Question

I have a file in this format:

ASCII format

The first rows look like this:

ncols 1440
nrows 720
xllcorner -180.0
yllcorner -90
cellsize 0.25
NODATA_value -9999

Basically I have the world with 1440 ’tiles’ in x direction (longitude) and 720 ’tiles’ in y direction (latitude). Each ’tile’ is a square with a length of 0.25 degrees. I think I have xllcorner and yllcorner correct. I can draw this map like this in R:

library("adehabitat")
bio1 <- import.asc("D:/ENFA/data.asc")
maps <- as.kasc(list(data = bio1))
image(maps, col = cm.colors(256), clfac = list(Aspect = cl))

The map looks fine.

I would like to perform some ecological niche factor analysis (ENFA) using the adehabitat package and am not too sure about the location data. Basically I have them as longitudes and latitudes at the moment but I could also generate then as ’tile index’ (e.g. lower left corner has the latitude -90 and longitude -180 so the ’tile index’ would be 0, 0 – right?). Which is the correct location data format? I would use ENFA code like this:

locs <- read.table("D:/ENFA/Locs.txt", header = TRUE, sep="\t")
dataenfa1 <- data2enfa(maps, locs)
pc <- dudi.pca(dataenfa1$tab, scannf = FALSE)
enfa1 <- enfa(pc, dataenfa1$pr,scannf = FALSE)
hist(enfa1)

I would appreciate any comments please. Thanks in advance.

Answer 1

The problem with leaving your coordinates in lat-long form is that, at most places on earth, a degree of longitude has a different length than a degree of latitude. This might distort your ENFA by exaggerating distances in some directions relative to those in others.

Especially if your data are from a relatively small area, I’d suggest re-expressing the coordinates in meters along an W/E x-axis and S/N y-axis. If all of your points fall inside a single UTM zone, then you could do the conversion within R, using project() in the rgdal package:

Here’s one example, taken from here:

library(rgdal)

# Make a two-column matrix, col1 = long, col2 = lat
xy <- cbind(c(118, 119), c(10, 50))
# Convert it to UTM coordinates (in units of meters)
project(xy, "+proj=utm +zone=51 ellps=WGS84")
          [,1]    [,2]
[1,] -48636.65 1109577
[2,] 213372.05 5546301 

Much more info about how to manipulate spatial data is available in the “Applied Spatial Data Analysis with R” by Bivand, Pebesma, and Gomez-Rubio. If you need more specific assistance, try the R-sig-Geo mailing list.

Hope this helps.