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Remote Sensing Toolkit (RST) plugin for automated multitemporal remote sensing analysis: application to Spain's 2024
Fatima Ezahrae Ezzaher1, Nizar Ben Achhab2, Hafssa Naciri2
1Mathematics and Intelligent Systems, Abdelmalek Essâadi University, 90000, Tangier, Morocco. fatimazahra.ezzaher@etu.uae.ac.ma.
A new QGIS plugin, Remote Sensing Toolkit (RST), automates satellite image processing for environmental monitoring. It accurately mapped the 2024 Spain flash flood using Sentinel-2 data, demonstrating its utility in disaster assessment.
Area of Science:
- Environmental Science
- Remote Sensing
- Geospatial Analysis
Background:
- Satellite imagery is crucial for environmental monitoring but processing large datasets is complex.
- Existing tools often require extensive programming knowledge, limiting accessibility.
- There is a need for automated, user-friendly solutions for biophysical index computation.
Purpose of the Study:
- To develop an open-source QGIS plugin (Remote Sensing Toolkit - RST) for automated satellite image processing.
- To enable computation of 100 biophysical indices from multiple satellite missions.
- To demonstrate RST's effectiveness in environmental monitoring and rapid disaster assessment.
Main Methods:
- Developed RST as a Python-based QGIS plugin with a programming-free interface.
- Integrated preprocessing tools (cloud masking, scaling, clipping) and AI-based outlier detection.
- Applied RST to Sentinel-2 data for the 2024 Spain flash flood, using SARIMA for anomaly detection in NDVI-derived water extent.
Main Results:
- RST successfully automated satellite data processing and biophysical index computation.
- Temporal anomalies in NDVI-derived water extent correlated with the Spain flash flood event.
- Generated flood extent maps were validated against Copernicus Emergency Management Service Rapid Mapping products.
Conclusions:
- The Remote Sensing Toolkit (RST) plugin effectively automates complex satellite data workflows.
- RST provides a valuable tool for environmental monitoring and rapid disaster response.
- NDVI-derived flood maps offer complementary information for flood extent assessment.
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