%0 Journal Article
%T Application of hyper-spectral remote sensing in monitoring chlorophyll-a concentration in drinking water source reservoir in North China<br>北方典型水库型水源地水体叶绿素a 含量遥感监测研究
%A HAN Li-Mei
%A XIAO Jie-Ying
%A WANG Yu-You
%A CUI Jian-Sheng
%A <br>韩立妹
%A 肖捷颖
%A 王宇游
%A 崔建升
%J 中国生态农业学报
%D 2012
%I 
%X Remote sensing has been widely used for water quality monitoring in recent decades. Hyper-spectral remote sensing is a very effective technology for detecting large-scale water eutrophication, which has attracted lots of research in monitoring chlorophyll-a. In this paper, we used hyper-spectral remote sensing technology to present a method for monitoring chlorophyll-a concentration in Huangbizhuang Reservoir in Shijiazhuang, Hebei Province. In-situ hyper-spectral measurements were conducted by using the portable EKO MS-720 spectroradiometer at 10 different points in Huangbizhuang Reservoir, the source of drinking water for Shijiazhuang City and irrigation water for a large area of croplands along Shijin Irrigation Channel. Water samples were also simultaneously collected for laboratory analyses. Sample site position information was recorded via portable GPS. Chlorophyll-a concentration of the water samples were measured in laboratory by Acetone-spectrophotometric. The hyper-spectral data were converted into remote sensing reflectance. Then different band reflectance, reflectance ratio and other reflectance indices were designed and calculated. Linear correlation analysis between chlorophyll-a concentration and spectral reflectance, reflectance ratio and first-order differential of the water sample reflectance were also analyzed and compared. At last, the spectral reflectance ratio model and the first-order differential model were selected based on obtained correlation coefficient and significance. The results showed that Huangbizhuang Reservoir water chlorophyll-a concentration was low, with the highest concentration of 4.55 g·L-1. It indicated that the reservoir water was in good condition. Spectral reflectance ratio model (R705nm/R680nm) showed close correlation with chlorophyll-a concentrations (r2 = 0.736 6). On the other hand, the 696 nm first-order differential reflectance model showed a lot more significant correlation with chlorophyll-a concentrations in the entire analytical tests (r2 = 0.875 5). This illustrated that the 696 nm first-order differential reflectance model was more effective for chlorophyll-a concentration monitoring in Huangbizhuang Reservoir. Through linear regression estimation, chlorophyll-a concentration in Huangbizhuang Reservoir was generally at the state of oligotrophication. Hence with regard to chlorophyll-a concentration, Huangbizhuang Reservoir water was suitable for domestic, industrial and irrigation use. The method proposed in this work had potential applications in environmental management for improved chlorophyll-a concentration monitoring efficiency in large-scale water bodies. It was also applicable in policy/decision- makings needed for early warning and prevention of water eutrophication.
%K Drinking water resource reservoir
%K Chlorophyll-a
%K Remote sensing monitoring
%K Reflectance spectra
%K Band ratio model
%K First-order differential model<br>典型水库型水源地
%K 叶绿素a
%K 遥感监测
%K 反射光谱
%K 波段比值模型
%K 一阶微分模型
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=03F54A49DE00578AA0E5DDF5BC021AA7&cid=1A8B5357F0EF07B8&jid=AB3ABF502E2E1FF39F0E3B80164C9031&aid=9B3C227A81E2A28CEB5DB90F703B5A90&yid=99E9153A83D4CB11&vid=A04140E723CB732E&iid=9CF7A0430CBB2DFD&sid=F5C4DB540B02644F&eid=8C8B0901DFA6ECA2&journal_id=1671-3990&journal_name=中国生态农业学报&referenced_num=0&reference_num=0