Estimation of DEM Uncertainty Using Clustering Analysis

Estimation of DEM Uncertainty Using Clustering Analysis
Laercio M. Namikawa

INPE - Instituto Nacional de Pesquisas Espaciais, C.P. 515, S.J.Campos, SP, 12201, Brazil (laercio@dpi.inpe.br)

Abstract: This paper presents a method to estimate the uncertainty in a DEM using Cluster Analysis. The method considers that there are always more than one DEM available for a specific area, therefore, a statistical analysis can be performed and used to create a map with clusters of high and low uncertainty in elevation. The resulting map is particularly important for simulation applications, where the simulation process can apply the uncertainty information to select the best DEM for a region and to define the spatial uncertainty of the simulated result. The method is tested in a region of Sao Paulo State in Brazil, with heterogeneous terrain features. The results show that the method can be used not only in simulation, but also to define geographic regions where data collection can be improved.

Keywords: DEM, Uncertainty, Cluster Analysis, SRTM, ASTER GDEM.

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