Title :
Comments on "Water Quality Retrievals From Combined Landsat TM Data and ERS-2 SAR Data in the Gulf of Finland
Author_Institution :
Archit. & Civil Eng, Queen´´s Univ., Belfast
fDate :
6/1/2007 12:00:00 AM
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;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2007.895432
