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This transformation can handle three types of input:
- scalar (point)
- regular grid
- irregular grid
When the input is a scalar time series the average value for a certain polygon in the output will be calculated by finding the points in the input time series which are within the area of the polygon and calculate the average value of these points. When the input contains polygon geometries, these will be converted to points, either by using X,Y attributes if those are defined, or by calculating the polygon centroid providing a result that is not very accurate as none of the polygons areas are accounted for.
When the input is a time series with a grid (regular or irregular) the transformation will determine which cells of the input time series have an overlap with the output polygon and the average value of these cells will be calculated. The average value will be a weighted average. The weight of each input cell wil be based on how much area of the input cell covers a certain part of the output polygon. This is done by the next algorithm, called "cookie cutter":
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Note: It should not be used to transform one regular grid into another regular grid with higher resolution (smaller cells). Use the bilinear interpolation then. A config warning is raised when you use the average method in such cases.
Input/Output time series
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