Page:Advanced Automation for Space Missions.djvu/30



TABLE 2.4,-WORLD MODEL CHARACTERISTICS OF LAND, OCEAN, AND ATMOSPHERIC WORLD MODELS.

Land Extensive, detailed contour maps exist Relatively static Sharp boundaries Small feature size Widely populated Oceans Gross maps exist Constant altitude Wide boundaries Large feature size Sparsely populated Atmosphere 3-dimensional Elementary model exists Rapidly varying Boundaries difficult to identify Large shifting patterns Some small feature sizes Substantially unpopulated

Niches possess a high degree of spatial redundancy. A large lake remains the same lake on each satellite overpass, and parts of the lake are very similar to other parts, yet are very distinct from the surrounding land. The large redundancy permits very substantial data reduction by processing each sensor reading across a single niche and extracting desired characteristics of that niche. These characteristics can be combined across sensors to produce yet further compaction. Despite the large reduction in physical data, no useful information is lost.

The likely scale of data compaction is illustrated by considering a 10 km X 10 km land region at a pixel resolution of 10 m. This scale gives an image measuring 1000 X 1000 pixels. If just one observational wavelength is involved, and 8 bits are used to represent intensity at each of the 106 pixels, the resulting image is 8 X 106 bits. A limited examination of aerial photographs suggests such a region will possess an average of 30 niches. Each must be fully described in terms of characteristics important to it such as area, average sensor value, variance, higher moments, two- dimensional sensor intensity gradient, and texture. If 15 characteristics are sufficient to describe most niches, then only 3600 bits (15 characteristics X 30 niches X 8 bits/niche-characteristic) are needed to replace the 8,000,000 bits of the full image. A reduction of 2222:1 is immediately accomplished.

Further reduction can be achieved by combining data across the approximately 20 sensor wavelengths proposed for the satellites, and also across the 15 characteristics. This reduced data can be used, for example, in signature identification, specification of niche status, or for classifying an anomaly. Near-maximum reduction occurs when imagery is required to answer a sophisticated question posing a choice from 256 (= 28) alternatives, an answer requiring just 8 bits - the 106 pixel elements over 20 sensors demand one 8-bit transmission and subsequent storage for a reduction of 20,000,000:1 ([106 elements X 20 sensors X 8 bits/sensor- element]/[8 answer bits]). If the question requires a "yes" or "no" answer only 1 bit must be transmitted and the absolute maximum data reduction in this simplified example is achieved - 160,000,000:1 - as summarized in table 2.5.

IESIS also is capable of discovery. Novel occurrences can be detected by the satellite system when searching for anomalous features in the imagery as compared to the world model. Many of these anomalies may be boundary changes in the existing map, e.g., overflow of the River Murray as shown with dark lines in figure 2.9. Others will involve unusual values of sensory characteristics of the niche (e.g., blight on a corn field). Prompt identification of these anomalies allows real-time management action in response to the "abnormal" occurrence. Figure 2.10 illustrates a hypothetical set of readouts from an intelligent satellite scan over Mildura.

The most efficient use of a world model requires placement of a simplified model in memory onboard the satellite system (to accomplish direct data reduction) and retention of a more sophisticated model in the ground operations facility. The latter serves as a master Earth model for use in updating, calibrating, and further processing transmitted data. (Estimated memory requirements are given in section 2.3.2.) Another very important feature of the ground- based world model is that it allows full cross-indexing of

TABLE 2.5,- DATA REDUCTION USING WORLD MODEL IN A SIMPLIFIED EXAMPLE.

Transmission/storage task Total bits Net reduction 106 image pixels, 20 sensors 8 bits each 1.6X108 1:1 30 niches, 20 sensors, 15 characteristics at 8 bits 7.2X104 2,222:1 256 choice answer 8 20,000,000:1 Yes or no answer required 1 160,000,000:1