Abstract
The paper presents an optimized method of digital terrain model (DTM) estimation based on modified kriging interpolation. Many methods are used for digital terrain model creation; the most popular methods are: inverse distance weighing, nearest neighbour, moving average, and kriging. The latter is often considered to be one of the best methods for interpolation of non-uniform spatial data, but the good results with respect to model’s accuracy come at the price of very long computational time. In this study, the optimization of the kriging method was performed for the purpose of seabed DTM creation based on millions of measurement points obtained from a multibeam echosounder device (MBES). The purpose of the optimization was to significantly decrease computation time, while maintaining the highest possible accuracy of created model. Several variants of kriging method were analysed (depending on search radius, minimum of required points, fixed number of points, and used smoothing method). The analysis resulted in a proposed optimization of the kriging method, utilizing a new technique of neighbouring points selection throughout the interpolation process (named “growing radius”). Experimental results proved the new kriging method to have significant advantages when applied to DTM estimation.
Highlights
Digital terrain model (DTM) models are commonly used in geographic information system (GIS)
Based on obtained results it can be concluded that the accuracy of the model is lowest when only Based one point is used for interpolation, and for the number of on the research performed so far, several important conclusions can be drawn: points equal to three or higher, the accuracy increases very slowly (‘gate’) or remains constant or even slightly decreases
The paper presents a research on kriging method variants in case of digital terrain model creation using bathymetric data obtained from multibeam echosounder device (MBES)
Summary
Digital terrain model (DTM) models are commonly used in geographic information system (GIS). Utilizing modern measurement devices such as multibeam echosounder devices (MBESs), we have possibility to gather a huge amount of measurement data which densely cover the surface being measured Each of such measurements contains information about the spatial location (x,y) and the depth at a given point. In another study [9], the authors present possibilities of geostatistical interpolation kriging method used in the process of generating digital terrain models (DTMs). The source of this data were direct measurements realized with a precise. A viable question arises as to whether it is possible to optimize the generic kriging method for the purpose of processing large bathymetric datasets in the process of DTM creation. The goal of the optimization would be to increase computation speed while preserving the high model accuracy
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