2026-09-18T19:12:54Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/671932022-01-13T07:54:11Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Edward F. Crawley.
Suarez, Brandon H
Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
2011-11-18T20:58:47Z
2011-11-18T20:58:47Z
2011
2011
http://hdl.handle.net/1721.1/67193
758672221
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 170-176).
The Global Earth Observation System (GEOS) is the essential data gathering network that enables the advancement of Earth science. In recent years, efforts have been made to understand the major GEOS architectural tradeoffs. Several decision support tools have been developed, including the Campaign-level Science Traceability Matrix (CSTM). The CSTM is a framework designed to trace the benefit delivered by a campaign of Earth observing systems to relevant stakeholders. This thesis first presents the CSTM v 1.1, an enhanced version of the original CSTM, which updates the scientific understanding captured in the framework. This benefit tracing framework is applied to the set of satellite missions recommended by the National Research Council Earth Science Decadal Survey. To support campaign scheduling, this thesis presents and applies a multi-objective Genetic Algorithm (GA), built using the Matlab GA toolkit. The algorithm seeks to maximize "Data Value", minimize the effects of "Data Gaps", and accounts for cost, budget, and technology readiness. The results show that under the current conditions, gaps in important measurements will arise in the near future as currently operational NASA Earth observation missions age and their replacements continue to experience development issues. This result motivates a systematic rethinking of measurement gap mitigation strategies and the use of airborne observational platforms in the GEOS. The integration of aircraft into the GEOS is explored through three case studies. Three unique modes of operation for aircraft in Earth observation are presented and characterized. Based on the results of the case studies, a quantitative framework, called CSTM v2.0, is introduced. CSTM v2.0 uses a Rule-Based Expert System (RBES) that evaluates instruments at a level of fidelity that allows for comparison between aircraft and spacecraft. The GA campaign scheduling tool is used to understand the role of aircraft in the GEOS. The results of this analysis show that aircraft provide a short-term source of high value missions and are able to fill critical measurement gaps. This thesis recommends that aircraft be considered as operational platforms in future GEOS architectures, recognizing that autonomous systems promise significant benefits for Earth observation.
by Brandon H. Suarez.
S.M.
176 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Aeronautics and Astronautics.
Integrating spacecraft and aircraft in Earth Observation System architectures
Thesis
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<Abstract>The Global Earth Observation System (GEOS) is the essential data gathering network that enables the advancement of Earth science. In recent years, efforts have been made to understand the major GEOS architectural tradeoffs. Several decision support tools have been developed, including the Campaign-level Science Traceability Matrix (CSTM). The CSTM is a framework designed to trace the benefit delivered by a campaign of Earth observing systems to relevant stakeholders. This thesis first presents the CSTM v 1.1, an enhanced version of the original CSTM, which updates the scientific understanding captured in the framework. This benefit tracing framework is applied to the set of satellite missions recommended by the National Research Council Earth Science Decadal Survey. To support campaign scheduling, this thesis presents and applies a multi-objective Genetic Algorithm (GA), built using the Matlab GA toolkit. The algorithm seeks to maximize "Data Value", minimize the effects of "Data Gaps", and accounts for cost, budget, and technology readiness. The results show that under the current conditions, gaps in important measurements will arise in the near future as currently operational NASA Earth observation missions age and their replacements continue to experience development issues. This result motivates a systematic rethinking of measurement gap mitigation strategies and the use of airborne observational platforms in the GEOS. The integration of aircraft into the GEOS is explored through three case studies. Three unique modes of operation for aircraft in Earth observation are presented and characterized. Based on the results of the case studies, a quantitative framework, called CSTM v2.0, is introduced. CSTM v2.0 uses a Rule-Based Expert System (RBES) that evaluates instruments at a level of fidelity that allows for comparison between aircraft and spacecraft. The GA campaign scheduling tool is used to understand the role of aircraft in the GEOS. The results of this analysis show that aircraft provide a short-term source of high value missions and are able to fill critical measurement gaps. This thesis recommends that aircraft be considered as operational platforms in future GEOS architectures, recognizing that autonomous systems promise significant benefits for Earth observation.</Abstract>
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