0
第4期
第28枣
2016年8月
浙江水利水电学院学报
J. Zhejiang Univ of Wat, Res & Electric Pow
Vol.28No.4 Aug.2016
基于归一化光谱的浑浊水体叶绿素a浓度遥感估算
程春梅
（浙江水利水电学院测绘与市政工程学院，浙江杭州
310018）
捕
要：光语归一化是将光语统一到相同的尺度进行数据分析的方法，有助于削弱环境因素对光语的影响.本文首
先讨论了光谱归一化处理对水依叶绿素a浓度反演的影响，然后基于归一化光谱提出了一个改进的两波投模型。使用大潮水体2010年9-10月和2011年4~5月的实测数据，对归一化前后建立的叶绿素a估算模型的对比分析表明，归一化处理增加了样点光谱反制率的集中程度，可以改进用相关分析方法建立的比值模型和一阶分模型的精度及应用精度.基于归化光谱建立了新的两波反演模型RN(A1）-1-RN(A2）-1，并使用2010年和2011 年两期数据建立模型并验证，结果表明新波投组合的模型精度优于波段比值模型，模型应用精度优于三波段和四
波段模型，该组合可为泽浊水体中叶绿素a浓度的逐感估算提供参考。关键词：光谱归一化；叶绿素a浓度；水色遂感
中图分类号：X131.2
文献标志码：A
文章编号：1008536X(2016)08-0058-08
RemoteSensingEstimationof Chlorophyll-aConcentrationin
Turbidity Water Based on Spectral Normalization
CHENG Chun-mei
( College of Geomaties and Municipal Engineering, Zhejiang University of Water
Resources and Electrie Power, Hangzhou 310018, China)
Abstract: Speetral normalization is the method that unifies spectra to the same scale before data analysis, and this process ing can weaken the impact of environmental factors on the spectrum. This study first discussed the impact of spectral nor-malization on the remote sensing inversion of chlorophyll-a eoncentration in water, and then proposed an improved two-band model based on the normalized spectra. Based on the in situ speetrum dsta in September-October, 2010 and April-May, 2010, Taihu Lake , China, this study compared the performance of the Chla estimation models built by the data before and after normalization, and the results show that spectral normalization increased speetral centralization of different samples at each wavelength, and the spectral normalization increased the model precision and validation precision of band ratio and first derivative model built by correlation analysis. A new two-band inversion model RN( >, ) 1 RN( A, ) 1 was estab-lished based on the normalized spectra and was validated by the data in 2010 and 2011. Results show that the model and validation precision of the new combination were better than the band ratio model and the validation precision was better than the three-band and four-band models, indicating that the new combination can be a reference for the remote sensing es-timation of chlorophyll-a concentration in turbidity water.
Key words;speetral normalization; chlorophyll-a concentration; water color remote sensing
引言
湖泊是地球上重要的淡水资源，随着经济发展收精日期：2016-03-20
基金项目：浙江省教育厅科研基金资助项目（Y201534666）
作者简介：程春梅（1987-），女，湖北武汉人，讲师，研究方间
水环境遥感与地理信息系统万方数据
和工业化程度的加剧，内陆湖泊浑浊水体的富营养化问题一直是人们关注的重点.叶绿素a是反映湖泊水体营养化程度的重要参数，其含量能够在一定程度上反映水质状况.由于遥感监测叶绿素a具有范围广、速度快、成本低和便于进行长期动态监测的优势，使用遥感数据进行水体叶绿素a浓度（Chla）的反演研究一直是水色遥感研究的热