SSTAR - Subtle Surface Thermal Anomalies Recognizer

SSTAR v1.0 SSTAR is a versatile and user-friendly application designed to analyze diffuse thermal anomalies at active volcanoes. SSTAR (Subtle Surface Thermal Anomalies Recognizer) is an interactive application designed to detect, analyze, and visualize subtle surface thermal anomalies from satellite thermal infrared observations. It provides a comprehensive framework for thermal data preprocessing, filtering, interpolation, anomaly quantification, spatiotemporal mapping, and visualization, facilitating the investigation of long-term thermal signals associated with volcanic, geothermal, and other geophysical processes. Authors: Társilo Girona and Laure Brenot Contact: tarsilo.girona@csic.es Installation and Files This repository provides three main files: (1) SSTAR_app.zipCompressed folder containing the SSTAR standalone installer (SSTAR_installer.exe) together with an example dataset illustrating the application of the software at Shishaldin Volcano (Alaska). This package is intended for users who wish to quickly explore SSTAR and does not require a MATLAB license, as the installer includes the necessary MATLAB Runtime. We recommend downloading this package to get started, as it provides a complete, ready-to-use setup along with a practical example demonstrating the workflow. (2) SSTAR_Installer.exeStandalone, user-friendly version of SSTAR with a graphical user interface (GUI). The installer includes the required MATLAB Runtime, allowing the application to run independently without a MATLAB license. This option does not include an example dataset. (3) SSTAR_v1.mlappMATLAB App Designer version of SSTAR, developed in MATLAB R2021b. This version contains the script and is intended for users with MATLAB (preferably R2021b) who wish to explore, adapt, or extend the underlying code and methodology. Quick Start Download the SSTAR_app.zip folder. Extract the contents of the folder. Open SSTAR_installer.exe. Run the installer and follow the instructions (this will also install the MATLAB Runtime if needed). Launch SSTAR from the installed application. Load the example dataset within the GUI and run the analysis. Follow the instructions provided in the README file and the HELP menu within the application. Notes The user-friendly, standalone version is designed for ease of use and does not require programming experience. The MATLAB version (SSTAR_v1.mlapp) provides full flexibility for customization and methodological development. A stable internet connection is recommended when downloading the example dataset (SSTAR_app.zip). At least 15.4 GB of free disk space is required to extract the contents of SSTAR_app.zip. Copyright (c) 2026 Társilo Girona and Laure Brenot.All rights reserved. Permission is hereby granted to use, copy, modify, and redistribute thissoftware and its associated documentation for non-commercial research,educational, and academic purposes only, provided that this copyrightnotice and this permission notice are retained in all copies orsubstantial portions of the software. Commercial use, commercial distribution, sublicensing, or sale of this software, in whole or in part, is prohibited without the prior writtenpermission of the copyright holders. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESSOR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OFMERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND NONINFRINGEMENT.IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANYCLAIM, DAMAGES, OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,TORT, OR OTHERWISE, ARISING FROM, OUT OF, OR IN CONNECTION WITH THESOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.