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I am publishing 100 Gb of aerial image til on GeoServer using pyramid technique. I have made GeoServer in a production environment according to GeoServer manual "Running in a production environment". I have prepared data using gdal_retile:

gdal_retile.py -s_srs EPSG:27700 -v -r bilinear -levels 4 -ps 500 500 -co 'TILED=YES' -co 'COMPRESS=JPEG' -targetDir OUTPUT *.jpg

Input jpg image details:

Driver: JPEG/JPEG JFIF Files: SS0096.jpg SS0096.jgw Size is 4000, 4000 Coordinate System is `' Origin = (200000.000000000000000,197000.000000000000000) Pixel Size = (0.250000000000000,-0.250000000000000) Metadata:
EXIF_BitsPerSample=8 8 8 EXIF_ColorSpace=65535 EXIF_Compression=1 EXIF_DateTime=2016:09:08 07:20:28 EXIF_Orientation=1
EXIF_PhotometricInterpretation=2 EXIF_PixelXDimension=4000
EXIF_PixelYDimension=4000 EXIF_PlanarConfiguration=1
EXIF_ResolutionUnit=2 EXIF_SamplesPerPixel=3 EXIF_Software=Adobe Photoshop CS2 Windows EXIF_XResolution=(72) EXIF_YResolution=(72) Image Structure Metadata: COMPRESSION=JPEG INTERLEAVE=PIXEL
SOURCE_COLOR_SPACE=YCbCr Corner Coordinates: Upper Left ( 200000.000, 197000.000) Lower Left ( 200000.000, 196000.000) Upper Right ( 201000.000, 197000.000) Lower Right ( 201000.000, 196000.000) Center ( 200500.000, 196500.000) Band 1 Block=4000x1 Type=Byte, ColorInterp=Red Overviews: 2000x2000, 1000x1000, 500x500, 160x160 Image Structure Metadata: COMPRESSION=JPEG Band 2 Block=4000x1 Type=Byte, ColorInterp=Green Overviews: 2000x2000, 1000x1000, 500x500, 160x160 Image Structure Metadata: COMPRESSION=JPEG Band 3 Block=4000x1 Type=Byte, ColorInterp=Blue Overviews: 2000x2000, 1000x1000, 500x500, 160x160 Image Structure Metadata: COMPRESSION=JPEG

Windows Server configuration is Intel Xeon E5, 2.20GHz (2 processor) and 32gb RAM. But when I am accessing this layer using WMTS service, it is taking a lot of time (around 20-30 minutes) to load completely.

Can anyone suggest me how to reduce rendering time?

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    Please clarify what you mean with "load completely". With what client, ar what resolution? Commented Apr 7, 2018 at 12:36
  • load completely in QGIS and ArcGIS at resolution 1:2000000. Commented Apr 7, 2018 at 16:04
  • how did you prepare your data files? Commented Apr 7, 2018 at 19:50
  • I have updated my question. please looks once. Commented Apr 9, 2018 at 10:48
  • For preparing the data, I followed following steps: 1. optimize data with gdal_translate gdal_translate -co "TILED=YES" -co "BLOCKXSIZE=512" -co "BLOCKYSIZE=512" input.tif output.tif 2. added overviews with gdal_addo gdaladdo -r average output.tif 2 4 8 16 32 3. Created the pyramid with GDAL retile gdal_retile.py -s_srs EPSG:27700 -v -r bilinear -levels 4 -ps 500 500 -co "TILED=YES" -co 'COMPRESS=JPEG' -co "BLOCKXSIZE=256" -co "BLOCKySIZE=256" -ot Byte -useDirForEachRow -targetDir Output output.tif Commented May 4, 2018 at 4:06

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The best advice is to follow Paul Ramsey's advice:

So, to sum up, your best format for image serving is:

  • GeoTiff, so you can avoid proprietary image formats and nonsense, with
  • JPEG compression, for visually fine results with much space savings, and YCBCR color, for even smaller size, and
  • internal tiling, for fast access of random squares of data, and
  • overviews, for fast access of zoomed out views of the data.

For gdal_translate he recommends the following options:

gdal_translate \ -co COMPRESS=JPEG \ -co PHOTOMETRIC=YCBCR \ -co TILED=YES \ 5255C.tif 5255C_JPEG_YCBCR.tif

and for overviews:

gdaladdo \ --config COMPRESS_OVERVIEW JPEG \ --config PHOTOMETRIC_OVERVIEW YCBCR \ --config INTERLEAVE_OVERVIEW PIXEL \ -r average \ 5255C_JPEG_YCBCR.tif \ 2 4 8 16
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  • Thanks a lot for your valuable answer. I followed these steps and reprocess the data again. but when I am rendering it using WMTS in QGIS, still it is taking a lot of time. Please, can you let me know what I am doing wrong? and one more question is my server configuration sufficient for publishing 100-300 GB of raster data? Commented Jun 12, 2018 at 4:36

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