How to resample a map using the statistical mode of class to fill the new pixel

Isaque,
If your LandScan raster is at 30m resolution, then best might be to
`aggregate()` to as close as 250m (e.g. using `fact=8` or `fact=9` and
`fun=modal`), and then use `projectRaster()`:

projectRaster(from, to, method="bilinear")

Others might have better ideas.
--Mel.


On 8/26/2016 10:43 PM, Tom Philippi wrote:

Mel's answer is complete if you are aggregating to an integer multiple
of grid cells: if your tree cover was 5, 10, 25, 50, 125, etc., m
pixels.  If you are unlucky enough to have your tree cover in 15 or
30m pixels, you may need to disaggregate to greatest common factor (5
or 10m) cells first, then aggregate up to 250m MODIS.  With mode on
categorical data, that should still give you your expected results;
with continuous raster values and other functions, it might not be
appropriate.

Tom 2


On Fri, Aug 26, 2016 at 7:28 PM, Bacou, Melanie <mel at mbacou.com
<mailto:mel at mbacou.com>> wrote:

     Isaque, check this thread on StackExchange:
     http://gis.stackexchange.com/questions/177423/r-aggregate-raster-with-mode-function-how-does-it-work
     <http://gis.stackexchange.com/questions/177423/r-aggregate-raster-with-mode-function-how-does-it-work>

     --Mel.


     On 8/26/2016 10:07 PM, Isaque Daniel wrote:

     > Hi dear all,
     >
     >
     > I need to resample a tree cover map create by Landsat imagery to

     the MODIS 250 meters.

     >
     > If I use the resample function of raster package, it will

     compute the value based on bilinear or ngb, in this condition the
     new class map will not answer my expectations.

     >
     >
     > I loking for a way of resample using the statistical mode to

     define the value of the pixel of the new map.

     >
     >
     > Some tip about this?
     >
     > Thanks
     > Isaque
     >
     >
     >
     >

     ------------------------------------------------------------------------------------------------------------------

     > Agronomist engineer
     > Master in Remote Sensing - National  Institute for Space

     Research (INPE) - Brazil

     > PHD Student in Transport - Bras?lia University (UNB)
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