基于GOCI和MODIS数据的太湖水体叶绿素a浓度反演研究.doc

文档介绍：
基于 GOCI 和 MODIS 数据的太湖水体叶绿素 a
浓度反演研究#
包颖1,田庆久1,孙绍杰2**
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(1. 南京大学国际地球系统科学研究所,南京 210023;
2. 美国南佛罗里达大学)
摘要:本文以高时间分辨率遥感影像 GOCI 和 MODIS 为数据源,利用“Gordon 改进算法”实现二类水体大
气校正,并在此基础上分别建立半分析模型和经验模型实现太湖水体叶绿素 a 浓度的估算。研究结果显示,
基于 MODIS 辅助数据的方法能快速有效的完成 GOCI 和 MODIS 等数据的大气校正,提高影像中水体信息含量;
并且 GOCI 和 MODIS 数据的 Chl-a 反演结果不仅能很好的反映蓝藻的空间分布,其反演模型的平均相对误差
也表明 GOCI 和 MODIS 数据在实时动态监测富营养化污染方面具有较大的应用潜力。
关键词:环境科学;叶绿素 a 浓度;GOCI;MODIS;半分析模型;太湖
中图分类号:X5
Estimation of Chl-a in Taihu Lake using GOCI and
MODISsatellite data
BAO Ying1, TIAN Qingjiu1, SUN Shaojie2
(1. International Institute for Earth System Science,Nanjing University,Nanjing 210023;
2. University of South Florida)
Abstract: In this paper, GOCI and MODIS with high temporal resolution were used as the data sourse
for Chl-a concentration estimation in Taihu Lake. Base on the algrithom of atmospheric correction
which was developed from Gordon method, semi-analysis model and empirical model were separately
established for Chl-a concentration. The results showed that: 1) atmospheric correction method which
was based on MODIS vicarious calibration could apply to GOCI and MODIS, improving the qualtiy of
the images. 2) the distributions of Chl-a estimated from GOCI and MODIS could reflect the actual
condition of algae. And the average relative errors also indicated that both of the data had potential in
real - time mo