Provided by: mapserver-bin_7.2.2-1_amd64 bug


       tile4ms - create a tile index Shape data set for use with MapServer's TILEINDEX feature


       tile4ms [ metafile tilefile [-tile-path-only] | -h]


       tile4ms  creates  a  tile index Shape data set for use with MapServer's TILEINDEX feature.
       The program creates a Shape data set of rectangles from extents of all the Shape data sets
       listed  in  metafile  (one  Shape  data set name per line) and the associated DBF with the
       filename for each shape tile in a column called LOCATION as required by mapserv.

       Note: Similar functionality can be found in the GDAL commandline utilities ogrtindex
       ⟨⟩ (for vectors) and gdaltindex ⟨
       gdaltindex.html⟩ (for rasters).

       tile4ms creates a Shape data set containing the MBR (minimum bounding  rectangle)  of  all
       shapes  in  the  files  provided,  which  can then be used in the LAYER object's TILEINDEX
       parameter of the mapfile.  The new filed created with this command is used by MapServer to
       only load the files associated with that extent (or tile).


              INPUT  file  containing list of shapefile names.  (complete paths 255 chars max, no

              OUTPUT shape file of extent rectangles and names of tiles in tilefile.dbf

              Optional flag. If specified then only the path to the shape files will be stored in
              the LOCATION field instead of storing the full filename.

       -h     Display usage information


       Short Example

       Create tileindex.shp for all tiles under the /path/to/data directory:

              cd /path/to/data
              find . -name "/*.shp" -print > metafile.txt
              tile4ms metafile.txt tileindex

       Long Example

       This  example  uses  TIGER Census data, where the data contains files divided up by county
       (in fact there are over 3200 counties, a very large dataset indeed). In  this  example  we
       will  show  how  to  display all lakes for the state of Minnesota. (note that here we have
       already converted the TIGER data into Shape format, but you could keep the data  in  TIGER
       format  and use the ogrtindex utility instead) The TIGER Census data for Minnesota is made
       up of 87 different counties, each containing its own lakes file ('wp.shp').

       1.  We need to create the 'meta-file' for the tile4ms command. This is a text file of  the
           paths  to  all  'wp.shp'  files for the MN state. To create this file we can use a few
           simple commands:

              find -name *wp.shp -print > wp_list.txt

           The newly created file might look like the following (after removing the full path):


       2.  Execute the tile4ms command with the newly created meta-file to create the index file:

              tile4ms wp_list.txt index
                Processed 87 of 87 files

       3.  A new file named 'index.shp' is created. This is the index file with the MBRs  of  all
           'wp.shp' files for the entire state, as shown in Figure 1. The attribute table of this
           file contains a field named 'LOCATION', that contains the path to each 'wp.shp  file',
           as shown in Figure 2.

           Figure 1: Index file created by tile4ms utility

           Figure 2: Attributes of index file created by tile4ms utility

       4.  The final step is to use this in your mapfile.

           · LAYER object's TILEINDEX - must point to the location of the index file

           · LAYER object's TILEITEM - specify the name of the field in the index file containing
             the paths (default is 'location')

           · do not need to use the LAYER's DATA parameter

           For example:

                NAME 'mn-lakes'
                STATUS ON
                TILEINDEX "index"
                TILEITEM "location"
                TYPE POLYGON
                  NAME "mn-lakes"
                    COLOR 0 0 255

       When you view the layer in a MapServer application, you will  notice  that  when  you  are
       zoomed  into a small area of the state only those lakes layers are loaded, which speeds up
       the application.


       shp2img(1), shptree(1), shptreetst(1), shptreevis(1), sortshp(1)

                                         20 February 2019                              tile4ms(1)