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Introduction

The package add the following algorithms to 'processing' (was 'sexante'):

  • Band mean: given a tiff with the weekly values (no limit on bands) returns a layer with the mean of specified bands.

  • Monthly mean: given a tiff with the weekly values (52 bands) returns a layer with the mean of specified month in the year.

  • Snow height by slope: given the snow height and a slope layer returns a layer with the snow weighted with the SAF function.

  • Ground surface temperature: given the snow heigth, air temperature, Qs and K will return the ground surface temperature as in the article "PERMACLIM: a model for the distribution of mountain permafrost, based on climatic observations"
    by Mauro Guglielmin, Barbara Aldighieri, Bruno Testa

Install

Permaclim is installed as standard qgis plugin. The algoritms will be available in 'processing'.

  • extract the repository in /.qgis2/python/plugins:

    $ git clone git://github.com/faunalia/permaclim.git <home>/.qgis/python/plugins/

  • install numpy and gdal python libraries.

    • tested with:

      • python-numpy Version: 1:1.6.1-6ubuntu1
      • python-gdal Version: 1.7.3-6ubuntu3

  • enable 'processing' plugin from the qgis interface

  • enable 'permaclim' plugin from the qgis interface

Models

With the plugin are provides two models:

  • "Analysys 1" computes the ground surface temperature based on the snow heigth

  • "Analysys 2" computes the ground surface temperature based on the snow heigth estimated through the slope.

The models must be copied in /.qgis2/processing/models/ directory.

Testing

To run the unit tests:

    $ export PYTHONPATH=<home>/.qgis2/python/plugins:/usr/share/qgis/python/plugins
    $ cd <home>/.qgis2/python/plugins/permaclim
    $ python tests.py

Credits

Developed for ARPA Piemonte (Dipartimento Tematico Geologia e Dissesto) within the project PERMANET.