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基于偏最小二乘法的巢湖悬浮物浓度反演
引用本文:刘忠华,李云梅,吕恒,徐祎凡,徐昕,黄家柱,檀静,郭宇龙.基于偏最小二乘法的巢湖悬浮物浓度反演[J].湖泊科学,2011,23(3):357-365.
作者姓名:刘忠华  李云梅  吕恒  徐祎凡  徐昕  黄家柱  檀静  郭宇龙
作者单位:南京师范大学虚拟地理环境教育部重点实验室,南京,210046
基金项目:高分辨率对地观测系统国家科技重大专项项目,国家自然科学基金项目,江苏省2008年度普通高校研究生科研创新计划,南京师范大学优秀博士论文培养计划项目
摘    要:悬浮物浓度是水质评价的重要参数.对2009年6月巢湖实测的高光谱数据进行小波变换以去除数据冗余,减少建模时间.考虑到不同的小波基函数和分解尺度对数据压缩的影响,采用3个指标作为评价标准,最终选择小波基函数为Db4,分解尺度为4的小波变换,经小波变换后,原来的451个波段的光谱数据压缩为34个特征变量.利用小波变换后的光...

关 键 词:小波变换  偏最小二乘法  高光谱数据  悬浮物  巢湖
收稿时间:2010/5/21 0:00:00
修稿时间:2010/10/8 0:00:00

Inversion of suspended matter concentration in Lake Chaohu based on Partial Leastsquares Regression
LIU Zhonghu,LI Yunmei,LV Heng,XU Yifan,XU Xin,HUANG Jiazhu,TAN Jing and GUO Yulong.Inversion of suspended matter concentration in Lake Chaohu based on Partial Leastsquares Regression[J].Journal of Lake Science,2011,23(3):357-365.
Authors:LIU Zhonghu  LI Yunmei  LV Heng  XU Yifan  XU Xin  HUANG Jiazhu  TAN Jing and GUO Yulong
Affiliation:Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210046, P. R. China,Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210046, P. R. China,Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210046, P. R. China,Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210046, P. R. China,Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210046, P. R. China,Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210046, P. R. China,Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210046, P. R. China and Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210046, P. R. China
Abstract:Suspended matter concentration is an important parameter of water quality evaluation.Hyperspectral data measured in Lake Chaohu in June,2009 were processed by wavelet transform in order to remove data redundancy and reduce modeling time.Three evaluation indexes were selected considering the effect of different wavelet functions and decomposed scales on the data compression,and the wavelet function Db4 and decomposed scale 4 were determined finally.The original hyperspectral data of 451 bands were compressed...
Keywords:Wavelet transform  Partial Least-squares Regression  hyperspectral data  suspended matter  Lake Chaohu  
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