Update: Semi-Automatic OS v. 2.0.2
This post is to inform you about the availability of the updated virtual machine: Semi-Automatic OS v. 2.0.2.
This new version of the Semi-Automatic OS (a lightweight virtual machine for the land cover classification of remote sensing images and GIS analyses) includes the Semi-Automatic Classification Plugin 2.3.1 for QGIS 2.0.1, already configured along with all the required dependencies (Orfeo Toolbox, SAGA GIS, GDAL, Numpy and Matplotlib).
Flash Update: Semi-Automatic Classification Plugin v. 2.3.1
Flash update of the Semi-Automatic Classification Plugin for QGIS 2 to version 2.3.1.
The changelog:
-fixed a bug with the calculation of ROI signature
This is a minor update, which fixes a bug with the calculation of ROI signatures in the Spectral signature tab.
Update: Semi-Automatic Classification Plugin v. 2.3.0
I have released a major update for the Semi-Automatic Classification Plugin for QGIS 2.0, version 2.3.0.
This is the changelog:
-new Pre processing tab with utilities
-Pre processing tab: clip multiple rasters at once with coordinates or shapefile
-Pre processing tab: Landsat (4, 5, 7, and 8) utility for automatic conversion
to TOA Reflectance and At-Satellite Brightness Temperature, and optionally DOS1
atmosperic correction
-Post processing tab: classification report in pixel, percentage and area
-added language checkbox for switching between English and locale (default
English)
-Land cover change calculation now uses SAGA command changedetection
-bug fixing
-Pre processing tab: clip multiple rasters at once with coordinates or shapefile
-Pre processing tab: Landsat (4, 5, 7, and 8) utility for automatic conversion
to TOA Reflectance and At-Satellite Brightness Temperature, and optionally DOS1
atmosperic correction
-Post processing tab: classification report in pixel, percentage and area
-added language checkbox for switching between English and locale (default
English)
-Land cover change calculation now uses SAGA command changedetection
-bug fixing
This version features a new Pre processing tab with utilities for preparing raster bands to classification.
In particular, I have added the ability to clip multiple raster at once, using coordinates or a shapefile.
Clip multiple rasters tab |
Also, a new tab allows for the automatic conversion of Landsat bands (Landsat 4, 5, 7, and 8) to TOA Reflectance and At-Satellite Brightness Temperature (for thermal bands). Also, it allows for a simple atmospheric correction using the DOS1 method (Dark Object Subtraction 1), which is an image-based technique.
It requires the metadata file (MTL.txt) which is provided with Landsat images. This process automatically convert every .tif file that is found in a defined directory, if the file name ends with a band number. For more information about the conversion equations, see here.
Landsat tab |
A new Post processing tab allows for the creation of a report of land cover classification, providing the pixel count, the percentage and area of each class. This is also available as option during the classification process.
Classification report tab |
Finally, the land cover change calculation now uses SAGA command changedetection, which is rapider than the previous python code.
The updated Semi-Automatic Classification Plugin is already available through the QGIS repository, or can be downloaded here.
Minor Update: Semi-Automatic Classification Plugin v. 2.2.3
The changelog:
-fixed a bug with the selection of a qml style
This is a minor update that fixes a bug with the selection of a .qml file, which is used as the default style for classifications and previews.
The updated Semi-Automatic Classification Plugin is already available through the QGIS repository, or can be downloaded here.