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Transformation - InterpolationSpatial sum

Description and usage

This transformation function is used to calculate the sum of an input time series (grid or scalar) within the area of a polygon of the output time series.

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When the input is a scalar time series the sum 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 sum of the input values of these points. 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 sum value of these cells will be calculated. If the input polygon is only partly within the output polygon the input value will only be accounted for the part which covers the output polygon.

The output time series can be a output time series with polygons or a irregular/regular grid. However it is expected to have a slow performance with large grids because this transformation is optimized for output time series based on polygons.

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Optional element defining the maximum value of the input time series. If the output value is higher than the configured maximum value the output value will be equal to the configured maximum value. 

Example

<interpolationSpatial>

	<sum>

		<inputVariable>

			<variableId>input</variableId>

		</inputVariable>
		<minimumValue>0</minimumValue>
		<maximumValue>10000</maximumValue>
		<outputVariable>

			<variableId>ouput</variableId>

		</outputVariable>

	</sum>

</interpolationSpatial>

Common issues

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