Dear Jonathan,

Interesting topic. Please send us also your code example and if possible part 
of your dataset (I assume it is a SpatialGridDataFrame?).

Operations on lists can be speed up by using lapply and by implementing your 
own functions, consider also running Rprof to check which operation is using 
the most time (read more in "R inferno" or e.g. here: 
http://manuals.bioinformatics.ucr.edu/home/programming-in-r#Progr_noloops), 
eventually if the operation is so complex, you simply cannot anticipate to have 
the results within few minutes (except if you try using super or grid 
computing; see 
http://cran.r-project.org/web/views/HighPerformanceComputing.html).

HTH,

T. Hengl
http://home.medewerker.uva.nl/t.hengl/ 


> -----Original Message-----
> From: r-sig-geo-boun...@stat.math.ethz.ch [mailto:r-sig-geo-
> boun...@stat.math.ethz.ch] On Behalf Of Jonathan Thayn
> Sent: Friday, January 29, 2010 5:02 PM
> To: r-sig-geo@stat.math.ethz.ch
> Subject: [R-sig-Geo] NDVI time-series filter
> 
> I need to smooth a collection of annual NDVI time-series data for a fairly 
> large
> image. Right now I am using an interruptive method that compares the 
> difference
> between each point and the mean of its two neighbors. This process repeats 
> until
> a threshold is reached. It works well, but it takes a long time. When I 
> process
> the image without smoothing the data it takes about 2 hours – with the 
> smoothing
> it looks like it will take up to 7 days.
> 
> The method needs to elevate troughs in the data but retain the peaks – I 
> assume
> that any troughs are really cloud contamination and that the peaks are 
> accurate
> NDVI values. Does anyone know of such a smoother that isn't so time consuming?
> 
> 
> Jonathan B. Thayn, Ph.D.
> Illinois State University
> Department of Geography - Geology
> 200A Felmley Hall
> Normal, Illinois 61790-4400
> 
> (309) 438-8112
> jth...@ilstu.edu
> my.ilstu.edu/~jthayn
> 
> 
> 
> 
> 
> 
>       [[alternative HTML version deleted]]

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