Calculate summary statistics for all features independently.

  distance = 500,
  projection = "worldalbers",
  retainAreaProportion = FALSE



A SpatialPolygonsDataFrame containing zones from which the summary statistics for the catchment variable will be calculated. Smaller polygons will increase the accuracy of the results.


A SpatialPolygonsDataFrame, SpatialLinesDataFrame or SpatialPointsDataFrame object containing the specifications of the facilities and zones for which the catchment areas are being calculated.


A vector of column names containing the variables in the polygonlayer to be used in the calculation of the summary statistics for the catchment areas.


Defines the size of the catchment areas as the distance around the targetlayer in the units of the projection (default = 500 metres)


The proj4string used to define the projection to be used for calculating the catchment areas or a character string 'austalbers' to use the Australian Albers Equal Area projection. Ignored if the polygonlayer is projected in which case the targetlayer will be converted to the projection used by the polygonlayer. In all cases the resulting object will be reprojected to the original coordinate system and projection of the polygon layer. Default is an Albers Equal Area projection but for more reliable results should use a local projection (e.g., Australian Albers Equal Area project).


Boolean value. If TRUE retains a variable in the resulting SpatialPolygonsDataFrame containing the proportion of the original area within the catchment area (Default = FALSE).


Calculates the summary statistics for a catchment area of multiple facilities or zones using straight-line distance from variables available in a SpatialPolygonsDataFrame with census tracts or other zones. Assumes that the frequency of the variable is evenly distributed throughout the zone. Returns the original source dataframe with additional columns with summary variables.

See also


if (FALSE) { data_dir <- system.file("extdata", package = "stplanr") unzip(file.path(data_dir, "")) unzip(file.path(data_dir, "")) sa1income <- readOGR(".", "smallsa1") testcycleway <- readOGR(".", "testcycleway") calc_moving_catchment( polygonlayer = sa1income, targetlayer = testcycleway, calccols = c("Total"), distance = 800, projection = "austalbers" ) }