MASADA stands for Massive Spatial Automatic Data Analytics. It has been developed in the frame of the “Global Human Settlement Layer” (GHSL) project of the European Commission’s Joint Research Centre, with the overall objective to support the production of settlement layers, by automatic classification of high and very high resolution satellite imagery.
The tool builds on the Symbolic Machine Learning (SML) classifier; a supervised classification method of remotely sensed data which allows extracting built-up information using a coarse resolution settlement map or a land cover information for learning the classifier.
The first version of MASADA (v1.3) supports Very High Resolution satellite data and includes pre-defined workflows for a variety of sensors (e.g. SPOT-5, SPOT-6/7, RapidEye, CBERS-4).
The second version of MASADA (v2.0) is tailored to the processing of Copernicus Sentinel-1 and Sentinel-2 data. Two workflows building on the SML but adapted to the characteristics of each of the two sensors have been implemented in a stand-alone software. The tool is designed for the processing of single scenes, for batch processing of a series of scenes and for parallel processing of large datasets thanks to a dedicated command-line interface.
This user guide is a comprehensive guide to all aspects of using the MASADA tool. It includes instructions for the installation of the software, the use of the tool and the manipulation of the data. It presents briefly the basic principles and background information on the two main modules integrated in this new version: S1 module and S2 module. Some guidelines on the parametrization of the modules are also provided together with test datasets.