17.29. Outros programas

Módulo foi contribuição de Paolo Cavallini - Faunalia

Nota

Este capítulo mostra como usar programas adicionais de dentro do Processing. Para completá-lo, você deve ter instalado, com as ferramentas de seu sistema operacional, os pacotes relevantes.

17.29.1. GRASS

GRASS is a free and open source GIS software suite for geospatial data management and analysis, image processing, graphics and maps production, spatial modeling, and visualization.

It is installed by default on Windows through the OSGeo4W standalone installer (32 and 64 bit), and it is packaged for all major Linux distributions.

17.29.2. R

R is a free and open source software environment for statistical computing and graphics.

It has to be installed separately, together with a few necessary libraries (LIST). To enable the use of R in QGIS, the Processing R Provider plugin must also be installed.

The beauty of Processing implementation is that you can add your own scripts, simple or complex ones, and they may then be used as any other module, piped into more complex workflows, etc.

Teste algum dos exemplos pré instalados, se você já possui R instalado (lembre-se de ativar os módulos R das configurações gerais de processamento)

17.29.3. Outros

LASTools is a set of mixed, free and proprietary commands to process and analyze LiDAR data. Availability in various operating system varies.

Mais ferramentas estão disponíveis através de plugins adicionais, e.g.:

  • LecoS: a suite for land cover statistics and landscape ecology

  • lwgeom: formerly part of PostGIS, this library brings a few useful tools for geometry cleanup

  • Animove: tools to analyse the home range of animals.

More will come.

17.29.4. Comparison among backends

Buffers and distances

Let’s load points.shp and type buf in the filter of the Toolbox, then double click on:

  • Fixed distance buffer: Distance 10000

  • Variable distance buffer: Distance field SIZE

  • v.buffer.distance: distance 10000

  • v.buffer.column: bufcolumn SIZE

  • Shapes Buffer: fixed value 10000 (dissolve and not), attribute field (with scaling)

See how speed is quite different, and different options are available.

Exercise for the reader: find the differences in geometry output between different methods.

Now, raster buffers and distances:

  • first, load and rasterize the vector rivers.shp with GRASS ► v.to.rast.value; beware: cell size must be set to 100 m, otherwise the computation time will be enormous; resulting map will have 1 and NULLs

  • same, with SAGA ► Shapes to Grid ► COUNT (resulting map: 6 to 60)

  • then, proximity (value= 1 for GRASS, a list of rivers ID for SAGA), r.buffer with parameters 1000,2000,3000, r.grow.distance (the first of the two maps; the second will show the areas pertaining to each river, if done on the SAGA raster).

Dissolver

Dissolve feições baseado em atributos comuns:

  • GRASS ► v.dissolve municipalities.shp on PROVINCIA

  • QGIS ► Dissolve municipalities.shp on PROVINCIA

  • OGR ► Dissolve municipalities.shp on PROVINCIA

  • SAGA ► Polygon Dissolve municipalities.shp on PROVINCIA (NB: Keep inner boundaries must be unselected)

Nota

O último é quebrado no SAGA <=2.10

Exercise for the reader: find the differences (geometry and attributes) between different methods.