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This book is a comprehensive reference on the theory and practical applications of artificial neural networks for atmospheric remote sensing. It covers the physical foundations of remote sensing (radiative transfer, sensor technologies), inversion and estimation techniques, and explains how neural networks — especially multilayer perceptrons — can be used to retrieve geophysical parameters from satellite data. The authors discuss issues such as data preprocessing, network initialization, training, model selection, and performance evaluation, and present applied examples such as precipitation retrieval and atmospheric profile inversion from microwave and hyperspectral infrared observations.

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245: $a: Neural Networks in Atmospheric Remote Sensing
245: $b:
082: $a:
100: $a: William J. Blackwell & Frederick W. Chen
650: $a: Computer Science
250: $a:
440: $v:
250: $b: Artech House
250: $c: 2009
020: $a: 978-1-59693-372-9
300: $a: 215