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Creating OpenAerialMap Imagery

Archive imagery has some special properties that are different from the way most imagery is currently stored. This document describes how archive imagery can be made.

Using GDAL

The basic steps are:
  1. If your image has non-data areas, and was converted from a lossy format like SID, first convert the edges to black.
  2. Use gdalwarp to embed the mask into the image as an alpha band, and reproject the image to EPSG:4326
  3. Use gdal_translate to convert the warped, alpha image to a 3-band mask image with a YCbCr JPEG mask at 80% quality.

(Note: Internal masks, a key component of OAM imagery, require GDAL 1.8+.)

You can use the following:

nearblack  -co TILED=YES -setmask -nb 0 -of GTiff -o ./prewarp.tif ./your_image.tif
gdalwarp -co TILED=YES -dstalpha  -t_srs EPSG:4326 prewarp.tif warped.tif
gdal_translate -co TILED=YES -co JPEG_QUALITY=80 -co COMPRESS=JPEG -co PHOTOMETRIC=YCBCR  -b 1 -b 2 -b 3 -mask 4 warped.tif final.tif
gdaladdo final.tif 2 4 8 16 32 64 128 256

If you need to use this imagery in a tool that is not GDAL, and does not correctly support TIFF mask bands, you can convert it back to a normal 4-band image with alpha using:

gdal_translate -b 1 -b 2 -b 3 -b mask final.tif myimage.tif

This will flatten the mask back into a ‘normal’ alpha band.

Using EC2

There is now an EC2 AMI available which has the tools installed to do simple image processing. Simply deploy ami-07db196e, and you will have a server which has a single script in it: “”. With this in place, you can do a conversion on any file as easily as:

./ 2011-3-11-oregon-portland-eastburnside-65th.tif

The end result of this will be a new file:

-rw-r--r-- 1 ubuntu ubuntu 413M 2011-08-24 07:09 2011-3-11-oregon-portland-eastburnside-65th.tif
-rw-r--r-- 1 ubuntu ubuntu  13M 2011-09-16 21:40 2011-3-11-oregon-portland-eastburnside-65th.tif_converted.tif

This runs by default on an EC2 small instance. This instance costs ~8 cents per CPU hour in the US/East region. Incoming bandwidth is not charged for in this region, so the large image download to pull an image in will be free; you will only pay for the imagery you transfer out, at 12cents/GB (first gigabyte is free).

A simple tutorial on getting started with EC2 is available on many websites; I was able to use the instructions in a blog post by Paul Stamatiou:

Image Format Support

GDAL supports a wide variety of formats, including both open and proprietary formats. Many aerial imagery providers use a proprietary format called MrSID to make their imagery available; this format can be added to GDAL on a number of platforms, but is generally not available by default on open platforms.

To install MrSID, you can refer to:

Once you have MrSID support, you should also be able to read large JPEG2000 images without problems; the open source (Jasper) JPEG2000 implementation is somewhat lacking in dealing with large images.

MrSID and JPEG2000 should provide support for the majority of aerial imagery data.

Tweaking nearblack parameters

Nearblack has 3 parameters to tweak to ensure proper setup.

  1. -near: This parameter determines how far from black a pixel can be and be considered close enough to mark as transparent. For non-lossy imagery, this should be set explicitly to 0. For lossy imagery – that is, imagery which has been converted from a JPG or MrSID – this can sometimes leave images with ‘ragged’ edges. For lossy imagery, it is generally best to use the default for this value, which is 15. If your image was very heavily compressed, it is possible you may have to bump this number slightly higher – but this has the possibility of marking edge areas as transparent if they are close to white or black, so use with caution.
  2. -nb: This determines how many pixels can be ‘non-black’ on edges but still be removed. If you have leftover pixels from compression when using -near 15, setting this to 1 or 2 may help remove them.
  3. -white: If the image you are converting uses white, instead of black, as a nodata color, then you can add the -white parameter, to use nearblack to mark white areas on edges as transparent.

The best way to check your nearblack parameters is to open a single resulting TIFF after the gdalwarp step in an image viewer that supports alpha bands in TIFFs (most of them); you will then be able to examine your edges and look for missed pixels.