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Task Geoinformatics Interpolation Methods

plc-dev edited this page Oct 18, 2020 · 2 revisions

Inverse Distance Weighting (IDW) Overview

IDW is an interpolation algorithm, leveraging tobler's first law of geography: "everything is related to everything else, but near things are more related than distant things."
It can be used to deterministically estimate an unknown spatial attribute of an unmeasured point with the help of surrounding measured points.
E.g. the altitude of a not yet measured point.
The distance between the points has to be known, as they are used to calculate the desired spatial attribute.
Major flaws of this method are the inability to account for spatial continuity and the redundancy of data.


Formula:



IDW formula

Video explaining the algorithm:



algorithm explanation

Kriging Overview

The Kriging model is a statistical model, that accounts for redundancy, spatial continuity and location/closeness of given data.

Formulas and theoretical explanation:

Theoretical explanation Intuitive explanation

Example/Interactive Demonstration

Intuitive explanation

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