| 基于Hydrolight的太湖水体区域化固有光学模型参数率定与验证 |
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| 作者姓名： | 黄佳慧 段洪涛 马荣华 张玉超 |
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| 作者单位： | 1. 中国科学院南京地理与湖泊研究所 湖泊与环境国家重点实验室, 南京 210008;
2. 中国科学院大学, 北京 100049 |
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| 基金项目： | 国家高技术研究发展（863）计划（2014AA06A509）、国家自然科学基金（41171271，41171273和41101316）和中国科学院南京地理与湖泊研究所“一三五”计划（NIGLAS2012135014和NIGLAS2012135010）资助 |
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| 摘 要： | 神经网络作为相对理想的可以业务化运行的水色遥感建模方法，在训练过程中需要巨量的数据集；而实测数据无法满足要求，需要利用水体辐射传输软件Hydrolight模拟数据集.利用数值统计方法对太湖7期野外实测数据进行分析，确定利用Hydrolight模拟太湖遥感反射率时，需要输入的藻类颗粒物、非藻类颗粒物和有色可溶性有机物的比吸收系数、比散射系数等参数；利用这些参数模拟遥感反射比，并与实测光谱数据进行比较，发现二者相关性普遍在0.95以上，证明确定的太湖区域化参数符合模拟需要，具有较强的实用价值.
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| 关 键 词： | 太湖 Ⅱ类水体 水色遥感 Hydrolight 辐射传输模型 |
| 收稿时间： | 2013-09-09 |
| 修稿时间： | 2014-02-20 |
Study on regional parameters of radiative transfer simulation based on Hydrolight in Taihu Lake |
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| Authors: | HUANG Jiahui DUAN Hongtao MA Ronghua ZHANG Yuchao |
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| Institution: | 1. State key laboratory of Lake Science and Environment, Nanjing Institute of Geography & Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | Neural network is a good modeling method in water color remote sensing field, and it needs a large amounts of training data sets. However, in situ data sets are far from enough for meeting the requirement of large amounts of training data sets in neural network. So Hydrolight is used to cover the shortage, and it can simulate large-scale data sets. Based on in situ data of 7 months from 2008 to 2011 in Taihu Lake and by using related numerical statistical methods, the primary required simulated parameters such as the mass-specific absorption coefficients of chlorophyll particles, mineral particles, and colored dissolved organic matter (CDOM) and the mass-specific scattering coefficients of chlorophyll particles and mineral particles are determined. Results show that, compared with the measured remote sensing reflectance spectrum, the simulated remote sensing reflectance spectrum matches well with the former one and the correlation coefficient reaches 0.95 generally. This study provides a good foundation for building large scale training data sets of Taihu Lake in neural network simulation. |
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| Keywords: | Taihu Lake water of case 2 lake color remote sensing Hydrolight radiation transfer model |
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