[GRASS-user] subsampling to a coarser resolution

[jamesmcc]

Thanks Glynn,

I didnt realize that bilinear was what I was doing, though I'm familiar with
it. This should work, though I immediately become concerned by the first
line of the documentation

r.resamp.interp - Resamples raster map layers to a finer grid using
interpolation. 

since I'm not going to a finer resolution. I noticed that you are the
author, so I thought I should say something! :)

One point of clarification in the equations you wrote, are the xy coords in
the input raster and in the current region are normalized by the resolution
of the input raster? 

Lastly, r.what looks nice but I have to kinda scratch my head. While I
appreciate being able to query the raster value at a specific geographic
location, I use GIS so that IT will keep track of the positions. I want to
get the values based on row,column of the raster not north,east... clearly,
if i could figure out how to get north,east from row,column I'd just pipe
this to r.what, but I havent figured that out either. 

Since I still cant check, I havent tried to implement any of this yet... 

thanks for you help!




Glynn Clements wrote:
> 
> 
> jamesmcc wrote:
> 
>> Greetings. I'm new to GRASS and after reading the help over and searching
>> this forum I've decided to post. 
>> 
>> I have a raster at 30m resolution in which is nested another raster at
>> 1.5m
>> resolution. I want to average the 4 points in the center of the higher
>> res
>> raster (in [row,col] enumerating from 1: [10,10], [10,11], [11,10] and
>> [11,11]) and assign this to the nesting cell of the lower res raster. Of
>> course I want to do this over all cells in the raster, which is say
>> 10x10. 
> 
> You can do this with:
> 
> 	r.resamp.interp method=bilinear
> 
> For each cell in the current region, it takes the cell's centre
> coordinates and samples the surface defined by the input map at that
> point. For method=bilinear, the sample for a given x,y coordinate is
> calculated as:
> 
> 	x0 = floor(x)
> 	x1 = x0 + 1
> 	u = x - x0
> 
> 	y0 = floor(y)
> 	y1 = y0 + 1
> 	v = y - y0
> 
> 	c00 = input[y0][x0]
> 	c01 = input[y0][x1]
> 	c10 = input[y1][x0]
> 	c11 = input[y1][x1]
> 
> 	c0 = c00 * (1-u) + c01 * u
> 	c1 = c10 * (1-u) + c11 * u
> 
> 	c = c0 * (1-v) + c1 * v
> 
> The input map is read at its native resolution.
> 
> method=bicubic is similar, but uses a 4x4 window and bicubic
> interpolation.
> 
>> Seems easy, but 
>> 1. I'm not confident in any of the resample routines going from their
>> descriptions (probably overlooking something. One problem is that
>> r.neighbors and r.mfilter arent clear about going between regions and
>> require odd neighborhoods both of which discourage me from trying them.
>> I've
>> also done an average resampling to 3m res, but how do i discard all the
>> unwanted cells and get to 30m res?)
> 
> r.neighbors and r.mfilter generate an output map with the same
> resolution as the input. You could subsequently use
> 
> 	r.resamp.interp method=nearest
> 
> to downsample the data, but this is inefficient as you'll be
> calculating many values which will subsequently be discarded.
> 
> The various r.resamp.* modules perform downsampling, i.e. they read
> the input map at its native resolution and generate output at the
> current region resolution, and only calculate the cell values which
> appear in the output map.
> 
>> 2. How in the world would I check this? Can I print out the cells in the
>> input raster and check those against the corresponding cells in the
>> output
>> raster. 
> 
> r.what can be used to obtain individual cell values, while r.out.ascii
> will output a raster map as ASCII data. Both of these read their input
> at the current region resolution, so you should first use
> 
> 	g.region rast=...
> 
> if you want the raw map data without any resampling.
> 
> -- 
> Glynn Clements <glynn at gclements.plus.com>
> _______________________________________________
> grass-user mailing list
> grass-user at lists.osgeo.org
> http://lists.osgeo.org/mailman/listinfo/grass-user
> 
> 

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