STEREO toolbox

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Durant les programmes STEREO successifs, de nombreux algorithmes de traitement d'images  ont été développés par les équipes de chercheurs. Ces algoritmes sont applicables à différents types d'images et à une multitude de domaines.

Les algorithmes développés dans le cadre des projets STEREO, bien qu’ils soient souvent publiés dans des revues scientifiques de qualité, ne sont que très rarement diffusés et utilisés par d'autres chercheurs, que ce soit au sein ou en dehors du réseau STEREO.

Dans le but spécifique de promouvoir ces algorithmes et de valoriser les résultats de recherche des scientifiques belges, le projet LUMOS (Remote sensing image processing algorithms for land use and land cover monitoring systems) a été initié, dans le cadre du programme Stereo III / Développement d'applications.

Son objectif était de transformer les algorithmes développés durant le programme STEREO II en plugins conviviaux (écrits en Python) pour l'environnement open-source commun QGIS.

L'équipe du projet LUMOS a donc réalisé un ensemble de plugins pour QGIS à l’intention de divers groupes d'utilisateurs (de l'étudiant à l'expert). Ces outils sont maintenant disponibles, accompagnés d’un manuel d'utilisation et d’exercices, le tout utilisable de manière simple et standardisée.

Découvrez ci-dessous ces outils, ainsi qu'une série de logiciels développés en parallèle du projet LUMOS par les équipes de chercheurs impliqués dans le programme STEREO.

Si vous souhaitez élaborer vous-même votre propre plugin QGIS, nous vous invitons à consulter la documentation fournie via ce lien. Vous y trouverez de l’aide documentée, étape par étape, pour traduire un algorithme en un plugin QGIS.

Si vous disposez d'outils logiciels en libre accès qui ont été développés dans le cadre d'un projet STEREO ou d'un autre projet en Observation de la Terre financé par BELSPO, n'hésitez pas à nous envoyer le lien à l'adresse stereonews@belspo.be et nous le publierons sur cette page.

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.

 

 

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.

It is based on VIPER Tools: a software package written for ENVI/IDL and released in 2007. Several updates have been released since and now it has been ported to PyQGIS in the period 2017 - 2020. The original VIPER Tools is now split over two python/QGIS tools: Spectral Library Tool and MESMA.

Spectral Library Tool

Build, visualize and optimize spectral libraries.

 

 

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.

The software is based on VIPER Tools: code written for ENVI/IDL and released in 2007. Several updates have been released since and now it has been ported to PyQGIS in the period 2017 - 2020. The original VIPER Tools is now split over two python/QGIS tools: Spectral Library Tools and MESMA.

 

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 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.

The original Tree Density Calculator was written in C++ and ported to PyQGIS in 2018/2019. It has been developed in an open source environment to encourage further development of the tool.

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.

 

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. It uses an MLP (Multi-Layer Perception) Neural Network Classifier and is based on the Neural Network MLPClassifier by scikit-learn.

The program was originally developed by Lieven P.C. Verbeke (Ghent University, Laboratory of Forest Management and Spatial Information Techniques). It was written in C++ and ported to PyQGIS in 2019 - 2020. It has been developed in an open source environment to encourage further development of the tool.

EOF-based Time Series Reconstructor

Image reconstructing algorithm based on EOFs (empirical orthogonal functions), designed specifically for oceanography.

 

The EOF-based Time Series Reconstructor software package is a QGIS plugin that provides a EOF-based reconstruction tool for filling gaps, caused by e.g. clouds, in geophysical time series, like ocean temperature. It is developed specifically for oceanography.

The software is based on DINEOF: a FORTRAN tool in continuous development since 2008.

The software has now been developed in the open source environment to encourage further development of the tool.

FORCE4Q

Visualize FORCE Level-2 outputs or Landsat/Sentinel2 Level-2A products in QGIS.

 

FORCE4Q is a QGIS plugin for generating higher level EO data products,  It is a QGIS port for the higher level functionality of the Framework for Operational Radiometric Correction for Environmental Monitoring (FORCE). It specifically makes use of FORCE’s Higher Level Processing System for generating image composites and time series from multitemporal Level 2 bottom of atmosphere surface reflectance imagery. FORCE4Q is compatible with Landsat 5-8 and Sentinel-2 reflectance imagery as downloaded from common online repositories.

Bit Flag Renderer

Visualisation of individual bit flags in the Quality Assurance (QA) band of common EO data like Landsat, MODIS or FORCE L2).

 

The Bit Flag Renderer is a QGIS Plugin to visualize bit flags in raster quality images.

The Bit Flag Renderer is developed at Humboldt-Universität zu Berlin, Earth Observation Lab.

EO Time Series Viewer

Interactive visualization and labelling of time series data that is composed of different spatial, spectral and temporal domains.

 

Get help in transforming your code to a QGIS plugin, but also:

  • Write test classes for your code;
  • Create online documentation (like what you are reading now);
  • What are the requirements to upload your plugin to the official QGIS repository;
  • Build and upload a python package to PyPi.
     

OTHER STEREO AVAILABLE TOOLS

Les équipes de chercheurs impliqués dans le programme STEREO ont également développé des logiciels accessibles en parallèle du projet LUMOS. Vous en trouverez une sélection ci-dessous.

ACOLITE

 

ACOLITE combines the atmospheric correction algorithms for aquatic applications of Landsat and Sentinel-2 developed at RBINS. This repository hosts the (more) generic version of ACOLITE with the aim of bringing together the processing of all different sensors. ACOLITE allows simple and fast processing of imagery from various satellites, including Landsat (5/7/8) and Sentinel-2/MSI (A/B), PlanetScope and RapidEye, Venµs, SPOT and Pléiades, WorldView-2 and -3, and Sentinel-3/OLCI (A/B) for coastal and inland water applications.
ACOLITE development was funded under various projects including the JELLYFOR and PONDER STEREO projects.

Complete InSAR suite developed by the signal Lab of CSL

 

The Centre Spatial de Liege (CSL) has a long standing experience in the frame of SAR processing and SAR interferometry (InSAR). In the frame of numerous projects mainly funded by BELSPO and ESA, the signal Lab of CSL has developed a complete InSAR suite now known has CIS. CIS, as all tools of its kind, allows performing all processing steps for InSAR, DInSAR, PolSAR, PolInSAR, … including geoprojection of results in raw or ENVI format.

DIARS toolbox

 

This website is part of the DIARS project that brings together European experts from remote sensing and ecology to demonstrate and characterize the impact of invasive species on ecosystems through the combined use of field data and data obtained through remote-sensing technologies and support the monitoring and prediction of spread and risk assessment of invasive plant species. It consists of a series of tutorials that walk you through a remote sensing-based framework for mapping, modelling and assessing the impact of biological invasions.

SAT-EX Codes & Data

 

The SAT-EX project focused on tne impact of climate and climate extremes on global vegetation. Different source codes are freely available via the Laboratory of Hydrology and Water Management (LHWM) github channel:

  • ConditionalSpectralGrangerCausality

  • E2CI---Detecting-relations-between-modes-of-climate-variability-and-land-evaporation

  • Hydro-climatic-biomes

  • ClimateVegetationDynamics_GrangerCausality

TACT

 

TACT is the Thermal Atmospheric Correction Tool for Landsat developed at RBINS. It retrieves ERA5 atmospheric profiles and uses libRadtran to compute the atmospheric transmittance, and down- and upwelling radiances. Currently TACT outputs the Water Surface Temperature (WST) in each thermal band present on the Landsat sensor, assuming a constant (water) emissivity over the scene.

TREX

 

TREX (Tool for Raster data EXploration) is an automatic processing tool allowing extraction of Time series of Leaf Area Index from ProbaV satellite images.

TREX was developped for the STEREO III HIWET (High-resolution modelling and monitoring of water and energy transfers in wetland ecosystems) project and is  available on GITHUB.

VIPER Tools

 

The VIPER Tools software package is an ENVI add-on that provides a suite of processing tools for multiband passive optical remote sensing data including hyperspectral and multispectral imagery. The major components of the software are tools for creating and managing spectral libraries, for selection of optimal endmembers for Spectral Mixture Analysis (SMA) and for calculating and interpreting SMA and Multiple Endmember Spectral Mixture Analysis (MESMA).