[R-sig-Geo] Raster file from ascii file and flattening Africa ....:)

[Kamran Safi]

Hi Corrado,

Being a advanced newbie myself, I first of all understand what you mean
by that and secondly ask you to qualify my answer.

I would, tackling your problem, create a raster polygon in a metric
equal area projection, such as Mollweide. Then you use overlay() and get
for each polygon the set of points that are within each raster polygon.
You need to import the xyz file in R and convert it into a Spatialpoints
data frame. 

Here's the first bit
This reads a coast line shapefile and extracts africa from it. Then uses
the boundings boxes to produce a grid at the extent of africa. Then it
projects that raster back to longlat for the overlay() procedure. 

map <- readShapePoly("E:/Science/continent.shp", ID="CONTINENT",
proj4string = CRS("+proj=longlat"))
africa <- as.SpatialPolygons.PolygonsList(map at polygons[1])
africa.proj <- spTransform(africa, CRS("+proj=moll"))
grd <- GridTopology(c(bbox(africa.proj)[1,1]+5000,
bbox(africa.proj)[2,1]+50000), c(100000,100000),
c(ceiling((bbox(africa.proj)[1,2] - bbox(africa.proj)[1,1]) /
100000),ceiling((bbox(africa.proj)[1,2] - bbox(africa.proj)[1,1]) /
100000)))

# if you should not have a coastline of africa:
# these are the values you'll need to produce the raster you need to
proceed
# bbox(africa.proj)
#         min     max
# r1 -2472164 6131319
# r2 -4202811 4490010


polys.proj <- as.SpatialPolygons.GridTopology(grd)
proj4string(polys.proj) <- CRS("+proj=moll")
polys <- spTransform(polys.proj, CRS("+proj=longlat"))
# now you have a spatialpolygon in longlat proj that has equal area and
a 
# cell size of 100km2
#prepare a list for you results
results <- rep(NA, length(polys at polygons))
# use something like this to calculate the values per raster grid
# this here is not working probably, as I didn't think about it all too
much
# I have though somewhere a code lying around doing exactly this step,
so if 
# you don't succeed, let me know and I dig that out
for(i in 1:length(polys at polygons))
{
results[i] <- mean(<your spatial
points>$values[which(overlay(as.SpatialPolygons.PolygonsList(map.Proj at po
lygons[i]), <your Spatialpoints>) != NA, ])
}

Apart from the final bits, I tested the start and it worked. The last
bit should not be too difficult to solve. The whole thing could be more
elegant by excluding those polygons that are in the sea. But I think
that is something others can try to get their heads around it. Shouldn't
be too difficult: get the centroid coordinates, overlay it with the
costlines of Africa and convert it back into a grid...

Hope this helped.

Kamran 


------------------------
Kamran Safi

Postdoctoral Research Fellow
Institute of Zoology
Zoological Society of London
Regent's Park
London NW1 4RY

http://www.zoo.cam.ac.uk/ioz/people/safi.htm

http://spatialr.googlepages.com
http://asapi.wetpaint.com

-----Original Message-----
From: r-sig-geo-bounces at stat.math.ethz.ch
[mailto:r-sig-geo-bounces at stat.math.ethz.ch] On Behalf Of Corrado
Sent: 03 December 2008 09:29
To: r-sig-ecology at r-project.org; r-sig-geo at stat.math.ethz.ch
Subject: [R-sig-Geo] Raster file from ascii file and flattening Africa
....:)

Dear friends,

I am a kind of advanced newbie, if that makes sense.

I have a text file of the form

coordinate x,coordinate y,cat={real number between 250 and 450}

where coordinate are expressed in latitude and longitude. The files
represents 
measurements of the size of a skulls on sites all over Africa.

>From it, I would like to build a raster file, 100 km by 100km.  There
are 2 
problems:

1) Unfortunately,  in some 100km x 100km squares, there is one of the
points 
whilst in others there are maybe 20. How do I average, so that in each
square 
I only have 1 value representing the average?
 
2) How do we "flatten" Africa so that we may use 100km x 100km squares
instead 
of 1 degree x 1 degree, without committing a geographical crime? What we
need 
is to respect the areas ....

Best regards and apologies for the silliness of the questions.
-- 
Corrado Topi

Global Climate Change & Biodiversity Indicators
Area 18,Department of Biology
University of York, York, YO10 5YW, UK
Phone: + 44 (0) 1904 328645, E-mail: ct529 at york.ac.uk

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