Retrieval of water quality parameters by neural network and analytical algorithm in Guanting Reservoir in Hebei Province in China

Xinyu Lan, Ziqi Guo, Ye Tian, Xiaoen Lei, Jie Wang
{"title":"Retrieval of water quality parameters by neural network and analytical algorithm in Guanting Reservoir in Hebei Province in China","authors":"Xinyu Lan, Ziqi Guo, Ye Tian, Xiaoen Lei, Jie Wang","doi":"10.1109/IGARSS.2015.7325866","DOIUrl":null,"url":null,"abstract":"Based on the measured spectra in the research area of Guangting reservoir, we build the model to retrieve chlorophyll-a, suspended solid and yellow substance. The paper mainly achieved the following results: we adopted matrix inversion method and L-M & NN method to analyse the water quality parameters, the selection schemes of the spectral band include REF, DER, RAN method, and then use the Guanting Reservoir experiment data for inspection and comparative analysis. The results showed that: the retrieval accuracy of L-M & NN method was better than matrix inversion method for three ocean color elements, the RAN weighted method overall had better retrieval accuracy. For Cchla, acdom (440), the best scheme in band selection is RAN, REF showed better retrieval accuracy for Cs.","PeriodicalId":125717,"journal":{"name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGARSS.2015.7325866","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Based on the measured spectra in the research area of Guangting reservoir, we build the model to retrieve chlorophyll-a, suspended solid and yellow substance. The paper mainly achieved the following results: we adopted matrix inversion method and L-M & NN method to analyse the water quality parameters, the selection schemes of the spectral band include REF, DER, RAN method, and then use the Guanting Reservoir experiment data for inspection and comparative analysis. The results showed that: the retrieval accuracy of L-M & NN method was better than matrix inversion method for three ocean color elements, the RAN weighted method overall had better retrieval accuracy. For Cchla, acdom (440), the best scheme in band selection is RAN, REF showed better retrieval accuracy for Cs.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于神经网络和解析算法的河北官厅水库水质参数检索
在广亭水库研究区实测光谱的基础上,建立了叶绿素-a、悬浮物和黄色物质的反演模型。本文主要取得了以下成果:采用矩阵反演法和L-M & NN法对水质参数进行分析,光谱波段的选择方案包括REF、DER、RAN法,并利用观厅水库实验数据进行检验和对比分析。结果表明:L-M & NN方法对三种海洋颜色元素的检索精度优于矩阵反演方法,RAN加权方法总体上具有更好的检索精度。对于Cchla, acdom(440),波段选择的最佳方案是RAN, REF对Cs的检索精度更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Interferometric and polarimetric methods to determine SWE, fresh snow depth and the anisotropy of dry snow Usefulness assessment of polarimetric parameters for line extraction from agricultural areas DEM and DHM reconstruction in tropical forests: Tomographic results at P-band with three flight tracks Nationwide ground deformation monitoring by persistent scatterer interferometry MICAP (Microwave imager combined active and passive): A new instrument for Chinese ocean salinity satellite
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1