Vector Fields from Spatial Time Series of Population Abundance
Displacement fields based on 2D cross-covariance
Displacement fields based on 2D cross-covariance using bounding box
Displacement fields for spatiotemporal data when velocity is spatially...
Diplacement fields for spatiotemporal data when velocity varies spatia...
Displacement fields for spatiotemporal data using a bounding box
Diplacement fields using bounding box when velocity varies spatially
Calculate statistics in source or sink regions
Retrieve matrix row and column indices
Efficiently compute Moran's I statistic
Detect Patterns in Vector Fields
Count populated pixels in a raster stack
Creating a raster stack from formatted datasets
Calculate Gradient Statistics in the Rook's Neighbourhood
Define a subset of grid locations with non-overlapping rook neighborho...
Classify Rook's Neighbours Comprising Spread Patterns in Vector Fields
Detect Rotating Patterns in Vector Fields
Compute statistics for subgrids
Cross-covariance in two spatial dimensions
Functions for converting time series of spatial abundance or density data in raster format to vector fields of population movement using the digital image correlation technique. More specifically, the functions in the package compute cross-covariance using discrete fast Fourier transforms for computational efficiency. Vectors in vector fields point in the direction of highest two dimensional cross-covariance. The package has a novel implementation of the digital image correlation algorithm that is designed to detect persistent directional movement when image time series extend beyond a sequence of two raster images.