Generalized regression neural network (GRNN)-based approach for colored dissolved organic matter (CDOM) retrieval: case study of Connecticut River at Middle Haddam Station, USA-Reference-Cited by-同舟云学术

Generalized regression neural network (GRNN)-based approach for colored dissolved organic matter (CDOM) retrieval: case study of Connecticut River at Middle Haddam Station, USA

Published:2014-08-12 Issue:11 Volume:186 Page:7837-7848
ISSN:0167-6369
Container-title:Environmental Monitoring and Assessment
language:en
Short-container-title:Environ Monit Assess

Author:

Heddam Salim

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s10661-014-3971-7.pdf

Reference46 articles.

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3. D’Alimonte, D., Zibordi, G., Berthon, J.F. (2004). Determination of CDOM and NPPM Absorption Coefficient Spectra from Coastal Water Remote Sensing Reflectance. IEEE Transactions on Geoscience and Remote Sensing, 42(8), doi: 10.1109/TGRS.2004.831444 .

4. Del Castillo, C. E., & Miller, R. L. (2008). On the use of ocean color remote sensing to measure the transport of dissolved organic carbon by the Mississippi River Plume. Remote Sensing of Environment, 112, 836–844. doi: 10.1016/j.rse.2007.06.015 .

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