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.
Modelling Study in Remote Sensing of Air Pollution Measured Data
LAY EKUAKILLE, Aime;
2000-01-01
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.File in questo prodotto:
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