part of the ongoing monitoring of Earth useful in effective management of the individual and collective activities of man.
Second, NASA currently is obtaining and storing data from Earth-sensing satellites at a rate far out of proportion to the present or expected utilization of that data. The potential utility of collected data is not being realized because the raw data are not accessible in a timely and convenient manner, and because most potential users do not have the resources to extract useful information from the raw files. The current philosophy of data collection and storage had its origin in the early days of space research when sensors were sent into space, turned on, and all results transmitted back and stored. While this appears to maximize the utilization of the space vehicle, it has proven to be a false economy - the vast majority of uncategorized, generally unorganized data have never been and possibly never will be analyzed. The data format, its raw condition (digital conversions of analog sensor readings), and the complete lack of cross-referencing of contents make the data extremely difficult to find, interpret, or use. The tremendous volume of information already amassed and the expected increases in future rates of collection due to improved sensor technology make the philosophy of unorganized data acquisition obsolete. An alternate philosophy of goal-oriented data collection (information is gathered to meet specific objectives) was taken as the cornerstone of the proposed mission.
Thus, the main mission objective was to develop the concept of a flexible, intelligent, user-oriented automated information system for the collection, analysis, storage, and delivery of satellite Earth-sensing information (table 2.1). TABLE 2.1.- RATIONALE FOR DEVELOPMENT OF AN INTELLIGENT EARTH-SENSING INFORMATION SYSTEM. Why use remote sensing of the Earth Management ---- control Improved understanding - knowledge Information cannot be obtained any other way Current difficulties Vast amount of unorganized data Acquisition and distribution of useful information High cost The solution Goal-oriented observation Direct user interaction with the system World model-based observations Autonomous system Within rational cost bounds, the system should maximize the utilization of this information for the following purposes: scientific, managerial, commercial, and humanitarian. In addition, the collection and storage of data having little or no utility should be minimized, and the costs of acquiring, interpreting, and storing Earth resource information must also be reduced.
Inexpensive data delivery can be accomplished by a system operating with relatively little human intervention. Price reduction requires that images be processed without costly manual procedures, and that the physical satellite system be managed so as to obtain a maximum of useful data for the given configuration of orbits and sensors. It seems possible to design and construct, by the year 2000, a largely autonomous system that can directly interface with individual users in natural language, accept requests for information, and provide answers based on satellite observations coupled with a resident theoretical model of the state of the world. Such a system should be able to achieve sophisticated data interpretation at modest cost through advances in machine hardware and artificial intelligence techniques. Tabic 2.2 lists several desirable system characteristics and suggested methods for their achievement. The key to the proposed system is a sophisticated world model (section 2.3) that enables the system to perceive both the present state of the world and how that state changes in time. TABLE 2.2
DESIRABLE CHARACTERISTICS OF AN INTELLIGENT EARTH SENSING INFORMATION SYSTEM AND METHODS OF REALIZATION. Desirable system characteristics Methods of realization Cost minimization relative to level of service provided Maximize system autonomy Interface users directly to system Goal oriented observing relative to world model Wide utilization Flexible user interfacing including natural
language Automatic data interpretation AI techniques based on world model
