🛰️ DEBRISWATCH Space Debris Mitigation Platform Developed by Issam Ahmad · Hackathon Build 2025
Overview DEBRISWATCH is a real-time space debris tracking and mitigation decision-support platform. It visualizes active orbital debris, assesses collision risk, and recommends removal strategies helping operators prioritize the most dangerous objects before a Kessler cascade event occurs. The app is built entirely in React with no external dependencies beyond standard libraries, making it easy to run anywhere.
Features ⬡ Orbital Tracker A live animated canvas showing 25+ tracked debris objects in low and medium Earth orbit. Objects are color-coded by risk level and orbit at realistic relative speeds. Click any object to pull up a full data panel including altitude, velocity, mass, inclination, origin country, and collision probability. ☰ Debris Catalog A filterable, scrollable table of all tracked objects. Filter by risk level (CRITICAL / HIGH / MEDIUM / LOW) and click any row to view a live sparkline of collision probability trends alongside detailed object metadata. ◈ Mitigation Strategies Five evidence-based debris removal technologies, each with efficacy scores, deployment timelines, cost estimates, and a plain-language description of how the method works. Selecting a strategy generates a tailored deployment plan targeting the highest-priority objects in your current queue. StrategyEfficacyEst. CostTimelineLaser Ablation92%$2.4M6–18 monthsIon Beam Shepherd88%$3.2M8–20 monthsHarpoon Capture85%$4.1M12–24 monthsDrag Augmentation78%$0.8M3–9 monthsFoam Spray61%$0.3M1–4 months ⊕ Risk Calculator Enter any debris object's mass (kg), orbital altitude (km), and diameter (m) to instantly compute:
Collision probability (%) Kinetic energy on impact (GJ / kt TNT equivalent) Natural atmospheric decay time (years) Kessler Syndrome fragmentation model output Recommended mitigation action
Getting Started Prerequisites
Node.js 18+ npm or yarn
Tech Stack LayerTechnologyFrameworkReact 18 (hooks)RenderingHTML5 Canvas APIStylingInline CSS + CSS-in-JSFontsSpace Mono, Orbitron (Google Fonts)AnimationrequestAnimationFrame, CSS keyframesDataSeeded deterministic simulation No backend required. All orbital data is generated client-side using a seeded pseudo-random model based on real debris catalogs (TLE-inspired parameters).
Orbital Model Debris positions are computed using a simplified 2D projection of inclined circular orbits: x = cx + cos(θ) × orbitRadius y = cy + sin(θ) × orbitRadius × yScale(inclination) Where θ increments each frame at a speed proportional to the object's altitude (lower orbit = faster angular velocity), consistent with Kepler's third law. Collision probability is derived from:
Cross-sectional area (function of debris size) Orbital altitude (flux density peaks in LEO shell ~800–1000 km) Object mass (determines fragmentation severity)
Risk Classification LevelCollision ProbabilityActionCRITICAL> 2.5%Immediate removalHIGH1.0% – 2.5%Schedule within 6 monthsMEDIUM0.5% – 1.0%Monitor + plan mitigationLOW< 0.5%Passive monitoring
Background Space debris is one of the most pressing long-term threats to orbital infrastructure. As of 2025, there are an estimated 36,500+ objects larger than 10 cm tracked by space agencies, with millions of smaller fragments untracked. A single high-energy collision can generate thousands of new debris fragments — the self-sustaining chain reaction known as Kessler Syndrome — potentially rendering entire orbital shells unusable for decades. DEBRISWATCH was built to demonstrate how a unified decision-support interface could help operators triage removal priorities and select the most cost-effective intervention strategy.
License MIT License — free to use, modify, and distribute.