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PRINT OUT IMAGE COORDINATES: E141-45 S30-06 LOCAL NAME: SEC 192, MILDURA, VICTORIA, AUSTRALIA 9-12 - 74 21:08 VMT NICHES 1 2 3 4 LAKE RIVER FOREST GLEN GRASSLAND CLASS NAME GEORGE CHARLES STIRLING GREEN LOW CHANNEL # AVERAGE 1 2 3 4 5 6 SENSOR BLUE GREEN YELLOW RED NEAR/R FAR/R READING: 85 ? 7 35 ? 3 7 ? 1 1 ? 1 6 ? 1 8 ? 1

63 ?4 60 + 2 30 ?3 16 ? 5 5 ? 1 1.6 ? 5

7 ? 1 58 ? 7 25 ? 2 12 ? 2 8 ? 2 3? 1 'COLOR 5960 ? 38 4500 ? 26 3106 ? 22 H2 ' IR 310 ? 28 305 ? 6 316 ? 5 H3

WEIGHTED AVERAGE OVER CHANNEL: COLOR TEMP 4302 ? 20 GROUND TEMP 307 ? 02 MOISTURE 0.06

H4

WOMBAT COUNT 506/mi2 CLOUD COVER 15% MURRAY IN FLOOD

H5

HIERARCHY HI ALL DATA, ALL SENSORS H2 NICHE AVERAGE, ALL SENSORS H3 NICHE CHARACTERISTIC H4 NEIGHBORHOOD CHARACTERISTIC H5 SPECIAL REQUEST

Figure 2.10.~ Hypothetical IESIS user printout following scan of Mildura City.

features of the incoming image are contrasted and identified with distinguishable features (niches) catalogued in the model. The number of bits N needed to store this information on some or all features is N = ni, where n is the number of niches in all or part of the world model and i is the number of bits required to describe a niche. Examples that estimate N are given below.

Niches. The niche is a broad distinguishable geographical region having some common features across its surface when viewed from space. Niches are easily separable, somewhat permanent features (large rivers, canals, lakes, major highways, cultivated areas or forests) recognizable within a predetermined orbital swath. Since niches consist of common features, data acquired across them have very high redundancy. A large amount of data reduction is obtained by describing the entire niche with a limited number of common values abstracted from the whole set of niche data on record.

It is estimated that a total of i= 122 bits is required for individual niche identification, as follows: Location of centroid, 6 bytes, 48 bits; maximum and minimum of horizontal, 2 bytes, 16 bits; maximum and minimum vertical, 2 bytes, 16 bits; orientation, 2 bytes, 16 bits; abstract shape among 1000 choices, 10 bits: naming the niche, 2 bytes, 16 bits. In addition, s sensors are assumed scanning

GROUND