| 基于光学分类的太湖水体叶绿素a浓度高光谱遥感 |
| 摘要点击 3099 全文点击 1396 投稿时间：2012-05-29 修订日期：2012-07-06 |
| 查看HTML全文
查看全文 查看/发表评论 下载PDF阅读器 |
| 中文关键词 复杂混浊水体 光学分类 叶绿素a浓度 反演模型 太湖 |
| 英文关键词 complex turbid waters water optical classification chlorophyll a concentration retrieval model Lake Taihu |
|
| 中文摘要 |
| 利用2006年11月、2008年11月、2010年5月和8月的太湖水体原位观测数据,在对水体进行光学分类的基础上,分别建立了针对各个类别水体的叶绿素a浓度高光谱反演模型. 通过对每类水体各个模型的性能比较,结果表明:第一类水体,四波段模型为最优模型; 第二类和第三类水体,一阶微分模型均为最优模型. 同时,也比较了水体分类前后模型的表现,表明水体分类后模型在精度和稳定性上都有不同程度的提高. 本研究结论对光学复杂混浊湖泊水体的水色遥感具有参考意义. |
| 英文摘要 |
| Four field investigations into the Lake Taihu were carried out for collecting in situ observed data in Nov., 2006, Nov., 2008, May and Aug., 2010. On the basis of water optical classification, different retrieval algorithms were developed, specifically for different types of waters. The obtained optimal models were ①the four-band model for Type 1 water; ②the first-order differential model for Type 2 and Type 3 waters. Meanwhile, an optimal retrieval model was also established using the same aggregated calibration data. Some comparisons were done between the developed models for the classified and non-classified waters. The compared results showed that models for the classified waters had better performances than that for the non-classified water, in both retrieval accuracy and model stability. The findings of this study are significant for promoting the development of water color remote sensing for optically complex turbid inland waters. |
|
|
|
