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depends mainly on <strong>the</strong> density of features of interest<br />

and <strong>the</strong> granularity of <strong>the</strong> data. Carefully adjusting<br />

<strong>the</strong> granularity for <strong>the</strong> most accuracy with <strong>the</strong> least<br />

number of data points will permit a reasonably small<br />

area (40 km x 60 km) to be stored at an accuracy of 15-<br />

20 meters using around one million bytes for x, y, and<br />

z coordinates. Attempting accuracies of 10 meters or<br />

less can increase <strong>the</strong> amount of data dramatically. The<br />

controlling factor for accuracy in data culling is <strong>the</strong><br />

straightness of <strong>the</strong> network segments. Very straight<br />

segments (even long ones) can be stored with only two<br />

points, while curved segments may require thousands of<br />

points to represent <strong>the</strong> same distance.<br />

In contrast to lineal and areal data, hypsographic data<br />

is recorded as a matrix of elevations, with each eleva<br />

tion's position in <strong>the</strong> matrix corresponding to its<br />

position in <strong>the</strong> real world.<br />

The storage space needed for matrix data is directly<br />

proportional to <strong>the</strong> spacing within <strong>the</strong> matrix and <strong>the</strong><br />

size of <strong>the</strong> area it represents. Storage may vary from<br />

several thousand bytes for a small area (40 km x 60 km)<br />

with wide spacing (about one elevation value every 500<br />

meters), to tens of millions of bytes for a large area<br />

(120 km x 240 km-) with a narrow spacing (one elevation<br />

value every 30 meters).<br />

6.0. Data Sources<br />

Although cartographic data bases have been evolving<br />

along with computer assisted cartographic techniques,<br />

most of <strong>the</strong> research has been in support of map sheet<br />

production. In order to create a tactical cartographic<br />

data base, it is necessary to first collect <strong>the</strong> digi<br />

tized data from existing charts, and <strong>the</strong>n to transform<br />

this collected data into some form that will support<br />

<strong>the</strong> requirement for rapid access. Experience has shown<br />

that such diverse distributors of source materials as<br />

<strong>the</strong> USGS, DMA and New York State Department of Trans<br />

portation Map Information Unit must be used in order to<br />

complete <strong>the</strong> collection process. This same experience<br />

has shown that <strong>the</strong> chart collection, digitization,<br />

transformation, and data base creation processes can<br />

require excessive expenditure of manpower and time.<br />

The problem of maintainability is compounded by <strong>the</strong><br />

scattered sources, and overly complicated collection<br />

process.<br />

83

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