Data fusion is the process of integration of multiple data and knowledge representing the same real-world object into a consistent, accurate, and useful representation.
Data fusion processes are often categorized as low, intermediate or high, depending on the processing stage at which fusion takes place. Low level data fusion combines several sources of raw data to produce new raw data. The expectation is that fused data is more informative and synthetic than the original inputs.
For example, sensor fusion is also known as (multi-sensor) data fusion and is a subset of information fusion.
In the geospatial (GIS) domain, data fusion is often synonymous with data integration. In these applications, there is often a need to combine diverse data sets into a unified (fused) data set which includes all of the data points and time steps from the input data sets. The fused data set is different from a simple combined superset in that the points in the fused data set contain attributes and metadata which might not have been included for these points in the original data set.