Neighborhood Aggregate
The NeighborhoodAggregate
operator computes an aggregate function for a pixel and its neighborhood.
The operator can be defined as a neighborhood matrix with either weights or predefined shapes and an aggregate function.
An example usage scenario is to calculate a Gaussian filter to smoothen or blur an image. For each time step in the raster time series, the operator computes the aggregate for each pixel and its neighborhood.
The output data type is the same as the input data type. As the matrix and the aggregate in and outputs are defined as floating point values, the internal computation is done as floating point calculations.
Parameters
Parameter  Type  Description  Example Value 

neighborhood  Neighborhood  Pixel neighborhood specification 

aggregateFunction  AggregateFunction  An aggregate function for a set of values 

Types
The following describes the types used in the parameters.
Neighborhood
There are several types of neighborhoods. They define a matrix of weights. The rows and columns of this matrix must be odd.
WeightsMatrix
The weights matrix is defined as an \( n \times m \) matrix of floating point values. It is applied to the pixel and its neighborhood to serve as the input for the aggregate function.
For instance, a vertical derivative filter (a component of a Sobel filter) can be defined like this:
{
"type": "weightsMatrix",
"weights": [
[1.0, 0.0, 1.0],
[2.0, 0.0, 2.0],
[1.0, 0.0, 1.0]
]
}
The aggregate function should be sum
in this case.
Rectangle
The rectangle neighborhood is defined by its shape \( n \times m \).
The result is a weights matrix with all weights set to 1.0
.
{
"type": "rectangle",
"dimensions": [3, 3]
}
AggregateFunction
The aggregate function computes a single value from a set of values. The following aggregate functions are supported:
sum
: The sum of all valuesstandardDeviation
: The standard deviation of all values. This ignoresNO DATA
values.
Inputs
The NeighborhoodAggregate
operator expects exactly one raster input.
Parameter  Type 

source  SingleRasterSource 
Errors
If the neighborhood rows or columns are not positive or odd, an error will be thrown.
Example JSON
{
"type": "NeighborhoodAggregate",
"params": {
"neighborhood": {
"type": "weightsMatrix",
"weights": [
[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0]
]
},
"aggregateFunction": "sum"
},
"sources": {
"raster": {
"type": "GdalSource",
"params": {
"data": {
"type": "internal",
"datasetId": "8d01593c75c04ffa8152eabfe4430817"
}
}
}
}
}