API reference¶
Area Weighted¶
Area weighted approaches use the area of overlap between the source and target geometries to weight the variables being assigned to the target
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Area interpolation for extensive and intensive variables. |
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Construct area allocation and source-target correspondence tables. |
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Construct area allocation and source-target correspondence tables using a spatial indexing approach |
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Construct area allocation and source-target correspondence tables according to a raster ‘populated’ areas |
Dasymetric¶
Dasymetric approaches use auxiliary data in addition to use the area of overlap between the source and target geometries to weight the variables being assigned to the target
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Interpolate data between two polygonal datasets using an auxiliary raster to mask out uninhabited land. |
Model¶
Model based approaches use additional spatial data, such as a land cover raster, to estimate the relationships between population and the auxiliary data. It then uses that model to predict population levels at different scales
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Estimate interpolated values using raster data as input to a generalized linear model. |
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Estimate interpolated values using raster data as input to a generalized linear model, then apply an adjustmnent factor based on pixel values. |
Data¶
Save raster data to the local quilt package storage. |