CHAPTER 2
TERRESTRIAL APPLICATIONS: AN INTELLIGENT EARTH-SENSING INFORMATION SYSTEM
2.1 Introduction
Figure 2.1.- Terrestrial applications: An intelligent Earth-sensing information system. PRECEDING PAGE BLANK NOT FILMO*
The Terrestrial Applications Team was charged with identifying a sample near-Earth NASA mission that could be implemented during the next two or three decades and that would require intensive application of artificial intelligence and robotics technologies. The team initially considered a long list of missions that included the design and automated fabrication of a satellite solar power station, weather sensing and prediction, crop assessment, large communication satellites, and disaster monitoring. As the catalogue of possible tasks evolved, it became clear that artificial intelligence would be most useful when applied to missions that generate data at very high rates - such as the NASA applications (Landsat) satellites which provide imaging data of the Earth. The team focused on the development of an integrated, user-oriented, Earth-sensing information system (fig. 2.1) incorporating a maximum of artificial intelligence capability for two primary reasons.
First, substantial economic benefits may accrue from the effective use of an integrated, intelligent remote Earth- sensing system. For example, a reduction in weather damage to crops, the location of mineral deposits and earthquake faults, and more efficient means of surveying large tracts of land may save time, money, and even human lives. With superior definition of models for weather forecasting, climate and oceanic processes may eventually make possible more precise meteorological prediction and ultimately even weather control and global climate modification (Outlook for Space, 1976). Such an intelligent sensing system can play a dominant role in the activity of understanding the Earth as a dynamic physical entity, and can provide a major
