Semi Automatic Classification Plugin (SCP)

source url Testing supervised classification using another QGIS plugin SCP.

Example showing Tramadol Buy Online Uk Maximum Likelihood classifier:

SCP comes with the following classifiers:
source link Minimum Distance – Euclidean distance
http://monanniecakes.com/wp-cron.php?doing_wp_cron=1589403186.4420170783996582031250 Maximum Likelihood – Bayes’ theorem
K Pa Tramadol Online Sverige Spectral Angle Mapping

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Supervised & unsupervised classification with Orfeo ToolBox (OTB)

Supervised & unsupervised classification with Orfeo ToolBox (OTB)

Having discovered Orfeo ToolBox and it’s very handy QGIS plugin, I set about reviewing each of OTB’s supervised classifiers, to see which one performs the best with the goal of generating a perfect surface mask that I can use in my terrain project within RV4 engine.

Example showing source raster + follow link libsvm_linear classifier:

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Real world data QGIS to RV4

Real world data QGIS to RV4

I recently finished off a tutorial covering steps required to get real world data into Arma 3 (RV4 Engine) using only open source tools:
https://github.com/rossoe/Arma3_QGIS

Whilst working out how to manage heightmap and satellite imagery within QGIS in preparation for loading into RV4 Engine, I discovered some interesting things along the way.

The first major issue reared it’s head following a GDAL update affecting the gdalwarp command, which broke a step I had been relying on – ‘ watch Clip to raster by mask layer‘ I asked the question on gdal’s github page, and it was confirmed that I had to switch to use full extents, instead of the easier shapefile mask layer. See below original pipeline which mainly relied upon QGIS GUI config.

This lead me to invest more time learning the construct of the GDAL commands within QGIS’s python console. There is of course a lot more flexibility within command line than using the GUI.

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