Editing vector layers with Quantum GIS

I’ve been looking around for an open source alternative to the excellent Desktop GIS Mapping Application MapInfo Pro. I’ve installed and played with both Quantum GIS (QGIS) and MapWindow. The latter is a little bare bones and does not seem to include any geometry editing, so I’ve been focussing instead on QGIS.

QGIS is a great application, though it is quite noticably slower to render very large mapping layers than MapInfo Pro. However – and this is, strangely, not very well known or documented – QGIS will only let you edit layers which are Shapefiles. There is no documentation that I can find which says why the “Toggle Editing” function is always disabled for other files – this is very confusing/frustrating if you don’t know about this Shapefile limitation.

There is a converter within QGIS (which is really just a UI on ogr2ogr) to convert between TAB and SHP formats, but Shapefile layers are rather limited because you can’t mix geometries within a layer – both nodes (points), and lines, for example. This is rather a problem because the map data I have has both points and lines – the points are needed to style the line endpoints and allow for data attributes on them. Separating points and lines into different layers in this context is a bit of a pain. Shapefiles also have various other limitations – for example, field names can be no longer than 10 characters.

Perhaps hooking up QGIS to an SQLite database with Spatialite extension might make managing the map data layers more streamlined – one for a rainy day…


I recently needed to organise and filter a heap of data from a new client. I didn’t want to deal with the overhead of a full-blown database and decided to try sqlite3. As it turns out, it was really easy to work with since the bindings are included with Python2.6. All I needed to do was read a bit on how to interface Python with sqlite here: and I was good to go! I also installed a nice database management utility called SQLite Database Browser v2.0b 1 which you can get here: It makes managing the structure of the database a bit easier than working in a windows command prompt and you can write SQL on-the-fly if you’re having some problems with your Python. I find that it is pretty stable (though some of my poorly written SQL queries do send it into a tizzy and I need to kill it and reopen).

Now, I’ve decided to create a sqlite database and integrate it with the Excel front-end for one of our solvers (used when clients require desktop deployment). I anticipated that integration with an SQL database would greatly simplify and speed-up the reporting (with the added bonus of a significant reduction in the need for me to write complex vba code). Initially I banged around getting really frustrated with Excel, and DAO (even after I installed the ODBC driver available here: Then I discovered SQLite for Excel here: Whew! So far, I have found it very easy to work with and I am busy completing my reporting tool.