Data Fusion and Modelling

Editors: Klopfer, M.

Pages: 1-165

Publisher: SANY Consortium

ISBN: 9783000285714

Abstract:

Data fusion and modelling techniques are usually used to integrate observation data, contextual data and phenomenological models from different sources in order to obtain new environmental information where and when sensor measurements are not available. Observation sensors may include in-situ, airborne and space-borne types, while models may include deterministic and stochastic models. In addition, data fusion numerical techniques provide a framework for integrating information uncertainties which are generated from sensor measurements and models with various inaccuracies. Several data fusion algorithms have been classified and developed in the SANY project. The classification exercise of these algorithms has been useful for hosting them under the SensorSA services and generically deploying them for multiple environmental risks and decision support pilot applications in SANY (Sabeur 2007)

Source: Manual