Methods of Retrieving Suspended Particulate Matter Concentration in Sea Reclamation Area with Satellite Remote Sensing

被引：0
|
作者：
Song N. [1 ,2 ]
Wang N. [3 ]
Wu N. [3 ]
Lin W. [3 ]
机构：
[1] Institute of Bohai Sea, National Marine Environmental Monitoring Center, Dalian
[2] State Environmental Protection Key Laboratory of Marine Ecological Environment Restoration, Dalian
[3] College of Transportation Engineering, Dalian Maritime University, Dalian
来源：
Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering | 2020年 / 28卷 / 05期
关键词：
Monitoring; Neutral network; Reclamation; Remote sensing; Space-time distribution; Suspended particulate matter;
D O I：
10.16058/j.issn.1005-0930.2020.05.009
中图分类号：
学科分类号：
摘要：
This paper aimed to explore an effective way to monitor suspended particulate matter concentration (SPMC) in sea reclamation area (SRA) with satellite remote sensing. Traditional regression algorithms and an artificial neural network (ANN) were used to develop the retrieval model for SPMC in SRA. Through the validation with in-situ water samples, the ANN model has a superior performance with a coefficient determination (R2) of 0.95 and mean relative error (MRE) of 30%, while other models have an inferior performance with MRE of 120%. This phenomenon is mainly caused by the optical characteristics of SRA. Using the developed ANN model, the retrieval results revealed that, the SPMC in the SRA during 2010~2015 changes seasonally with higher in winter and lower in summer; the higher SPMC is found around the construction site, while the lower values were found in the far offshore regions. The distribution pattern of SPMC in the SRA is mainly caused by the reclamation construction, wind force and tidal current directions. © 2020, The Editorial Board of Journal of Basic Science and Engineering. All right reserved.
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页码：1108 / 1121
页数：13
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共 40 条
  • [11] Yang Ting, Zhang Hui, Wang Qiao, Et al., Retrieving for chlorophyll-a concentration and suspended substance concentration based on HJ-1A HIS image, Environmental Science, 11, pp. 3207-3214, (2011)
  • [12] Zhou Xiaoyu, Sun Deyong, Li Yunmei, Et al., Hyperspectral remote sensing of total suspended matter concentrations in lake Taihu based on water optical classification, Environmental Science, 7, pp. 2618-2627, (2013)
  • [13] Chen J, Cui T W, Qiu Z F, Et al., A three-band semi-analytical model for deriving total suspended sediment concentration from HJ-1A/CCD data in turbid coastal waters, ISPRS Journal of Photogrammetry and Remote Sensing, 93, pp. 1-13, (2014)
  • [14] Shi Kun, Li Yunmei, Liu Zhonghua, Et al., Estimation of total suspended matter concentration based on semi-analysis, Environmental Science, 6, pp. 1571-1580, (2011)
  • [15] Cao Yin, Ye Yuntao, Zhao Hongli, Et al., Ensemble modeling methods for remote sensing retrieval of water quality parameters in inland water, China Environmental Science, 37, 10, pp. 3940-3951, (2017)
  • [16] Le C F, Lehrter J C, Schaeffer B A, Et al., Bio-optical water quality dynamics observed from MERIS in Pensacola Bay, Florida, Estuarine Coastal and Shelf Science, 173, pp. 26-38, (2016)
  • [17] Martinez J M, Espinoza-Villar R, Armijos E, Et al., The optical properties of river and floodplain waters in the Amazon River Basin: Implications for satellite-based measurements of suspended particulate matter, Journal of Geophysical Research-Earth Surface, 120, 7, pp. 1274-1287, (2015)
  • [18] Sun Deyong, Li Yunmei, Yue Chengfeng, Et al., Scattering characteristics of Taihu Lake and its relationship models with suspended particle concentration, Environmental Science, 28, 12, pp. 2688-2694, (2007)
  • [19] Zhan Haigang, Shi Ping, Chen Chuqun, Retrieval of chlorophyll concentration in seawater using neural network, Science Bulletin, 45, 17, pp. 1879-1884, (2000)
  • [20] Chen J, Quan W T, Cui T W, Et al., Estimation of total suspended matter concentration from MODIS data using a neural network model in the China eastern coastal zone, Estuarine Coastal and Shelf Science, 155, pp. 104-113, (2015)
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