GUARDIANS OF THE MEDITERRANEAN: An Orbit-Based Distributed Processing Concept for Rapid Wildfire Alert Generation
- Paper ID
104788
- author
- company
Turkish Technology Team Foundation
- country
Türkiye
- year
2026
- abstract
Mediterranean ecosystems experience recurrent high-intensity wildfires, and response effectiveness is strongly influenced by detection latency. Conventional low Earth orbit (LEO) Earth observation systems primarily rely on store-and-forward architectures in which raw imagery is transmitted to ground stations before processing. This operational sequence introduces delays that may extend to tens of minutes depending on orbital geometry and ground segment availability. This study investigates an alternative architectural approach in which preliminary anomaly detection is executed onboard a distributed nanosatellite constellation, reducing dependency on ground-based processing during critical early ignition phases. The proposed concept considers a regional constellation of twelve 3U-class nanosatellites in low Earth orbit optimized for coverage over the Eastern Mediterranean basin, with specific modeling centered on the Antalya and Taurus Mountain region during peak summer risk conditions. Instead of transmitting full-resolution imagery, each satellite performs onboard spectral anomaly analysis using a compact convolutional model trained for thermal signature discrimination. Only compressed alert packets containing geolocation vectors, confidence scores, and time stamps are transmitted to ground receivers. Orbital mechanics simulations were conducted using Systems Tool Kit (STK) to evaluate revisit frequency and regional coverage distribution under various inclination and altitude configurations. Computational load and power demand were modeled in a Python-based simulation environment to estimate feasibility within a constrained 3U platform envelope. The architecture assumes multispectral sensing in selected shortwave infrared and thermal bands to balance detection capability with mass and power limitations. Simulation results indicate that when a satellite is within observational range, onboard processing enables anomaly classification within approximately 60 seconds of acquisition, significantly reducing decision latency compared to conventional ground-dependent workflows. Under modeled peak-season conditions, the detection framework demonstrated a simulated false-negative rate below 4% for high-intensity wildfire signatures, while maintaining discrimination capability between agricultural burns and uncontrolled events. This work does not present a flight-validated system but a conceptual validation study at early technology readiness level. The findings suggest that redistributing computational authority from ground infrastructure to orbit may enhance responsiveness in time-critical environmental monitoring scenarios. The architecture is presented as a scalable systems-engineering framework rather than a finalized operational mission, offering a basis for future refinement in distributed space-based environmental protection strategies. Declaration on the use of Generative AI and AI-assisted Technologies in the writing process Language editing tools were used solely for grammatical refinement. All technical concepts, modeling assumptions, and system architecture proposals originate from the authors.