Title :
Pre/postprocessing in the radiometric inversion of atmospheric profiles by using neural networks
Author :
Frate, Fabio Del ; Schiavon, Giovanni
Author_Institution :
Rome Univ., Italy
Abstract :
A new neural network algorithm for the inversion of radiometric data to retrieve atmospheric profiles of temperature and vapor has been developed. The potentiality of the neural networks has been exploited not only for inversion purposes but also for data feature extraction and dimensionality reduction. In its complete form, the algorithm uses a neural network architecture consisting of 3 stages: the input stage reduces the dimension of the input vector, the middle stage performs the mapping from the reduced input vector to the reduced output vector, the third stage brings the output of the middle stage to the desired actual dimension. The effectiveness of the algorithm has been evaluated comparing its performance to that obtainable with more traditional linear techniques
Keywords :
atmospheric humidity; atmospheric techniques; atmospheric temperature; feedforward neural nets; geophysical signal processing; geophysics computing; neural nets; radiometry; remote sensing; algorithm; atmosphere; atmospheric profile; dimensionality reduction; feedforward neural net; humidity; inverse problem; measurement technique; meteorology; microwave radiometry; neural net; neural network algorithm; postprocessing; preprocessing; radiometric inversion; remote sensing; signal processing; temperature; vertical profile; water vapor; water vapour; Atmospheric modeling; Brightness temperature; Intelligent networks; Microwave radiometry; Network topology; Neural networks; Performance evaluation; Principal component analysis; Temperature measurement; Vectors;
Conference_Titel :
Geoscience and Remote Sensing Symposium Proceedings, 1998. IGARSS '98. 1998 IEEE International
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4403-0
DOI :
10.1109/IGARSS.1998.691458