太阳成8722(中国)有限公司-GREEN NO.1

标题：Assessment of water quality in natural river based on HJ1A/1B CCD multi-spectral remote sensing data作者：Xiao, Xiao; Xu, Jian; Hu, Chengfang; Wang, Zhaohui; Zhao, Dengzhong;Wen, Xiongfei; Cao, Bo; Cheng, Xuejun

来源出版物：MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL REMOTE SENSING TECHNOLOGY, TECHNIQUES AND APPLICATIONS V 卷：9263 文献号：UNSP 92631M DOI：10.1117/12.2068402 2014 出版年：2014

丛书：Proceedings of SPIE

会议名称：Conference on Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V

会议时间：OCT 14-16, 2014

会议地点：Beijing, PEOPLES R CHINA

摘要：This study selects the typical middle and lower reaches of Han River as the study area and focuses on water quality evaluation methods and water quality evaluation of the surface water of the river basin. On the basis of the field survey, the author conducted a water quality sampling survey in the study area in spring and summer in 2012. The main excessive factors in the study area are determined as TN and TP. Using HJ1A/1B CCD multi-spectral data, the multiple linear regression inversion model and neural network inversion model are established for content of TN and TP. In accordance with these inversion results, the single factor water quality identification indexes in the study area are obtained. The results show that, BP neural network model boasts the highest inversion accuracy and that the single factor water quality identification indexes resulting from its inversion results are highly accurate, reliable and applicable, which can really reflect the changes in water quality and better realize the evaluation of water quality in the study area. Water quality evaluation results show that the water pollution in the study area is organic pollution; the water quality of Han River experiences large differences in different regions and seasons; downstream indexes are superior to upstream indexes, and the indexes in summer are superior to those in spring; the TN index seriously exceeds the standard in spring and the TP index seriously exceeds the standard in some regions.

入藏号：WOS:000349892800032

文献类型：Proceedings Paper

语种：English

作者关键词：inversion model, Han River, HJ1A/1B, multispectral data, assessment

扩展关键词：MECKLENBURG LAKE DISTRICT; NEURAL-NETWORK; CHLOROPHYLL; GERMANY; MODEL

通讯作者地址：Xiao, Xiao;

地址：

[Xiao, Xiao]Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

研究方向：Remote Sensing; Optics

ISSN：0277-786X

ISBN:978-1-62841-330-4