Release of the new QGIS Semi-Automatic Classification Plugin

[nadiopt]

http://monde-geospatial.com/release-new ... rsion-4-0/
Written by Luca Congedo, the Semi-Automatic Classification Plugin (SCP) is a free open source plugin for QGIS that allows for the semi-automatic classification (also supervised classification) of remote sensing images. Also, it provides several tools for the pre processing of images, the post processing of classifications, and the raster calculation.
SCP allows for the rapid creation of ROIs (training areas), through region growing algorithm, which are stored in a shapefile. The scatter plot or ROIs is available. Spectral signatures of training areas are calculated automatically, and can be displayed in a spectral signature plot along with the values thereof. Spectral distances among signatures (e.g. Jeffries Matusita distance, or spectral angle) can be calculated for assessing spectral separability. Spectral signatures can be exported and imported from external sources. Also, a tool allows for the selection and download of spectral signatures from the USGS Spectral Library .
The following tools are available for the pre processing of images: automatic Landsat conversion to surface reflectance, clipping multiple rasters, and splitting multi-band rasters. The classification algorithms available are: Minimum Distance, Maximum Likelihood, Spectral Angle Mapping. SCP allows for interactive preview of classification.
The post processing tools include: accuracy assessment, land cover change, classification report, classification to vector, reclassification of raster values. Also, a band calc tool allows for the raster calculation using NumPy functions