Advanced space system concepts and their orbital support needs (1980 - 2000). Volume 3: Detailed data. Part 1: Catalog of initiatives, functional options, and future environments and goals

The following areas were discussed in relation to a study of the commonality of space vehicle applications to future national needs: (1) index of initiatives (civilian observation, communication, support), brief illustrated description of each initiative, time periods (from 1980 to 2000+) for implementation of these initiatives; (2) data bank of functional system options, presented in the form of data sheets, one for each of the major functions, with the system option for near-term, midterm, and far-term space projects applicable to each subcategory of functions to be fulfilled; (3) table relating initiatives and desired goals (public service and humanistic, materialistic, scientific and intellectual); and (4) data on size, weight and cost estimations

EOS Data and Information System (EOSDIS)

In the past decade, science and technology have reached levels that permit assessments of global environmental change. Scientific success in understanding global environmental change depends on integration and management of numerous data sources. The Global Change Data and Information System (GCDIS) must provide for the management of data, information dissemination, and technology transfer. The Earth Observing System Data and Information System (EOSDIS) is NASA's portion of this global change information system

Network MIMO with Partial Cooperation between Radar and Cellular Systems

To meet the growing spectrum demands, future cellular systems are expected to share the spectrum of other services such as radar. In this paper, we consider a network multiple-input multiple-output (MIMO) with partial cooperation model where radar stations cooperate with cellular base stations (BS)s to deliver messages to intended mobile users. So the radar stations act as BSs in the cellular system. However, due to the high power transmitted by radar stations for detection of far targets, the cellular receivers could burnout when receiving these high radar powers. Therefore, we propose a new projection method called small singular values space projection (SSVSP) to mitigate these harmful high power and enable radar stations to collaborate with cellular base stations. In addition, we formulate the problem into a MIMO interference channel with general constraints (MIMO-IFC-GC). Finally, we provide a solution to minimize the weighted sum mean square error minimization problem (WSMMSE) with enforcing power constraints on both radar and cellular stations.Comment: (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems

Useful applications of earth-oriented satellites - Systems for remote-sensing information and distribution, panel 8

Problems and potential use of data gathered by remote sensing from satellites or aircraf

Policy issues and data communications for NASA earth observation missions until 1985

The series of LANDSAT sensors with the highest potential data rates of the missions were examined. An examination of LANDSAT imagery uses shows that relatively few require transmission of the full resolution data on a repetitive quasi real time basis. Accuracy of global crop size forecasting can possibly be improved through information derived from LANDSAT imagery. A current forecasting experiment uses the imagery for crop area estimation only, yield being derived from other data sources

Earth observing system. Data and information system. Volume 2A: Report of the EOS Data Panel

The purpose of this report is to provide NASA with a rationale and recommendations for planning, implementing, and operating an Earth Observing System data and information system that can evolve to meet the Earth Observing System's needs in the 1990s. The Earth Observing System (Eos), defined by the Eos Science and Mission Requirements Working Group, consists of a suite of instruments in low Earth orbit acquiring measurements of the Earth's atmosphere, surface, and interior; an information system to support scientific research; and a vigorous program of scientific research, stressing study of global-scale processes that shape and influence the Earth as a system. The Eos data and information system is conceived as a complete research information system that would transcend the traditional mission data system, and include additional capabilties such as maintaining long-term, time-series data bases and providing access by Eos researchers to relevant non-Eos data. The Working Group recommends that the Eos data and information system be initiated now, with existing data, and that the system evolve into one that can meet the intensive research and data needs that will exist when Eos spacecraft are returning data in the 1990s