17.30. Interpolation and contouring

Paolo Cavallini’nin kattığı modül - Faunalia <https://www.faunalia.eu> _

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This chapter shows how to use different backends to calculate different interpolations.

17.30.1. Interpolation

The project shows a gradient in rainfall, from south to north. Let’s use different methods for interpolation, all based on vector points.shp, parameter RAIN:

Uyarı

Set cell size to 500 for all analyses.

  • GRASS ‣ v.surf.rst

  • SAGA ‣ Multilevel B-Spline Interpolation

  • SAGA ‣ Inverse Distance Weighted [Inverse distance to a power; Power: 4; Search radius: Global; Search range: all points]

  • GDAL ‣ Grid (Inverse Distance to a power) [Power:4]

  • GDAL ‣ Grid (Moving average) [Radius1&2: 50000]

Then measure variation among methods and correlate it with distance to points:

  • GRASS ‣ r.series [Unselect Propagate NULLs, Aggregate operation: stddev]

  • GRASS ‣ v.to.rast.value on points.shp

  • GDAL ‣ Proximity

  • GRASS ‣ r.covar to show the correlation matrix; check the significance of the correlation e.g. with http://vassarstats.net/rsig.html.

Thus, areas far from points will have less accurate interpolation.

17.30.2. Eşyükseklik

Various methods to draw contour lines [always step= 10] on the stddev raster:

  • GRASS ‣ r.contour.step

  • GDAL ‣ Contour

  • SAGA ‣ Contour lines from grid [NB: in some older SAGA versions, output shp is not valid, known bug]