spFastMarch: Runs the spatial version of the Modified Fast Marching Method
In fastmaRching: Fast Marching Method for Modelling Evolving Boundaries

Description Usage Arguments References Examples

View source: R/FMM.R

This function runs the Modified Fast Marching Method of Silva and Steele (2012,2014) from sp and raster objects and outputs results in the same formats, makin it more convenient for (geo)spatial analyses and simulation.

1	spFastMarch(domain, seeds, spatial.res)

`domain`	A `raster` object of chosen dimension and resolution with diffusivity values for every cell. Values above 1 will boost diffusivity, below 1 will inhibit it. Values of 0 should mark cells that block diffusion.
`seeds`	A `SpatialPointsDataFrame` object containing the incept time and rate-of-spread for each of the n seeds in its data.frame, in columns named exactly incept (for incept time) and speed ( for rate-of-spread). This object will be automatically transformed to the projection of domain.
`spatial.res`	(Optional) Spatial resolution of the raster, necessary only to correct the rate-of-spread unit. Defaults to that of the raster used for domain.

Sethian, J.A. (1996), A fast marching level set method for monotonically advancing fronts, Proc. Natl. Acad. Sci. 93 (4), 1591-1595, doi:

Silva, F. and Steele, J. (2012), Modeling Boundaries Between Converging Fronts in Prehistory, Advances in Complex Systems, 15(1-2), 1150005, doi: 10.1142/S0219525911003293

Silva, F. and Steele, J. (2014), New methods for reconstructing geographical effects on dispersal rates and routes from large-scale radiocarbon databases, Journal of Archaeological Science 52, 609-620, doi: 10.1016/j.jas.2014.04.021

library(raster); library(sp); library(rgdal)
domain <- raster(system.file("external/test.grd", package="raster")) # sample raster
domain <- domain > 0 # flattening elevation data
coords <- cbind(c(179000,181200), c(330000, 333000)) # coordinates for seeds
seed.df <- data.frame(incept=c(0,10), speed=c(.1,.1)) # incept time and speed for each seed
seeds <- SpatialPointsDataFrame(coords, seed.df, proj4string=crs(domain))

fm <- spFastMarch(domain, seeds)
par(mfrow=c(1,3))
plot(fm$process, main='process')
plot(fm$arrival.time, main='arrival time')
plot(fm$cost.distance, main='distance')