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TRIANGULATE/TRIGRID problem in IDL 5.3 (SGI)



Dear IDL community,

I'm hoping someone can provide me with some inspiration on a problem
which has bugged me for a while now.

I have 1354 x 10 float arrays of latitude, longitude, and image data
from a satellite. I create a map projection, and convert the lat/lon
coordinates to irregularly spaced device coordinates (x, y) in the
graphics window. I then use TRIANGULATE and TRIGRID to create regularly
spaced interpolated grids of the column and row coordinates in the
original image array. If these interpolated column and row arrays are
computed correctly, they can be used with INTERPOLATE to compute an
image which is interpolated to the pixels in the graphics window. This
method (in theory) should be better than the subjective technique used
by my IMAGEMAP procedure.

However the interpolated column and row arrays have bogus values along
the top and bottom edges of the satellite swath (the edges are curves in
the example). For example, along the bottom edge of the interpolated
swath there are cyan pixels where the pixels should be darker blue. This
causes the bilinear interpolated image (not shown here) to have very
noticeable artifacts.

I have tried every combination of TRIANGULATE and TRIGRID keywords I can
think of, to no avail. Spherical gridding does not seem to be the answer
because it requires the output grid to be regularly spaced in latitude
and longitude (my output grid must be evenly spaced in x/y device
coordinates).

I have attached my minimal example program below, and the data file
mentioned can be obtained from

ftp://origin.ssec.wisc.edu/pub/gumley/tmp/latlon.xdr

To run the program:

.compile latlon
window, /free, xsize=1100, ysize=850
device, decomposed=0
latlon

An annotated output image is available at

ftp://origin.ssec.wisc.edu/pub/gumley/tmp/latlon.jpg

If anyone has suggestions, I'd be glad to hear them.

Cheers,
Liam.
http://cimss.ssec.wisc.edu/~gumley/

;---
PRO LATLON

;- Read lat and lon arrays
restore, 'latlon.xdr'
help, lat, lon
dims = size(lat, /dimensions)
ncol = dims[0]
nrow = dims[1]

;- Create map projection
map_set, 30, -112.5, scale=5e6, /noborder

;- Create input row/column coordinate arrays
col = rebin(findgen(ncol), ncol, nrow, /sample)
row = rebin(reform(findgen(nrow), 1, nrow), ncol, nrow, /sample)

;- Convert the lat/lon data to device coordinates
result = convert_coord(lon, lat, /data, /to_device)
x = reform(result[0, *], ncol, nrow)
y = reform(result[1, *], ncol, nrow)

;- Get edges of image in device coordinates
loc = where(x ge 0.0 and x le (!d.x_vsize - 1.0) and $
            y ge 0.0 and y le (!d.y_vsize - 1.0))
xmin = floor(min(x[loc]))
ymin = floor(min(y[loc]))
xmax = ceil(max(x[loc]))
ymax = ceil(max(y[loc]))

;- Interpolate
triangulate, lon[loc], lat[loc], tri
intcol = trigrid(x[loc], y[loc], col[loc], tri, $
  [1.0, 1.0], float([xmin, ymin, xmax, ymax]))

;- Display the interpolated column array
loadct, 13
index = where(intcol gt 0)
min_value = min(intcol[index])
tv, bytscl(intcol, min=min_value, top=(!d.table_size - 1)), $
  xmin, ymin

END
;---