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 # Summary
-With increasing number of Synthetic Aperture Radar satellite missions and datasets, the demand for processing tools is also increasing. However, to process Synthetic Aperture Radar data very limited free tools are available ([PolSARpro](https://earth.esa.int/web/polsarpro/home), [SNAP](https://step.esa.int/main/toolboxes/snap/)) with major concentration on pre-processing. In application user point of view there is a neccesity for tools to derive polarimetric descriptors like vegetation indices and decomposition parameters. In addition there are no free tools in a GIS platform, which is very much essential as remote sensing and GIS are highly inter-dependent. So we have developed a plugin which supports data of all the three avaialble polarimetric modes (full, compact and dual).
-```SAR tools``` plugin generates polarimetric descriptors (viz. vegetation indices, polarimetric decomposition parameters) from C3/T3/C2/T2 matrices obtained from PolSARpro The input data needs to be in PolSARpro format (```*.bin``` and ```*.hdr```). 	
-The plug-in is coded in Python and is dependant of the Quantum GIS framework. More specifically, it makes use of following libraries (bundled with Quantum GIS): [numpy](https://numpy.org/), [gdal](https://gdal.org/) and [QGIS](https://qgis.org/en/site/index.html) core library.
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+The demand for processing tools increases with the increasing number of Synthetic Aperture Radar (SAR) satellite missions and datasets. However, to process SAR data, a minimal number of free tools are available ([PolSARpro](https://earth.esa.int/web/polsarpro/home), [SNAP](https://step.esa.int/main/toolboxes/snap/)), which consolidates all necessary pre-processing steps. Bearing this in mind, there is a need to develop specific tools for the remote sensing user community to derive polarimetric descriptors like the vegetation indices and decomposition parameters. Besides, to the best of our knowledge, there are no such free tools available on the GIS platform, which are quite necessary for SAR remote sensing. 
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+Hence we have developed a plugin for ```QGIS``` that supports data for all the three available polarimetric modes (i.e., full-, compact, and dual). The SAR tools plugin generates polarimetric descriptors (viz., vegetation indices, polarimetric decomposition parameters) from the 3x3 (C3/T3) or the 2x2 (C2/T2) covariance (coherency) matrices obtained from the ESA's [PolSARpro](https://earth.esa.int/web/polsarpro/home) software. The input data needs to be in PolSARpro format (```*.bin``` and ```*.hdr```). The plugin is coded in Python and is dependant on the Quantum GIS framework. It uses the following libraries (bundled with Quantum GIS): [numpy](https://numpy.org/), [gdal](https://gdal.org/) and [QGIS](https://qgis.org/en/site/index.html) core library.
 
 # Background
 The polarimetric decomposition techniques which are incorporated in this QGIS based plugin are model-free, i.e. to compute the decomposition power components no prior assumptions on the volume models is considered. The conventional model-based methods utilize a typical hierarchical process to enumerate power components uses various branching conditions, leading to several limitations. In this regard, these decomposition techniques utilizes some roll-invariant target characterization parameters to decompose the total power into even bounce, odd bounce and diffused power components. The powers obtained from the proposed technique are guaranteed to be non-negative, with the total power being conserved.