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Recent decades have seen the development of more advanced sensor and communication systems, with the future certainly holding more innovation in these areas. However, current operations involve "stovepipe" systems in which inefficiencies are inherent. In this thesis, we examine how to increase the value of Earth observations made by coordinating across multiple collection systems. We consider both air and space assets in an asynchronous and distributed environment. We consider requests with time windows and priority levels, some of which require simultaneous observations by different sensors. We consider how these improvements could impact Earth observing sensors in two use areas; climate studies and intelligence collection operations. The primary contributions of this thesis include our approach to the asynchronous and distributed nature of the problem and the development of a value function to facilitate the coordination of the observations with multiple surveillance assets.We embed a carefully constructed value function in a simple optimization problem that we prove can be solved as a Linear Programming (LP) problem. We solve the optimization problem repeatedly over time to intelligently allocate requests to single-mission planners, or "sub-planners." We then show that the value function performs as we intend through empirical and statistical analysis.To test our methodologies, we integrate the coordination planner with two types of subplanners, an Unmanned Aerial Vehicle (UAV) sub-planner, and a satellite sub-planner. We use the coordinator to generate observation plans for two notional operational Earth Science scenarios. Specifically, we show that coordination offers improvements in the priority of the requests serviced, the quality of those observations, and the ability to take dual collections. We conclude that a coordinated planning framework provides clear benefits.

among separate sensing assets, creating inefficiencies that could be avoided through coordinated planning. Such isolation between operations of separate planners means that requests may not be allocated to the most appropriate sensors based on their specific requirements. Studies requiring sensing assets have become increasingly more prevalent in the past few years, suggesting a more urgent need for a coordinated planning framework. One of the major recent uses of sensor systems involves employing satellites or unmanned aerial vehicles (UAVs) to study Earth's climate. The Earth Observing System, designed by NASA, is one such example of a set of sensors being used for climatology. Within this system, NASA launched many satellites. The Suomi National Polar-Orbiting Partnership (NPP) satellite is one of these, launched in October 2011. This satellite orbits Earth about 14 times per day, observing nearly the entire surface in this time period. The sensors onboard NPP perform many different climate-related operations, such as creating global models of temperature and moisture profiles for use by meteorologists, monitoring the ozone levels near the poles, measuring atmospheric and oceanic properties, and examining both emitted and reflected radiation from Earth's surface [1]. The Aqua satellite, also in the NASA Earth Observing System, collects information about the following: Earth's water cycle, including evaporation from the oceans, water vapor in the atmosphere, clouds, precipitation, soil moisture, sea ice, land ice, and snow cover on the land and ice. Additional variables also being measured by Aqua include radiative energy fluxes, aerosols, vegetation cover on the land, phytoplankton and dissolved organic matter in the oceans, and air, land, and water temperatures [2]. These are just two examples of the many satellites currently in orbit collecting climate-related information, all of which have some sort of overlapping interests and may even contain some of the same sensor models. As such, implementing a coordinated planning scheme within satellite planners of the Earth Observing System, or any climate-related satellites, could prevent redundant gathering of the same data while spreading collection demands more evenly across the satellites for more effective sensor utilization. Recent interest in examining natural disasters has also increased, furthering the need to efficiently coordinate between sensor planners. The Hurricane and Severe Storm Sentinel, which is a NASA investigation designed to enhance understanding of the "processes that underlie hurricane formation and intensity change in the Atlantic Ocean basin," is one such example of a mission trying to learn more about natural disasters [3]. The U.S. Forest Service has also recently been employing UAVs and satellites to help image active wildfires, reducing the risks of "smoke, excessive thermal wind drafts, and unfamiliar terrain" on the pilots that usually do the imaging in airplanes or helicopters [4]. Science and forestry are not the only areas that c...

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