SAT
WATCH
EXPLORING THE ORBITS
TRACKING, PREDICTING, AND MITIGATING ORBITAL THREATS
TEAM:
USSEIM
UPRIYA
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H
inki
PROBLEM
STATEMENT
Sources:
image_1: https://www.bigstorynetwork.com/content/blinded-by-the-light-nasa-says-96-of-space-telescope-images-at-risk
Image_2:https://www.reuters.com/science/nasa-study-shows-how-satellite-light-pollution-hinders-space-telescopes-2025-12-03/
Image_3: https://skyandtelescope.org/astronomy-news/satellites-and-space-debris-are-polluting-our-night-skies/
Image_4: https://www.stevens.edu/news/space-debris-endangers-future-space-missions-but-theres-a-way-to-clean-it-up
RESEARCH QUESTIONS
1. Trends and current state of satellite populations in the atmosphere?
2. How fast is orbital debris growing and what does that mean for future satellite safety and space sustainability & light pollution and astronomy?
3. Who is responsible:
governments, space agencies, or private companies?
DATA CLEANING & TRANSFORMATION
Datasets:
Source 1: Kaggle dataset Link to Dataset
Source 2:
Dataset Cleaning and Merging:
ANALYSIS & RECOMMENDATIONS
Analysis Takeaway:
• Satellite growth accelerated strongly from 2015–2023, with a big boom after 2019.
• LEO is the most crowded orbit with commercial communication satellites.
• SpaceX/Starlink dominates by 60% the active-satellite landscape controlling the orbit.
• The trend is still rising, and more satellites will become debris if they are not removed properly.
SATWATCH recommendations for Stakeholder:
• Tighten launch rules for crowded orbits .
• Restrict Satellite orbits above observatories to reduce light pollution.
• Push for global regulation and shared debris standards.
HAPPY TO ANSWER YOUR QUESTIONS
THANK YOU
TEAM: SUPRIYA AND HUSSEIM
“Satellite expansion is no longer just a technological success story; it is becoming a governance problem that requires global regulation, cleaner design, and active debris management.”
CHALLENGES
• Dataset selection was difficult because the needed information was spread across multiple sources, so no single dataset gave a full picture.
• Data cleaning took time, especially because values were inconsistent, spelling varied, and some fields needed standardization.
• Key information was fragmented across different datasets, which made merging and comparing data more complex.
• API access was limited to 2 hours, which restricted exploration, extraction, and validation of the data.
• The topic is highly technical, and many satellite-related terms were not well documented, especially column definitions and metadata.