4.5 Article

Comparison of different semi-empirical algorithms to estimate chlorophyll-a concentration in inland lake water

期刊

ENVIRONMENTAL MONITORING AND ASSESSMENT
卷 170, 期 1-4, 页码 231-244

出版社

SPRINGER
DOI: 10.1007/s10661-009-1228-7

关键词

Field spectral; Lake Chagan; Continuum removal; Three-band model

资金

  1. National Natural Science Foundation of China [40801137, 40871168, 40671138]
  2. Chinese Academy of Sciences [07YJ011001, CXNIGLAS200807]

向作者/读者索取更多资源

Based on in situ water sampling and field spectral measurement from June to September 2004 in Lake Chagan, a comparison of several existing semi-empirical algorithms to determine chlorophyll-a (Chl-a) content was made by applying them to the field spectra and in situ chlorophyll measurements. Results indicated that the first derivative of reflectance was well correlated with Chl-a. The highest correlation between the first derivative and Chl-a was at 680 nm. The two-band model, NIR/red ratio of R(710/670), was also an effective predictor of Chl-a concentration. Since the two-band ratios model is a special case of the three-band model developed recently, three-band model in Lake Chagan showed a higher resolution. The new algorithm named reverse continuum removal relies on the reflectance peak at 700 nm whose shape and position depend strongly upon chlorophyll concentration: The depth and area of the peak above a baseline showed a linear relationship to Chl-a concentration. All of the algorithms mentioned proved to be of value and can be used to predict Chl-a concentration. Best results were obtained by using the algorithms of the first derivative, which yielded R (2) around 0.74 and RMSE around 6.39 mu g/l. The two-band and three-band algorithms were further applied to MERIS when filed spectral were resampled with regard to their center wavelengths. Both algorithms showed an adequate precision, and the differences on the outcome were small with R (2) = 0.70 and 0.71.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据