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Tutorial: building and testing the Tabula Peutingeriana sample

RasterLite2 has the capability to even store big images completely lacking any kind of georeferencing.
In this very peculiar case a special Reference System will be applied, identified by SRID=-1 and simply corresponding to a generic, absolutely unqualified Cartesian planar space and just supporting pixels as the internal measure unit.
Corollary: every non-georeferenced big image will be considered in a Reference System of its own; the origin coordinates 0,0 will always be placed on the lower left corner of the image. Consequently any attempt to overlap or join two different images into the same SRID=-1 Reference System will be completely meaningless and will certainly produce odd and unpredictable results.

The Tabula Peutingeriana is a very interesting historical map, and is universally reputed to be a very accurate and faithful copy of some unknown original map probably dating back to the times of Emperor Augustus. It's not based on a topographical representation of the usual modern type, it's much more a topological representation; anyway it represents in full detail the road network connecting the ancient Roman Empire.
Georeferencing such a map is obviously impossible: anyway it could be easily loaded as an hi-quality, hi-resolution digital big image stored within a RasterLite2 DB-file.

Step 1) downloading the input datasource

You can easily download an accurate hi-resolution digital copy of the Tabula Peutingeriana; it's licensed on the Public Domain (CC-0) and it's absolutely free.

Step 2) creating the Peutingeriana Coverage

$ rl2tool CREATE -db peutingeriana.sqlite -cov peutingeriana -smp UINT8 \
-pxl RGB -cpr JPEG -srid -1 -res 1.0

rl2_tool: request is CREATE
===========================================================
              DB path: peutingeriana.sqlite
             Coverage: peutingeriana
          Sample Type: UINT8
           Pixel Type: RGB
      Number of Bands: 3
          Compression: JPEG (lossy)
  Compression Quality: 80
   Tile size (pixels): 512 x 512
    Not Georeferenced:
Pixel base resolution: X=1.0 Y=1.0
===========================================================

     SQLite version: 3.8.4.2
 SpatiaLite version: 4.2.0-devel
RasterLite2 version: 0.8

Raster Coverage "peutingeriana" successfully created

Operation CREATE successfully completed
$
You'll now invoke rl2tool CREATE exactly in the same way you've already tested in any previous tutorial; the relevant differences are in that:

Step 3) populating the Peutingeriana Coverage

$ rl2tool IMPORT -db peutingeriana.sqlite -cov peutingeriana \
-srid -1 -src Tabula_Peutingeriana_-_Miller.jpg -pyr

rl2_tool; request is IMPORT
===========================================================
              DB path: peutingeriana.sqlite
    Input Source path: Tabula_Peutingeriana_-_Miller.jpg
             Coverage: peutingeriana
              Section: from file name
Immediately building Pyramid Levels
===========================================================

     SQLite version: 3.8.4.2
 SpatiaLite version: 4.2.0-devel
RasterLite2 version: 0.8

Importing: Tabula_Peutingeriana_-_Miller.jpg
------------------
    Image Size (pixels): 46380 x 2953
                   SRID: -1
       LowerLeft Corner: X=0.00 Y=0.00
      UpperRight Corner: X=46379.00 Y=2952.00
       Pixel resolution: X=1.0 Y=1.0
  ----------
    Pyramid levels successfully built for: Tabula_Peutingeriana_-_Miller

Operation IMPORT successfully completed
$
Once again, you'll invoke rl2tool IMPORT in the most usual way; you are simply required to specify yet another time -srid -1 so to explicitly confirm that this one is a peculiar non-georeferenced big image.

Step 4) testing the Peutingeriana sample

As you've already done in any previous tutorial you can now directly test the Peutingeriana Coverage by publishing a standard WMS service.
You simply have to start the wmslite light-weight server, then connecting some WMS viewer (e.g. LibreWMS) to the service being published on localhost aka IP address 127.0.0.1, port 8080.

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