I'm trying to provide SRTM1 (1 arcsecond resolution elevation) images and data
using GeoServer, but can't figure out how to serve such a large dataset
efficiently. Here's what I've done so far:
- Downloaded the 1 degree squared HGT files. The Earth is 360*180 = 64800
square degrees, but only 14295 HGT files since the other square degrees
are 100% water. The HGT files are uncompressed and 25,934,402 bytes each.
- I then used commands like:
gdal_translate -co TILED=YES -co COMPRESS=DEFLATE N58W122.hgt N58W122.hgt.tif
to convert these HGT files into TIFFs. The TIFFs vary in size, but are much
smaller.
- I then imported the directory with the TIFFs as a store using
ImageMosaic. This took a while, but appears to have worked, since "srtm1"
(the name I gave it) now appears in my list of stores.
- I then created a layer using this source, but when I use "OpenLayers"
preview, the server hangs for a while and ultimately dies with "too many
open files" (or similar). This seems odd, since my Linux OS had
fs.file-max set to 13063650. I even tried doubling it to 26127300, but
that didn't help.
At this point, I suspect I need to create an image pyramid or something so
GeoServer can handle the data efficiently, but I'm not sure exactly what to
do. I've used 'gdal_retile.py' previously to create pyramids from one large
image into tiles at various zoom levels, but I think I want to do the opposite
here (merge smaller images for lower zoom levels). The gdal_retile.py option
-pyramidsonly seems to say it does that, but I can't get it work (it just
hangs and creates no files)
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