Developing a Python-based Synthetic Aperture Radar Visualization System for Flood Mapping

Overview

As we enter an era where natural disasters are increasing in frequency and intensity globally, the need for advanced disaster response technologies has never been more pressing. Floods, in particular, pose a formidable threat to communities and infrastruct ure worldwide, demanding effective and comprehensive response systems. Remote sensing plays a crucial role in disaster response and has become an indispensable tool for scientists and decision makers alike. Synthetic Aperture Radar (SAR), an effective and rapidly developing technique, has traditionally relied solely on satell ites for environmental monitoring. However, the unconventional approach of using an unmanned aerial vehicle (UAV) -based SAR system adds flexibility, unparalleled resolution, and potential for detailed disaster tracking. Our system aims to pioneer new approaches to SAR-based remote sensing by creating a high-quality and low-computational-cost UAV-based SAR visualization system. Our software, programmed from scratch and fully based in Python, showcases effective approaches to SAR visualization using an integration of live UAV-based scans with geospatial satellite imagery for flood disaster response. Our project details the development of our SAR visualization system and our findings on the most effective approaches.

Competition history

• JSHS 2024 Category not listed

Resources

• National JSHS abstract book ↗

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