目(2022YFC3103101)资助。

语种：中文

中文关键词：颗粒物后向散射特性;遥感反演;湛江湾;随机森林

外文关键词：Particulate backscattering characteristics;Remote sensing retrieval;Zhanjiang Bay;Random forest

中文摘要：湛江湾2018年1月的原位调查,获得了原位遥感反射率(Rrs)、颗粒物后向散射系数(b_(bp))、叶绿素a(Chl a)和无机悬浮颗粒物(ISM)浓度等参数,分析了湛江湾水体颗粒物后向散射特性,并对颗粒物后向散射系数进行了遥感反演研究。研究结果显示:在研究区域观察到表层水体6个波段(420, 442, 470, 510, 590和700 nm)颗粒物后向散射系数的变异系数均在50%~60%之间,其变化范围为0.026 1~0.211 2 m^(-1),这意味着水体光学性质的复杂性。为了更好地量化b_(bp)的光谱特性,研究以510 nm为参考波段构建了b_(bp)幂函数光谱模型,获得的光谱模型斜率指数n=1.55。研究发现b_(bp)(510)与ISM呈现乘幂关系,与颗粒物组成(Chla/ISM)呈现指数关系,决定系数R2分别为0.74和0.62,表明研究区域颗粒物后向散射系数一阶驱动因子主要为无机悬浮颗粒物浓度,二阶驱动因子颗粒物组成对b_(bp)(510)变异也具有重要的贡献。为了准确估算湛江湾颗粒物后向散射系数,研究基于原位遥感反射率构建了随机森林模型,并与QAA-v6、 QAA-RGB和QAA-705三种半分析算法进行对比。随机森林模型的R2为0.86,平均绝对百分比误差MAPE为12%,均方根误差RMSE为0.02 m^(-1), QAA-v6、 QAA-RGB和QAA-705三种半分析算法R2分别为0.63、 0.71和0.53, MAPE分别为186%、 117%和243%, RMSE分别为0.16、 0.09和0.18 m^(-1),三种半分析算法虽然也具有较高的R2,但估计值和测量值之间存在显著差异,且MAPE和RMSE也较大,三种半分析算法显著低于随机森林方法的反演精度,表明运用遥感反演湛江湾b_(bp),随机森林方法具有较大的应用潜力。

外文摘要：Based on the in-situ investigation of Zhanjiang Bay in January 2018,the in-situ remote sensing reflectance(R rs),particulate backscattering(b_(bp)),chlorophyll a concentration(Chl a)and inorganic suspended matter concentration(ISM)were obtained.The backscattering characteristics of particulates in Zhanjiang Bay were analyzed,and the backscattering coefficients of particulates were retrieved by remote sensing.The research results showed that the coefficients of variation(CV)of b_(bp) in the six bands(420,442,470,510,590 and 700 nm)were between 50%~60%in surface water,and the variation range was 0.0261~0.2112 m^(-1),which also mean the complexity of optical properties in water.In order to better quantify the spectral characteristics of b_(bp),the power function spectral model of b_(bp) was constructed with 510 nm as the reference band,and the slope index of the spectral model was 1.55.In the meantime,the b_(bp)(510)had a power relationship with ISM and an exponential relationship with particulate composition(Chl a/ISM),while the determination coefficient(R 2)was 0.74 and 0.62,respectively.It indicated that the first-order driving factor of particulate backscattering in the bay was mainly the concentration of inorganic suspended matter,and the second-order driving factor of particulate composition also contributed to the variation of b_(bp)(510).In addition,in order to accurately estimate the particulate backscattering coefficient in Zhanjiang Bay,a random forest model was constructed based on in-situ remote sensing reflectance,and compared with three semi-analytical algorithms such as QAA-v6,QAA-RGB and QAA-705.The R 2 of random forest model was 0.86,the mean absolute percentage error(MAPE)was 12%,the root mean square error(RMSE)was 0.02 m^(-1),the R 2 of QAA-v6,QAA-RGB and QAA-705 was 0.63,0.71 and 0.53,the MAPE was 186%,117%and 243%,and the RMSE was 0.16,0.09 and 0.18 m^(-1),respectively.Although the three semi-analytical algorithms also had high R 2,there were significant differences between the estimated and measured values,and the MAPE and RMSE were also large.The retrieval accuracy of three semi-analytical algorithms was significantly lower than that of the random forest method,which indicated that the random forest method had great potential application when using remote sensing to retrieve the b_(bp) in Zhanjiang Bay.