Here an hypotetical tabular data file:

POSX	POSY	height	type
1722813.000	5102614.000	4.0	Lanterne
1722818.000	5102572.000	3.5	Lanterne
1722825.276	5102541.078	3.5	Sfere
1722838.000	5102546.000	3.5	Sfere
1722851.848	5102550.524	3.5	Sfere
1722814.747	5102522.739	4.0	Sfere
1722809.241	5102501.789	4.0	Sfere

We need to convert it to KML in order to visualize the data in Google Earth. Google Earth makes use of the WGS84 coordinate system, so we are going to use the excellent OGR/GDAL command line software both for the coordinate conversion process (Gauss-Boaga –> WGS84) and the data format conversion (CSV –> KML).

It is a multi step process:

• Write the supporting files
• Create a CSV out of the spreadsheet
• Create the data access VRT file
• Create the  Gauss-Boaga rototranslation file
• Converting the files
• from CSV to SHP (still Gauss-Boaga)
• from  SHP Gauss-Boaga to SHP WGS84
• from SHP (WGS84) to KML

Let’s start: we need to prepare some support files to help us convert the data. First of all we need to export the data from the spreadsheet software to a Comma Separated Values (CSV) file. Which will look like this:

POSX,POSY,height,type
1722813.000,5102614.000,4.0,Lanterne
1722818.000,5102572.000,3.5,Lanterne
1722825.276,5102541.078,3.5,Sfere
1722838.000,5102546.000,3.5,Sfere
1722851.848,5102550.524,3.5,Sfere
1722814.747,5102522.739,4.0,Sfere
1722809.241,5102501.789,4.0,Sfere

OGR supports a virtual format which allows specification via an XML file. If you convert your worksheet into a CSV, you can generate a VRT file to instruct GDAL on how to access the data. I’ve created my VRT file like the following, and saved it on the disk as example.vrt:

<OGRVRTDataSource>
    <OGRVRTLayer name="example">
        <SrcDataSource>/home/simone/Desktop/test_data/example.csv</SrcDataSource>
        <GeometryType>wkbPoint</GeometryType>
        <LayerSRS>WGS84</LayerSRS>
        <GeometryField encoding="PointFromColumns" x="POSX" y="POSY"/>
    </OGRVRTLayer>
</OGRVRTDataSource>

This line in example.vrtis the important one:

<GeometryField encoding="PointFromColumns" x="POSX" y="POSY"/>

it tells GDAL which culumn is what. Which column is the east-west and north-south coordinate. We are now ready to generate a SHP, still in Gauss-Boaga coordinates.

ogr2ogr -f "ESRI Shapefile" example.shp example.vrt

Now we can convert example.shp to WGS84, using this PROJ file (gauss-boaga.prj):

PROJCS["Monte Mario / Italy zone 1",
GEOGCS["Monte Mario",DATUM["Monte_Mario",
SPHEROID["International 1924",6378388,297,AUTHORITY["EPSG","7022"]],
TOWGS84[-104.1,-49.1,-9.9,0.971,-2.917,0.714,-11.68],
AUTHORITY["EPSG","6265"]],
PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],
UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],
AUTHORITY["EPSG","4265"]],
UNIT["metre",1,AUTHORITY["EPSG","9001"]],
PROJECTION["Transverse_Mercator"],
PARAMETER["latitude_of_origin",0],
PARAMETER["central_meridian",9],
PARAMETER["scale_factor",0.9996],
PARAMETER["false_easting",1500000],
PARAMETER["false_northing",0],
AUTHORITY["EPSG","3003"],
AXIS["X",EAST],AXIS["Y",NORTH]
]

and by executing the following code:

ogr2ogr -s_srs gauss-boaga.prj -t_srs EPSG:4326 example_wgs84.shp example.shp

We are ready for the final step: convert the SHP file to KML:

ogr2ogr -f "KML" wgs84_GE.kml wgs84_example.shp

wgs84_GE.kml is our final output file.

                          

Please be aware that I post on this blog only seldom. My main channel of posting updates, lately, has been twitter.

                          

Recently, on 10. January, an illegal horse racing, in a sort of clandestine racetrack was blocked by the military police in Pachino, Syracuse (Sicily, Italy). The blitz has, so far, allowed to identify more than 20 horse owners, jockeys and 3 veterinarians. The land placed in the open countryside, less than 2km from the sea, where the race was stopped, was a clandestine race-course, complete with boxes for the horses.

Just after discovering the news, I went hunting for that track on aerial images. We have been lucky enough to have been granted access to some 25cm resolution images, these images were made by the Regione Sicilia, after some more research I ended up discovering that the racetrack is located in Contrada Granelli, and not nearby the inhabited part of the Pachino town, so in the end, I was able to find it on the map, and tag it accordingly.

<way id=”49641876″>
<tag k=”clandestine” v=”yes”/>
<tag k=”leisure” v=”track”/>
<tag k=”name” v=”Granelli”/>
<tag k=”sport” v=”horse_racing”/>
</way>

Here is the result:

horse

Show embedded map in full-screen mode

Surely this is not as important as what my friend Mikel is doing in Kibera, but still a declaration of indipendence from the canonical mapmakers.

                          

These are the total number of users in the Haiti planet extract as of today (the 29th), and dating back to the 14th. For comparison purpose I’ve added the data for 30th dec 2009. It can clearly be seen that the biggest spike was on 16th, reason being on the 15th the first high quality images were made available for retracing. Then, same thing, same reason, on the 22nd.

first column: date of the extract
second: unique users contributing to the Haiti map
third: Megabytes of the uncompressed extract file (useful for gathering a rough idea of “detail”)

                          

http://www.ibm.com/developerworks/opensource/library/j-spatial/index.html

                          

To my non-artistic eyes this smart artist creates folding cubes that you need to donwload –> print –> cut –> fold with no need for glue. An amazing piece of art.

                          

http://dontrepreneur.com/2009/12/14/how-to-create-a-great-startup-office-space-while-being-abusrdly-cheap/

First let me tell you I furnished my entire office for about $4,500 complete with four workspaces, including chairs, desk lamps, wastebins and office supplies. A lounge area complete with futon couch, area rug and end table. Lamps, rugs and some strategically placed whiteboards. Throw in a microwave, printer, a wireless router, TV stand, 32 inch HD television and Xbox 360 entertainment system. Finally, I almost forgot a refrigerator, storage ottomans, extra chairs, three bookcases and some very nice standing lamps. All for $4,500—purchased and set up in 7 days.