I want to fit a polynomial function (max. 3rd order) on each raster cell over all my spectral bands (Landsat 1-7) creating a new raster(stack) representing the coefficients. I got my data (including NA values) in a stack with 6 Layer (Landsat Band 1-7[excluding 6]).

I guess somehow I should tell the polynomial function on which spectral wavelength the bands are located

- Landsat7 Wavelength (micrometers)

- Band 1 0.45-0.52
- Band 2 0.52-0.60
- Band 3 0.63-0.69
- Band 4 0.77-0.90
- Band 5 1.55-1.75
- Band 7 2.09-2.35

so that it can fit it properly. Has anyone an idea how to do that polynomial fitting of each cell and extracting the coefficients in R? Thanks for any help!

Answer:

Your question is not very clear, as you do not specify what you are fitting. I am guessing it is band number. You can do something like this.

```
library(raster)
b <- brick(system.file("external/rlogo.grd", package="raster"))
b[[2]][125:225] <- NA
s <- stack(b, flip(b, 'y'))
names(s) <- paste0('b', 1:6)
bands <- 1:6
f <- function(x) {
# in case of NAs; match the number of coefficients returned
if (any(is.na(x))) return(c(NA, NA, NA))
m <- lm(x ~ bands + I(bands^2))
coefficients(m)
}
z <- calc(s, f)
z
plot(z)
```

If you need to speed this up you can follow the example here: http://gis.stackexchange.com/questions/144211/want-cell-linear-regression-values-for-a-netcdf-or-multi-band-raster/144408#144408

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