A Data Fusion Technique for Mosaicking of Different Sources Digital Elevation Models

Mario Costantini(1) , Fabio Malvarosa(1) , Federico Minati(1) , and Frank Martin Seifert(2)

(1) Telespazio S.p.A., Via Tiburtina, 965, 00156 Roma, Italy
(2) ESA ESRIN, Via G. Galilei, 00044 Frascati, Italy


Digital elevation models (DEMs) can be obtained by using different techniques, either based on measurements on situ, or remote sensed data (e.g. levelling, fotogrammetry, SAR interferometry, radargrammetry, laser scanning, etc.). Different DEMs are usually not homogeneous and affected by different systematic vertical and horizontal errors, in addition to random noise. Standard mosaicking procedures try to reduce only the inconsistencies in overlapping areas and provide results where discontinuities are no more clearly visible, but do not remove the systematic errors that caused the artifacts.

In this work we propose a method that exploits the information contained in the area of overlap between different DEMs in order to reduce horizontal and vertical systematic errors. Then, only after systematic error has been removed as far as possible, more standard mosaicking methods are used to reduce random noise and fill areas where data are missing. The same fusion approach is suitable for mosaicking of other kinds of images in addition to DEMs.

The proposed technique allows obtaining accurate and homogeneous DEMs, as demonstrated in the framework of the DUDES project funded by ESA. The DEM obtained from the fusion of ERS and SRTM interferometric DEMs has been validated by comparison with high resolution DEMs. The obtained DEM largely fulfill DTED2 specifications. Moreover, the accuracy of the obtained DEM is better of each of the single SRTM and ERS DEMs used as input for the fusion.


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