Help: contvert multiband 16 bit tif to 8 band tif

Technically speaking it is OK to predict in future (prepare a stfdfObj
object with spacetime coordinates in future, then run krigeST), but I
would assume that the prediction variance will be large (well this
depends on your variogram / temporal nugget and temporal range of
spatial autocorrelation). Consider for example the prediction models for
weather in the Netherlands:
http://www.knmi.nl/waarschuwingen_en_verwachtingen/ensemble.html
As you get further from the measurement horizon, the confidence limits
become wider and wider.

Also, I do not know how much is krigeST applicable to non-Gaussian data.

PS: Sending more focused questions that refer to some specific line in
the code / or specific topic of broad interest are usually more
efficient on R-sig-geo (see: "Do your homework before posting" in
http://www.r-project.org/posting-guide.html).

T. (Tom) Hengl
Url: http://www.wageningenur.nl/en/Persons/dr.-T-Tom-Hengl.htm
Network: http://profiles.google.com/tom.hengl
Publications: http://scholar.google.com/citations?user=2oYU7S8AAAAJ

On 9-5-2014 12:55, Franklin Tchakounte wrote:
> Hello
>
> i am exercising (would like) to use spatiotemporal kriging to predict
> in the future the rate of populations in neighborhoods in towns. I
> have values for population rate in 2011, 2012, 2013, 2014 for many
> neighbourhoods and i need to know the corresponding values in 2015 and
> 2016 with the spatio temporal kriging using R.
> I would to know (if possible) how to apply extrapolation (spatio
> temporal kriging) with R from the beginning to the end.
>
> i have attached the actual R code with the help of Graeler and data file.
>
> Thank you a lot
>
> Franklin
>
>
>
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