Comments on "Water Quality Retrievals From Combined Landsat TM Data and ERS-2 SAR Data in the Gulf of Finland

Author

Sha, W.

Author_Institution

Archit. & Civil Eng, Queen´´s Univ., Belfast

Volume

45

Issue

6

fYear

2007

fDate

6/1/2007 12:00:00 AM

Firstpage

1896

Lastpage

1897

Abstract

A paper by Zhang , using a feedforward artificial neural network (ANN) for water quality retrievals from combined Thematic Mapper data and synthetic aperture radar data in the Gulf of Finland, has been published in this journal. This correspondence attempts to discuss and comment on the paper by Zhang The amount of data used in the paper by Zhang is not enough to determine the number of fitting parameters in the networks. Therefore, the models are not mathematically sound or justified. The conclusion is that ANN modeling should be used with care and enough data

Keywords

environmental science computing; neural nets; remote sensing; water; ERS-2 SAR data; Gulf of Finland; Landsat tm data; Thematic Mapper data; feedforward artificial neural network; synthetic aperture radar; water quality retrievals; Artificial neural networks; Equations; Indium phosphide; Information retrieval; Linear regression; Mathematical model; Neural networks; Neurons; Remote sensing; Satellites; Combined Thematic Mapper/synthetic aperture radar data; retrievals; water quality;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/TGRS.2007.895432

Filename

4215090