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一种基于GOCI数据的叶绿素a浓度三波段估算模型
摘要点击 2551  全文点击 1320  投稿时间:2015-01-08  修订日期:2015-04-02
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中文关键词  GOCI  内陆二类水体  叶绿素a浓度  三波段
英文关键词  GOCI  inland case 2 water  chlorophyll-a concentration  three band model
作者单位E-mail
郭宇龙 江苏省地理信息资源开发与利用协同创新中心, 南京 210023 gyl.18@163.com 
李云梅 江苏省地理信息资源开发与利用协同创新中心, 南京 210023
南京师范大学江苏省碳氮循环过程与污染控制重点实验室, 南京 210023 
liyunmei@njnu.edu.cn 
李渊 浙江工商大学旅游与城市管理学院, 杭州 310018  
吕恒 江苏省地理信息资源开发与利用协同创新中心, 南京 210023  
刘阁 江苏省地理信息资源开发与利用协同创新中心, 南京 210023  
王旭东 江苏省地理信息资源开发与利用协同创新中心, 南京 210023  
张思敏 江苏省地理信息资源开发与利用协同创新中心, 南京 210023  
中文摘要
      以标准三波段算法为基础,构建了适用于GOCI影像数据的叶绿素a浓度三波段估算模型. 并以三峡水库、巢湖、洞庭湖和太湖水体的289组实测叶绿素a浓度以及光谱数据作为基础,模拟了GOCI影像和MERIS影像波段,率定了模型参数,并与MERIS三波段算法和目前常用的GOCI波段比值算法进行了对比分析,最终用GOCI影像数据进行了独立数据验证. 结果表明:① 对目前的数据集,680 nm处和660 nm处的色素颗粒物吸收系数具有相对固定的比例关系,比值为1.351; ② GOCI三波段模型在模型率定中,得到与MERIS三波段模型近似的效果,线性拟合的决定系数为0.809,略低于MERIS三波段模型的0.820,但明显优于GOCI比值模型(0.450),有效避免了GOCI波段比值模型中在叶绿素a浓度低值区出现的"扩散"现象,体现出较好的普适性; ③ 通过验证数据集中平均相对误差和均方根误差两个误差指标的对比,发现GOCI三波段模型误差表现与建模数据一致,与MERIS数据接近,明显优于GOCI波段比值模型; ④ 通过GOCI影像的同步验证,发现GOCI波段比值算法会对太湖叶绿素a浓度产生明显的低估,且难以体现叶绿素a浓度空间变异. GOCI三波段算法效果相对较好. 相比于目前常用的波段比值算法,GOCI三波段算法具有更高的稳定性和精度,有较强的应用潜力.
英文摘要
      A GOCI-based three band model is proposed for chlorophyll-a concentration estimation based on the classical three band model. The model was built based on 289 in-situ measured chlorophyll-a concentration and hyperspectral spectrums-simulated GOCI spectrums, and was compared with MERIS-based three band model and GOCI band ratio model. At last, the model was validated using several GOCI images and an independent in-situ sampling dataset. The results showed that: ① For the current dataset, the ratio of aph(680) and aph(660) was relatively stable. ② The GOCI-based three band algorithm had a similar performance with MERIS-based three band algorithm in the modeling dataset. The R2 value of the GOCI-based three band model was 0.809, which was a little lower than that of the MERIS-based three band model (R2=0.820), but was obviously higher than that of GOCI band ratio model (R2=0.450). ③ The performance of GOCI-based three band model in the validation dataset was similar with that in the modeling dataset, which was close to that of the MERIS-based three band model, and significantly better than that of GOCI band ratio model. ④ The GOCI image data validation indicated that GOCI band ratio model would clearly underestimate chlorophyll-a concentration in Taihu Lake. The spatial difference of chlorophyll-a concentration that yielded by the band ratio model was not clear. Compared with the widely used band ratio algorithm, the GOCI-based three band algorithm has higher stability, better accuracy, and stronger potential in application.

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