{"id":{"repo_id":"york","oai_identifier":"oai:yorkspace.library.yorku.ca:10315/42123"},"canonical_url":"https://search.dev.ndltd.org/etd/york/oai:yorkspace.library.yorku.ca:10315/42123","repository":{"repo_id":"york","name":"York University","base_url":"https://yorkspace.library.yorku.ca/oai/request"},"display":{"title":"Image Classification and Initial Orbit Determination of Resident Space Objects (RSO)","abstract":"The importance of Space Situational Awareness (SSA) research is steadily growing due to continuous launches of new technologies, leading to increased congestion and potential collisions in Earth’s orbit. Optical imagers, based in both ground and space, serve as important tools for observing, detecting, and studying resident space objects (RSOs). Optical imagers capture vast amounts of data that can be used for different applications in SSA research. However, manually inspecting and classifying these images for specific purposes is a time-consuming task. Implementing an automated image classification can streamline the labelling process for optical databases to expedite SSA research. Another significant aspect of SSA research and RSO tracking using optical images involves reliable object identification and Orbit Determination (OD). Angles-only Initial Orbit Determination (IOD) methods are often employed as a starting point to optimize the OD process. These advancements play a pivotal role in enhancing and contributing to SSA research.","abstract_html":"The importance of Space Situational Awareness (SSA) research is steadily growing due to continuous launches of new technologies, leading to increased congestion and potential collisions in Earth’s orbit. Optical imagers, based in both ground and space, serve as important tools for observing, detecting, and studying resident space objects (RSOs). Optical imagers capture vast amounts of data that can be used for different applications in SSA research. However, manually inspecting and classifying these images for specific purposes is a time-consuming task. Implementing an automated image classification can streamline the labelling process for optical databases to expedite SSA research. Another significant aspect of SSA research and RSO tracking using optical images involves reliable object identification and Orbit Determination (OD). Angles-only Initial Orbit Determination (IOD) methods are often employed as a starting point to optimize the OD process. These advancements play a pivotal role in enhancing and contributing to SSA research.","abstract_has_math":false,"creators":["Vallecillo Baires, Andrea Maria"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Lee, Regina"],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-07-18","date_published":"2024-07-18","updated_at":"2026-07-24T06:33:51Z","subjects":["Engineering"],"languages":["en"],"rights":["Author owns copyright, except where explicitly noted. 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Implementing an automated image classification can streamline the labelling process for optical databases to expedite SSA research. Another significant aspect of SSA research and RSO tracking using optical images involves reliable object identification and Orbit Determination (OD). Angles-only Initial Orbit Determination (IOD) methods are often employed as a starting point to optimize the OD process. 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However, manually inspecting and classifying these images for specific purposes is a time-consuming task. Implementing an automated image classification can streamline the labelling process for optical databases to expedite SSA research. Another significant aspect of SSA research and RSO tracking using optical images involves reliable object identification and Orbit Determination (OD). Angles-only Initial Orbit Determination (IOD) methods are often employed as a starting point to optimize the OD process. These advancements play a pivotal role in enhancing and contributing to SSA research."],"dc:identifier.uri":["https://hdl.handle.net/10315/42123"],"dc:language":["en"],"dc:rights":["Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests."],"dc:subject":["Engineering"],"dc:title":["Image Classification and Initial Orbit Determination of Resident Space Objects (RSO)"],"dc:type":["Electronic Thesis or Dissertation"]},"updated_at":"2026-07-24T06:33:51Z"}