Algorithms and Schemes for Chlorophyll a Estimation by Remote Sensing and Optical Classification for Turbid Lake Taihu, China
文献类型：期刊论文
| 作者 | Zhang, Fangfang1; Li, Junsheng1; Shen, Qian1; Zhang, Bing1; Wu, Chuanqing1; Wu, Yuanfeng1; Wang, Ganlin1; Wang, Shenglei1; Lu, Zhaoyi1 |
| 刊名 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
 |
| 出版日期 | 2015 |
| 卷号 | 8期号:1页码:246-256 |
| 关键词 | Chlorophyll a (CHLA) estimation algorithm Lake Taihu optical classification remote sensing |
| 通讯作者 | Zhang, FF (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China. |
| 英文摘要 | Monitoring chlorophyll a (CHLA) by remote sensing is particularly challenging for turbid productive waters. Although several empirical and semianalytical algorithms have been developed for such waters, their accuracy varies significantly due to variability in optical properties. In this paper, we evaluated the performance of six CHLA concentration (C-chla) estimation algorithms [e. g., two-band ratio algorithm (TBR), normalized difference chlorophyll index (NDCI), synthetic chlorophyll index (SCI), three-band algorithm (TBS), four-band algorithm (FBS), and improved four-band algorithm (IOC3M)] for a highly turbid lake based on remote sensing reflectance classification. Remote sensing reflectance was classified using the iterative k-mean clustering method. We also developed four estimation schemes (S1-S4) for the six algorithms to assess the effect of the estimation scheme on the accuracy of the algorithms. The estimation schemes were developed based on classification methods (no, soft, or hard classification) and the optimization bands used. The six algorithms performed differently for different remote sensing reflectance classes and different estimation schemes. The optimal algorithms for Classes 1, 2, and 3 were TBS, NDCI, and TBR, respectively. For the four estimation schemes, TBS and NDCI outperformed the other four algorithms. The accuracy of TBS and NDCI was higher than FBS, IOC3M, TBR, and SCI. The accuracy of all six algorithms was improved by remote sensing reflectance classification, particularly for Classes 2 and 3. Soft classification with recalibration of the bands for each class outperformed hard classification for all the three classes. |
| 研究领域[WOS] | Engineering, Electrical & Electronic ; Geography, Physical ; Remote Sensing ; Imaging Science & Photographic Technology |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:000349550400033 |
| 源URL | [http://ir.ceode.ac.cn/handle/183411/38324]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1.[Zhang, Fangfang 2.Li, Junsheng 3.Shen, Qian 4.Zhang, Bing 5.Wu, Yuanfeng 6.Wang, Ganlin 7.Wang, Shenglei 8.Lu, Zhaoyi] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China 9.[Wu, Chuanqing] Minist Environm Protect, Satellite Environm Applicat Ctr, Beijing 100029, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Fangfang,Li, Junsheng,Shen, Qian,et al. Algorithms and Schemes for Chlorophyll a Estimation by Remote Sensing and Optical Classification for Turbid Lake Taihu, China[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2015,8(1):246-256. |
| APA | Zhang, Fangfang.,Li, Junsheng.,Shen, Qian.,Zhang, Bing.,Wu, Chuanqing.,...&Lu, Zhaoyi.(2015).Algorithms and Schemes for Chlorophyll a Estimation by Remote Sensing and Optical Classification for Turbid Lake Taihu, China.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,8(1),246-256. |
| MLA | Zhang, Fangfang,et al."Algorithms and Schemes for Chlorophyll a Estimation by Remote Sensing and Optical Classification for Turbid Lake Taihu, China".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 8.1(2015):246-256. |
入库方式： OAI收割
来源：遥感与数字地球研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。