Title :
Modeling study in remote sensing of air pollution measured data
Author :
Andria, G. ; D´Orazio, A. ; Ekuakille, A. Lay ; Notarnicola, M.
Author_Institution :
Dipt. di Elettrotecnica ed Elettronica, Politecnico di Bari, Italy
Abstract :
The aim of this work is to study modeling of air pollution measured data that are remotely sensed through appropriate instrumentation. Modeling is basically important in order to validate measured data. We use spatial and bidimensional modeling to reduce uncertainty in recovering data. We also use Gaussian model and we study the possibility of decreasing recovering error by using mathematical parameters
Keywords :
Gaussian processes; air pollution measurement; geophysics computing; measurement errors; remote sensing; Gaussian model; air pollution; bidimensional modeling; mathematical parameters; railway diesel locomotive; recovering error; remote sensing; simulation; spatial modeling; uncertainty; Air pollution; Atmospheric measurements; Atmospheric modeling; Chemical analysis; Computational modeling; Current measurement; Mathematical model; Pollution measurement; Remote sensing; Uncertainty;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2000. IMTC 2000. Proceedings of the 17th IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-5890-2
DOI :
10.1109/IMTC.2000.848842
