approxExtrapDemand: Extrapolate land use area in time In lulcc: Land Use Change Modelling in R

Description

Extrapolate land use area from two or more observed land use maps to provide a valid (although not necessarily realistic) demand scenario.

Usage

 `1` ```approxExtrapDemand(obs, tout, ...) ```

Arguments

 `obs` an ObsLulcRasterStack object containing at least two maps `tout` numeric vector specifying the timesteps where interpolation is to take place. Comparable to the `xout` argument of `Hmisc::approxExtrap` `...` additional arguments to `Hmisc::approxExtrap`

Details

Many allocation routines, including the two included with `lulcc`, require non-spatial estimates of land use demand for every timestep in the study period. Some routines are coupled to complex economic models that predict future or past land use demand based on economic considerations; however, linear extrapolation of trends remains a useful technique.

Value

A matrix.

`Hmisc::approxExtrap`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24``` ```## Plum Island Ecosystems ## load observed land use maps obs <- ObsLulcRasterStack(x=pie, pattern="lu", categories=c(1,2,3), labels=c("forest","built","other"), t=c(0,6,14)) ## obtain demand scenario by interpolating between observed maps dmd <- approxExtrapDemand(obs=obs, tout=c(0:14)) ## plot matplot(dmd, type="l", ylab="Demand (no. of cells)", xlab="Time point", lty=1, col=c("Green","Red","Blue")) legend("topleft", legend=obs@labels, col=c("Green","Red","Blue"), lty=1) ## linear extrapolation is also possible dmd <- approxExtrapDemand(obs=obs, tout=c(0:50)) ## plot matplot(dmd, type="l", ylab="Demand (no. of cells)", xlab="Time point", lty=1, col=c("Green","Red","Blue")) legend("topleft", legend=obs@labels, col=c("Green","Red","Blue"), lty=1) ```