[GRASS-dev] Grass Data Explorer QGIS Plugin

Sören Gebbert soerengebbert at googlemail.com
Wed Oct 7 16:04:34 PDT 2015


Dear all,
just for your information:

I have implemented a simple QGIS Plugin to browse and visualize GRASS
GIS raster, vector and time series data in a fast way. It is not
designed to run any GRASS GIS processing modules or to create, remove
or modify GRASS GIS map layers.

The Plugin is implemented in Python and makes use of PyGRASS and the
GRASS GIS Temporal Framework. The use of the PyGRASS RPC interface
should avoid any G_fatal_error crashes. However, it introduces instead
stalled pipes, hanging processes and forever waiting RPC calls.

It allows IMHO fast visualization of raster map layers directly from a
GRASS GIS database, without conversion or export.

Vector maps are converted into QGIS memory layers, to allow all the
great and fancy QGIS vector layer visualization features.

A specific feature is the analysis of space time raster datasets
(STRDS), which are visualized as a specific layer in QGIS. The
corresponding raster
map layers can be switched directly in the STRDS layer settings. In
addition some basic statistical analysis can be performed on the
selected temporal raster map layer and the whole time series. SQL
WHERE statements can be used to select specific raster layer subsets
in the STRDS layer settings.

The Plugin is available here:
https://bitbucket.org/huhabla/grass-data-explorer/wiki/Home

I will not put it into the official QGIS Plugin repository, since it
is too experimental and will be modified a lot.

Be aware that this plugin only works with a very recent GRASS GIS 7.1
svn version.

To run the plugin, QGIS must be started from within an active GRASS
GIS session. Switching mapsets or locations is not supported.

The plugin is highly experimental and has a lot of bugs. Hence, after
closing QGIS, run "killall -9 qgis" to kill all the RPC processes,
that are spawned to enable parallel data access.

Use it on your own risk!! However, for me it is already very useful. :)

Best regards
Soeren


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