It uses an MLP (Multi-Layer Perception) Neural Network Classifier and is based on the Neural Network MLPClassifier by scikit-learn.
The Neural Network MLPClassifier software package is both a QGIS plugin and stand-alone python package that provides a supervised classification method for multi-band passive optical remote sensing data. Neural Network MLP Classifier Supervised classification method for multi-band passive optical remote sensing data, based on the MLP (multi-layer perception) neural network classifier by scikit-learn. It has been developed in an open source environment to encourage further development of the tool. The original Tree Density Calculator was written in C++ and ported to PyQGIS in 2018/2019.
The Tree Density Calculator is a QGIS plugin and command line interface package designed to calculate tree densities based on brightness images, using the local maximum of a sliding window. Tree Density Calculator Calculate the tree density of a given region, by moving a sliding window over a brightness image and detecting local maxima. The original VIPER Tools is now split over two python/QGIS tools: Spectral Library Tools and MESMA. Several updates have been released since and now it has been ported to PyQGIS in the period 2017 - 2020.
The software is based on VIPER Tools: code written for ENVI/IDL and released in 2007. The Spectral Library Tool software package is both a QGIS plugin and stand-alone python package that provides a suite of processing tools for multi- and hyperspectral spectral libraries. Spectral Library Tool Build, visualize and optimize spectral libraries. The original VIPER Tools is now split over two python/QGIS tools: Spectral Library Tool and MESMA. It is based on VIPER Tools: a software package written for ENVI/IDL and released in 2007. MESMA is both a QGIS plugin and stand-alone python package that implements the MESMA (Multiple Endmember Spectral Mixture Analysis) unmixing algorithm in the field of Remote Sensing. QGIS PLUGINS FOR STEREO ALGORITHMS developed as part of the LUMOS project MESMA in QGIS Multiple Endmember Spectral Mixture Analysis (MESMA), visualisation of results and other MESMA-related post-processing. If you have dataset or software tools which are freely available and are the result of a STEREO or other EO research project funded by BELSPO, do not hesitate to send the link to and we will publish it on this webpage. If you want to build your own QGIS plugin, please have a look at the documentation here where you will find step-by-step support for translating an algorithm to a QGIS plugin with documentation.
The LUMOS team realized a set of plugins for QGIS, based on BELSPO research, that appealed to a diverse user group (from student to expert) and now offer you those tools with a user manual and exercises, all in a simple, standardized way.ĭiscover below these tools, as well as a series of datasets and software packages developed in parallel with the LUMOS project by the teams of researchers involved in the STEREO programme.
Its objective was to transform the algorithms developed during the STEREO II programme into user-friendly plugins (written in Python) for the common open-source environment QGIS. With the specific aim of promoting these algorithms and enhancing the research results of Belgian scientists, the LUMOS project (Remote sensing image processing algorithms for land use and land cover monitoring systems) was initiated as part of the Stereo III programme / Application Development. Too often algorithms developed under the umbrella of STEREO projects, although published in A1 publications, are not or only very occasionally disseminated/used by other researchers within and outside the STEREO network. These algorithms can be used to treat different types of images in a multitude of domains. During the successive STEREO programmes, research teams have developed numerous image treatment algorithms.